botany research topics 2020

100+ Botany Research Topics [Updated 2024]

Botany, the scientific study of plants, holds the key to understanding the intricate and fascinating world of flora that surrounds us. As we delve into the realm of botany research, we uncover a vast array of botany research topics that not only contribute specifically to our scientific knowledge but also play an important role in addressing real-world challenges. 

In this blog, we will embark on a journey through the rich landscape of botany research, exploring various captivating topics that researchers are delving into.

How to Select Botany Research Topics?

Table of Contents

Selecting an appropriate and engaging botany research topic is a crucial step in the research process. Whether you are a student working on a thesis, a scientist planning a research project, or someone passionate about exploring the wonders of plant biology, the right choice of topic can significantly impact the success and enjoyment of your research. 

Here are some guidelines on how to select botany research topics:

• Identify Your Interests:
• Start by reflecting on your own personal interests within the field of botany. Consider the aspects of plant biology that fascinate you the most. 
• Whether it’s plant physiology, taxonomy, ecology, genetics, or any other subfield, choosing a topic aligned with your interests can make the research process more enjoyable.
• Review Literature:
• Conduct a thorough review and it will be of existing literature in botany. Explore recent research articles, journals, and books to identify gaps in knowledge, emerging trends, and areas where further investigation is needed. 
• This can help you find inspiration and identify potential research questions.
• Consider Relevance:
• Assess the relevance of your chosen topic to the current state of botany and its applications. Consider how your research could contribute to addressing real-world challenges, advancing scientific knowledge, or informing practical solutions. 
• Relevant research topics often garner more attention and support.
• Evaluate Feasibility:
• Evaluate all possible feasibility of your chosen topic in terms of available resources, time constraints, and research capabilities. 
• Consider the accessibility of study sites, the availability of equipment and materials, and the level of expertise required. A feasible research topic is one that aligns with your resources and constraints.
• Collaborate and Seek Guidance:
• Discuss your ideas with mentors, professors, or colleagues in the field. 
• Collaborative discussions can provide valuable insights, help refine your research questions, and guide you toward topics that align with current research priorities.
• Consider working with a professional academic editor to review your work after you’ve finished writing it.
• Explore Emerging Technologies:
• Consider incorporating emerging technologies and methodologies in your research. This not only adds a contemporary dimension to your study but also opens up new possibilities for exploration. 
• Technologies like CRISPR-Cas9, high-throughput sequencing, and remote sensing have revolutionized botany research.
• Think Interdisciplinary:
• Botany often intersects with various other disciplines, such as ecology, genetics, molecular biology, environmental science, and more. 
• Consider interdisciplinary approaches to your research, as this can lead to innovative and comprehensive insights.
• Address Global Challenges:
• Botany research can play a crucial role in addressing global challenges like climate change, food security, and biodiversity loss. 
• Choosing a topic that contributes to solving or mitigating these challenges adds societal relevance to your work.
• Explore Local Flora:
• If applicable, explore the flora of your local region. Investigating plant species native to your area can have practical implications for local conservation, biodiversity studies, and environmental management.
• Stay Inquisitive and Open-Minded:
• Keep an open mind and stay curious. Scientific research often involves unexpected discoveries, and being open to exploration can lead to novel and exciting findings. 
• Be willing to adapt your research questions based on your findings and new insights.

100+ Botany Research Topics For All Students

Plant physiology.

• The Role of Plant Hormones in Growth and Development
• Mechanisms of Photosynthesis: A Comprehensive Study
• Impact of Environmental Stress on Plant Physiology
• Water Use Efficiency in Plants: Regulation and Adaptation
• Nutrient Uptake and Transport in Plants
• Signaling Pathways in Plant Defense Mechanisms
• Regulation of Flowering Time in Plants
• Physiological Responses of Plants to Climate Change
• Role of Mycorrhizal Associations in Plant Nutrition
• Stress Tolerance Mechanisms in Halophytic Plants

Plant Taxonomy

• Phylogenetic Analysis of a Plant Family: Case Study
• Integrating Molecular Systematics in Plant Taxonomy
• Plant DNA Barcoding for Species Identification
• Revision of a Plant Genus: Taxonomic Challenges
• Cryptic Species in Plant Taxonomy: Detection and Implications
• Floristic Diversity in a Specific Geographic Region
• Evolutionary Trends in Angiosperms
• Ethnobotanical Contributions to Plant Taxonomy
• Application of GIS in Plant Taxonomy
• Conservation Status Assessment of Endangered Plant Species

Plant Ecology

• Ecosystem Services Provided by Plants
• Dynamics of Plant-Animal Interactions in a Habitat
• Impact of Invasive Plant Species on Native Flora
• Plant Community Composition Along Environmental Gradients
• Ecological Consequences of Plant-Pollinator Decline
• Microbial Interactions in the Rhizosphere
• Plant Responses to Fire: Adaptation and Recovery
• Climate Change Effects on Plant Phenology
• Restoration Ecology: Reintroducing Native Plants
• Plant-Soil Feedbacks and Ecosystem Stability

Plant Pathology

• Molecular Mechanisms of Plant-Pathogen Interactions
• Emerging Plant Diseases: Causes and Consequences
• Integrated Disease Management in Agriculture
• Fungal Pathogens: Diversity and Control Strategies
• Plant Immunity and Defense Mechanisms
• Resistance Breeding Against Viral Pathogens
• Bacterial Diseases in Crop Plants: Diagnosis and Management
• Impact of Climate Change on Plant Pathogen Dynamics
• Biocontrol Agents for Plant Disease Management
• Genetic Basis of Host Susceptibility to Plant Pathogens

Ethnobotany

• Traditional Medicinal Plants: Documentation and Validation
• Cultural Significance of Plants in Indigenous Communities
• Ethnobotanical Survey of a Specific Region
• Sustainable Harvesting Practices of Medicinal Plants
• Traditional Plant Use in Rituals and Ceremonies
• Plant-Based Foods in Indigenous Diets
• Ethnopharmacological Studies on Antimicrobial Plants
• Conservation of Ethnobotanical Knowledge
• Ethnobotanical Contributions to Modern Medicine
• Indigenous Perspectives on Plant Conservation

Genetic and Molecular Biology

• CRISPR-Cas9 Applications in Plant Genome Editing
• Epigenetics in Plant Development and Stress Response
• Functional Genomics of Plant Responses to Abiotic Stress
• Genetic Diversity in Crop Plants and its Conservation
• Genetic Mapping and Marker-Assisted Selection in Plant Breeding
• Genome Sequencing of Non-Model Plant Species
• RNA Interference in Plant Gene Regulation
• Comparative Genomics of Plant Evolution
• Genetic Basis of Plant Adaptation to Extreme Environments
• Plant Epigenome Editing: Methods and Applications

Plant Anatomy and Morphology

• Comparative Anatomy of C3 and C4 Plants
• Xylem and Phloem Development in Plants
• Leaf Anatomy and Adaptations to Photosynthesis
• Morphological Diversity in Plant Reproductive Structures
• Evolution of Floral Symmetry in Angiosperms
• Root Architecture and its Functional Significance
• Stem Cell Dynamics in Plant Meristems
• Comparative Morphology of Succulent Plants
• Tissue Regeneration in Plants: Mechanisms and Applications
• Wood Anatomy and Tree-Ring Analysis in Dendrochronology

Climate Change and Plant Responses

• Impact of Global Warming on Alpine Plant Communities
• Plant Responses to Elevated CO2 Levels
• Drought Tolerance Mechanisms in Plants
• Shifts in Plant Phenology Due to Climate Change
• Climate-Induced Changes in Plant-Pollinator Interactions
• Carbon Sequestration Potential of Forest Ecosystems
• Ocean Acidification Effects on Seagrass Physiology
• Plant Responses to Increased Frequency of Extreme Events
• Alpine Plant Adaptations to Harsh Environments
• Climate-Driven Changes in Plant Distribution and Biogeography

Emerging Technologies in Botany Research

• Application of Machine Learning in Plant Phenotyping
• Nanotechnology in Plant Science: Current Status and Future Prospects
• Metagenomics in Studying Plant Microbiomes
• Remote Sensing for Monitoring Plant Health
• High-Throughput Sequencing in Plant Genomics
• CRISPR-Based Gene Drives for Ecological Restoration
• Advances in Plant Imaging Techniques
• Synthetic Biology Approaches in Plant Engineering
• Augmented Reality Applications in Plant Biology Education
• Digital Herbariums: Integrating Technology in Plant Taxonomy

Misc Botany Research Topics

• Metabolic Pathways in Plant Secondary Metabolism: Regulation and Significance
• Population Genomics of Endangered Plant Species: Implications for Conservation
• Impact of Soil Microbes on Plant Health and Productivity
• Evolutionary Dynamics of Plant-Pathogen Coevolution: Insights from Molecular Data
• Application of CRISPR-Based Gene Editing for Improving Crop Traits
• Phytochemical Profiling of Medicinal Plants for Drug Discovery
• Investigating the Role of Epigenetic Modifications in Plant Stress Responses
• Role of Plant Volatile Organic Compounds (VOCs) in Ecological Interactions
• Biotic and Abiotic Factors Influencing Plant Microbiome Composition
• Molecular Basis of Plant-Microbe Symbiosis: Lessons from Nitrogen-Fixing Associations

How to Make Botany Research Successful?

Conducting successful botany research involves a combination of careful planning, effective execution, and thoughtful analysis. Whether you are a student, a researcher, or someone conducting independent studies, here are key tips to ensure the success of your botany research:

• Establish Clear Objectives: Clearly articulate the goals and objectives of your research. What specific inquiries do you intend to address? A well-defined research focus serves as a guiding framework, ensuring your efforts remain purposeful and on course.
• Conduct an In-Depth Literature Review: Immerse yourself in the existing body of literature within your field of study. Identify gaps, discern trends, and pinpoint areas where your research could contribute significantly. A thorough literature review lays a robust groundwork for shaping your research design.
• Choose an Appropriate Research Topic: Select a research topic that resonates with your interests, aligns with your expertise, and addresses the current needs of the scientific community. Ensure that the chosen topic is not only feasible but also harbors the potential for impactful outcomes.
• Develop a Sound Research Plan: Create a detailed research plan outlining the methodologies, timelines, and resources required. A well-structured plan helps in efficient execution and minimizes the risk of unforeseen challenges.
• Utilize Cutting-Edge Technologies: Stay updated with the latest technologies and methodologies in botany research. Incorporate advanced tools such as high-throughput sequencing, CRISPR-Cas9 , and remote sensing to enhance the precision and efficiency of your research.
• Collaborate and Seek Guidance: Collaborate with experts in the field, seek mentorship, and engage in discussions with colleagues. Networking and collaboration can provide valuable insights, guidance, and potential avenues for collaboration.
• Ensure Ethical Considerations: Adhere to ethical guidelines and standards in your research. Obtain necessary approvals for human subjects, follow ethical practices in plant experimentation, and ensure the responsible use of emerging technologies.
• Implement Robust Experimental Design: Design experiments with attention to detail, ensuring that they are replicable and provide statistically significant results. Address potential confounding variables and incorporate controls to enhance the reliability of your findings.
• Collect and Analyze Data Thoughtfully: Implement systematic data collection methods. Use appropriate statistical analyses to interpret your results and draw meaningful conclusions. Transparent and well-documented data analysis enhances the credibility of your research.
• Regularly Review and Adapt: Periodically review your progress and be open to adapting your research plan based on emerging findings. Flexibility and responsiveness to unexpected results contribute to a dynamic and successful research process.
• Communicate Your Research Effectively: Share your findings through publications, presentations, and other relevant channels. Effective communication of your research results contributes to the broader scientific community and enhances the impact of your work.
• Foster a Collaborative Research Environment: Encourage collaboration within your research team. A collaborative environment fosters creativity, diverse perspectives, and a collective effort towards achieving research goals.
• Contribute to Sustainable Practices: If your research involves fieldwork or plant collection, adhere to sustainable practices. Consider the impact on local ecosystems and strive to minimize any negative consequences.
• Stay Resilient: Research can have its challenges, setbacks, and unforeseen obstacles. Stay resilient, remain focused on your goals, and view challenges as opportunities for growth and learning.
• Celebrate Achievements and Learn from Failures: Acknowledge and celebrate your achievements, no matter how small. Learn from any setbacks or failures and use them as lessons to refine and improve your research approach.

In the vast and diverse field of botany research, scientists are continually unraveling the mysteries of the plant kingdom. From the intricate processes of photosynthesis to the challenges posed by emerging plant diseases and the potential of cutting-edge technologies, botany research is a dynamic and ever-evolving field. 

As we delve deeper into the green secrets of the plant world, our understanding grows, offering not only scientific insights but also solutions to address pressing global challenges such as food security, biodiversity loss, and climate change. 

The exploration of botany research topics is a journey of discovery, paving the way for a sustainable and harmonious coexistence with the plant life that sustains our planet.

Related Posts

Step by Step Guide on The Best Way to Finance Car

The Best Way on How to Get Fund For Business to Grow it Efficiently

Botany News

Top headlines, latest headlines.

• Ferns' Surprisingly Sweet Defense Strategy
• Symbiosis Origin and GE Crops
• Gene for Resilient 'Pixie' Corn
• What Makes Some Plant Groups So Successful?
• Orchids Aid Seedlings Through Fungal Networks
• Harnessing Energy On Circadian Rhythms
• Taller Corn Plants, Even in Poor Conditions
• Symbiotic Bacteria Communicate With Plants
• Climate Change and Food Production
• Legacy of Indigenous Stewardship of Camas

Earlier Headlines

Tuesday, may 21, 2024.

• How Plants 'mate' For Life and Repel Other Suitors

Friday, May 17, 2024

• Modern Plant Enzyme Partners With Surprisingly Ancient Protein
• Scientists Discover Mechanism of Sugar Signaling in Plants
• Plants Restrict Use of 'Tipp-Ex Proteins'

Thursday, May 16, 2024

• Natural Toxins in Food: Many People Are Not Aware of the Health Risks
• Bioengineered Enzyme Creates Natural Vanillin from Plants in One Step

Wednesday, May 15, 2024

• Regenerating Worms Have Genetic Control Over Their Algal Partners
• From Roots to Resilience: Investigating the Vital Role of Microbes in Coastal Plant Health
• Two Decades of Studies Suggest Health Benefits Associated With Plant-Based Diets
• Now We Know, What Gets Roots to Grow: Can Help in Future Droughts
• Iconic Baobabs: The Origin and Long-Distance Travels of Upside Down Trees

Monday, May 13, 2024

• Like Dad and Like Mum...all in One Plant
• Some Varieties of Annual Flowers Have a Place in Pollinator-Friendly Gardens
• Prostate Cancer Study: More Health Benefits from Plant-Based Diet

Friday, May 10, 2024

• Scientists Unlock Key to Breeding 'carbon Gobbling' Plants With a Major Appetite
• New Light Shed on Carboxysomes in Key Discovery That Could Boost Photosynthesis

Thursday, May 9, 2024

• Saturated Soils Could Impact Survival of Young Trees Planted to Address Climate Change

Wednesday, May 8, 2024

• New Record Holder for Smallest Dispersers of Ingested Seeds: Woodlice
• An Adjuvant Made in Yeast Could Lower Vaccine Cost and Boost Availability

Tuesday, May 7, 2024

• Free-Forming Organelles Help Plants Adapt to Climate Change

Friday, May 3, 2024

• Genomes of 'star Algae' Shed Light on Origin of Plants
• Plants Utilize Drought Stress Hormone to Block Snacking Spider Mites

Thursday, May 2, 2024

• For Microscopic Organisms, Ocean Currents Act as 'expressway' To Deeper Depths
• Wild Orangutan Treats Wound With Pain-Relieving Plant

Wednesday, May 1, 2024

• Marriage of Synthetic Biology and 3D Printing Produces Programmable Living Materials
• Calcium Can Protect Potato Plants from Bacterial Wilt
• Novel Genetic Plant Regeneration Approach Without the Application of Phytohormones

Tuesday, April 30, 2024

• Discovery of Mechanism Plants Use to Change Seed Oil Could Impact Industrial, Food Oils
• Unlocking the Genetic Mysteries Behind Plant Adaptation: New Insights Into the Evolution of a Water-Saving Trait in the Pineapple Family (Bromeliaceae)

Monday, April 29, 2024

• Fixin' To Be Flexitarian: Scrap Fish and Invasive Species Can Liven Up Vegetables

Friday, April 26, 2024

• AI Deciphers New Gene Regulatory Code in Plants and Makes Accurate Predictions for Newly Sequenced Genomes

Thursday, April 25, 2024

• Barley Plants Fine-Tune Their Root Microbial Communities Through Sugary Secretions
• Scientists Released Long-Term Data of Ground Solar-Induced Fluorescence to Improve Understanding of Canopy-Level Photosynthesis

Wednesday, April 24, 2024

• Artificial Intelligence Helps Scientists Engineer Plants to Fight Climate Change

Tuesday, April 23, 2024

• World's Chocolate Supply Threatened by Devastating Virus

Monday, April 22, 2024

• The Spiciness of Mustard May Depend on Soil Microbes

Wednesday, April 17, 2024

• Plant Sensors Could Act as an Early Warning System for Farmers
• Unique Field Study Shows How Climate Change Affects Fire-Impacted Forests
• Making Crops Colorful for Easier Weeding

Tuesday, April 16, 2024

• CO2 Worsens Wildfires by Helping Plants Grow
• Seed Ferns: Plants Experimented With Complex Leaf Vein Networks 201 Million Years Ago
• Twisted Pollen Tubes Induce Infertility

Monday, April 15, 2024

• How Blue-Green Algae Manipulate Microorganisms
• Tropical Forests Can't Recover Naturally Without Fruit-Eating Birds

Thursday, April 11, 2024

• Biofortified Rice to Combat Deficiencies
• Genetic Underpinnings of Environmental Stress Identified in Model Plant

Monday, April 8, 2024

• How Plants Adjust Their Photosynthesis to Changing Light
• Integrated Dataset Enables Genes-to-Ecosystems Research

Wednesday, April 3, 2024

• New Sunflower Family Tree Reveals Multiple Origins of Flower Symmetry

Sunday, March 31, 2024

• Combination of the Climate Crisis and Continued Deforestation May Result in Significant Damage to the Animal World

Thursday, March 28, 2024

• Researchers Discover Key Gene for Toxic Alkaloid in Barley
• Lyrebird Synchronizes Elements of Its Mating Dance

Wednesday, March 27, 2024

• Sweet Success: Sugarcane's Complex Genetic Code Cracked

Tuesday, March 26, 2024

• Researchers Find Energy Development and Tree Encroachment Impact Wyoming Pronghorn
• New Maps Help Decision-Makers Factor Albedo Into Tree-Planting Decisions
• Discovery of Amino Acid Unveils How Light Makes Plants Open

Monday, March 25, 2024

• Seeing the Forest for the Trees: Species Diversity Is Directly Correlated With Productivity in Eastern U.S. Forests
• New Route to Recyclable Polymers from Plants
• 'Winners and Losers' As Global Warming Forces Plants Uphill

Thursday, March 21, 2024

• Rose Essential Oil: A Safe Pesticide for Organic Agriculture
• Decoding the Plant World's Complex Biochemical Communication Networks

Wednesday, March 20, 2024

• Across Oceans and Millennia: Decoding the Origin and History of the Bottle Gourd
• Researchers Investigate How Freshwater Diatoms Stay in the Light

Tuesday, March 19, 2024

• Fairy Circles: Plant Water Stress Causes Namibia's Gaps in Grass
• Why Do Tree Frogs Lay Their Eggs on the Ground?

Monday, March 18, 2024

• Cacao Plants' Defense Against Toxic Cadmium Unveiled

Wednesday, March 13, 2024

• Simple Trick Could Improve Accuracy of Plant Genetics Research
• Summer Solstice Triggers Synchronized Beech Tree Reproduction Across Europe
• Study Brings Scientists a Step Closer to Successfully Growing Plants in Space
• Exploring Arctic Plants and Lichens: An Important Conservation Baseline for Nunavut's Newest and Largest Territorial Park

Tuesday, March 12, 2024

• Alaska Dinosaur Tracks Reveal a Lush, Wet Environment
• Rainforest's Next Generation of Trees Threatened 30 Years After Logging

Thursday, March 7, 2024

• Earth's Earliest Forest Revealed in Somerset Fossils

Wednesday, March 6, 2024

• The World's Most Prolific CO2-Fixing Enzyme Is Slowly Getting Better
• Marine Algae Implants Could Boost Crop Yields
• Invasive Plant Time Bombs: A Hidden Ecological Threat

Tuesday, March 5, 2024

• Microalgae With Unusual Cell Biology
• Plant Lavender, Marjoram and Ivy on Your Green Wall to Clean Up the Air

Monday, March 4, 2024

• An Inside Look at Beech Tree Disease
• An Evolutionary Mystery 125 Million Years in the Making
• Photosynthetic Secrets Come to Light

Saturday, March 2, 2024

• In Wake of Powerful Cyclone, Remarkable Recovery of Pacific Island's Forests

Friday, March 1, 2024

• Light Into the Darkness of Photosynthesis
• A New Plant's Name That Tells a Story
• Convergent Evolution of Algal CO2-Fixing Organelles

Thursday, February 29, 2024

• Cyber-Physical Heating System May Protect Apple Blossoms in Orchards
• Refrigerate Lettuce to Reduce Risk of E. Coli Contamination
• Lake Ecosystems: Nitrogen Has Been Underestimated
• Small Dietary Changes Can Cut Your Carbon Footprint by 25%

Wednesday, February 28, 2024

• Creepy Crawlies Protect Apples When Flowers Are Planted on Farms

Tuesday, February 27, 2024

• Walleye Struggle With Changes to Timing of Spring Thaw
• Scientists Use Blue-Green Algae as a Surrogate Mother for 'meat-Like' Proteins
• Low-Temperature Plasma Used to Remove E. Coli from Hydroponically Grown Crops

Friday, February 23, 2024

• Common Plant Could Help Reduce Food Insecurity
• Biomolecular Condensates -- Regulatory Hubs for Plant Iron Supply
• Altering the Circadian Clock Adapts Barley to Short Growing Seasons

Wednesday, February 21, 2024

• Modeling Tree Masting

Tuesday, February 20, 2024

• 'The Future Is Fungal': New Research Finds That Fungi That Live in Healthy Plants Are Sensitive to Climate Change
• Photosynthetic Mechanism of Purple Sulfur Bacterium Adapted to Low-Calcium Environments

Monday, February 19, 2024

• Pollinator's Death Trap Turns Into Nursery
• LATEST NEWS
• Top Science
• Top Physical/Tech
• Top Environment
• Top Society/Education
• Health & Medicine
• Mind & Brain
• Living Well
• Space & Time
• Matter & Energy
• Computers & Math
• Plants & Animals
• Agriculture & Food
• Beer and Wine
• Bird Flu Research
• Genetically Modified
• Pests and Parasites
• Cows, Sheep, Pigs
• Dolphins and Whales
• Frogs and Reptiles
• Insects (including Butterflies)
• New Species
• Spiders and Ticks
• Veterinary Medicine
• Business & Industry
• Biotechnology and Bioengineering
• CRISPR Gene Editing
• Food and Agriculture
• Endangered Animals
• Endangered Plants
• Extreme Survival
• Invasive Species
• Wild Animals
• Education & Learning
• Animal Learning and Intelligence
• Life Sciences
• Behavioral Science
• Biochemistry Research
• Biotechnology
• Cell Biology
• Developmental Biology
• Epigenetics Research
• Evolutionary Biology
• Marine Biology
• Mating and Breeding
• Molecular Biology
• Microbes and More
• Microbiology
• Zika Virus Research
• Earth & Climate
• Fossils & Ruins
• Science & Society

Strange & Offbeat

• 'Missing' Early Sea Sponges Discovered
• Younger Classmates Diagnosed With ADHD
• Upending Theory of Milky Way Formation
• Black Holes a Byproduct of Dark Matter?
• Marine Cyanobacteria Can Communicate
• 'Tweezer-Like' Bionic Tools Feel Right
• Odd Planet-Forming Disks Around Low-Mass Stars
• Toward Blood Stem Cell Self-Renewal
• Restored Hearing and Speech in Kids Born Deaf
• Babies and AI Both Learn Key Foundation Models

Trending Topics

• How it works

Published by Nicolas at January 17th, 2024 , Revised On January 23, 2024

A Breakdown Of Common Topics In Botany Papers

Botany, the scientific study of plants, encompasses a diverse array of disciplines that delve into the intricacies of plant life. As a cornerstone of biological sciences, botany provides invaluable insights into the fascinating world of flora, from the microscopic structures of cells to the vast ecosystems where plants thrive. In this blog, we will discuss the most important topics in botany papers at universities in Canada . 

Table of Contents

Botany As A Scientific Discipline

Botany, also known as plant biology, is a branch of biology that focuses on the study of plants, including algae, fungi, mosses, ferns, conifers, and flowering plants. The discipline encompasses a broad spectrum of topics, ranging from the molecular and cellular levels to ecological and evolutionary aspects. Botanists examine plant structure, function, growth, reproduction, and their interactions with the environment.

Botany research papers play a pivotal role in advancing our understanding of the plant kingdom. These scholarly articles serve as conduits for sharing groundbreaking research, new discoveries, and innovative methodologies within the scientific community. Through the dissemination of knowledge in peer-reviewed journals, botany papers contribute to the collective body of information that shapes the trajectory of botanical science.

The importance of a botany thesis or dissertation extends beyond academic circles, influencing agricultural practices, environmental conservation, pharmaceutical discoveries, and even our basic understanding of life on Earth. 

Taxonomy, a fundamental aspect of botany, is the science of classifying and naming living organisms. In the context of plants, taxonomy involves categorizing them based on shared characteristics, relationships, and evolutionary history. The systematic organization provided by taxonomy serves as a crucial framework for understanding plant diversity, aiding in communication among scientists and facilitating further research.

In botany research paper format , taxonomy is a cornerstone that underpins various studies, providing a structured approach to exploring and documenting the vast array of plant species. By classifying plants into groups based on shared traits, researchers can unravel the evolutionary relationships among different taxa, contributing to our understanding of plant evolution and biodiversity.

Phylogenetic Analysis

Phylogenetic analysis is a central theme in botany papers that explore the evolutionary relationships between plants. This approach involves constructing phylogenetic trees or cladograms, visually representing the evolutionary history and genetic relatedness of different plant species. Molecular data, such as DNA sequences, are often used to decipher these relationships, offering insights into the branching patterns and common ancestors of plants.

Systematics And Nomenclature

Systematics involves the study of the diversity of organisms and their evolutionary relationships. In botany papers, systematic research often focuses on classifying plants into hierarchical categories based on shared characteristics. This includes the establishment of rules and principles for naming and classifying plants, known as nomenclature.

Botanists employ a standardized system of nomenclature, governed by the International Code of Nomenclature for algae, fungi, and plants (ICN), to assign scientific names to plant species. 

Taxonomy Research Paper Topics

• Integration of Morphological and Molecular Data in Modern Taxonomy
• The Impact of Next-Generation Sequencing on Resolving Taxonomic Uncertainties
• Taxonomic Revisions: Case Studies in Reevaluating Species Boundaries
• The Role of DNA Barcoding in Identifying and Classifying Biodiversity
• Challenges and Opportunities in Integrating Traditional and Molecular Taxonomy
• Evolutionary Trends in Taxonomic Diversification: Lessons from Key Plant Families
• Exploring Cryptic Species: Hidden Diversity in Taxonomic Classification
• The Influence of Environmental Factors on Taxonomic Variation in Microorganisms
• Taxonomy and Conservation: Prioritizing Species for Protection
• Phylogenetic Reconstruction and Biogeography: Tracing Evolutionary History

Plant Physiology

Plant physiology is the branch of botany that explores the internal processes and mechanisms governing the life and functioning of plants. It discusses the physiological activities that occur within plant cells, tissues, and organs. Understanding plant physiology is essential for unravelling the fundamental processes that sustain plant life and influence growth, development, and responses to environmental stimuli.

The physiological processes in plants are diverse and interconnected, involving molecular, biochemical, and biophysical mechanisms. These processes include photosynthesis, respiration, water and nutrient uptake, hormonal regulation, and many others. Each contributes to the overall health and functionality of plants, allowing them to adapt to changing conditions and thrive in various environments.

Photosynthesis And Respiration

Photosynthesis, a fundamental process in plant physiology, involves the conversion of light energy into chemical energy, primarily in the form of glucose. This process occurs in chloroplasts, where pigments such as chlorophyll capture sunlight and convert it into chemical energy through a series of complex biochemical reactions.

Water And Nutrient Uptake

Water and nutrient uptake are vital physiological processes that sustain plant life. Roots play a crucial role in absorbing water and essential nutrients from the soil, transporting them through the plant’s vascular system to support various physiological functions. 

Researchers investigate how plants adapt to varying nutrient levels, the impact of mycorrhizal associations on nutrient uptake, and the strategies plants employ to cope with water stress. These studies contribute not only to our understanding of plant physiology but also have implications for optimizing agricultural practices and addressing challenges related to water and nutrient availability in different ecosystems.

Hormonal Regulation In Plants

Hormonal regulation is a complex and tightly controlled aspect of plant physiology that influences growth, development, and responses to environmental stimuli. Plant hormones, such as auxins, gibberellins, cytokinins, abscisic acid, and ethylene, play key roles in coordinating various physiological processes.

Plant Physiology Research Paper Topics

• Photosynthetic Efficiency in Response to Environmental Stressors: A Comparative Study
• Mechanisms of Water Transport in Plants: From Roots to Leaves
• The Role of Plant Hormones in Coordinating Growth and Development
• Metabolic Adaptations of Plants to Nutrient Limitation: Insights from Molecular Studies
• Stomatal Regulation and Water Use Efficiency in Crops: Implications for Agriculture
• Cellular Signaling in Plant Responses to Abiotic Stress: Unraveling the Molecular Mechanisms
• Impact of Elevated Carbon Dioxide Levels on Plant Physiology and Growth
• Nitrogen Metabolism in Plants: Integration of Nitrate and Ammonium Assimilation
• Role of Phytochromes in Plant Photomorphogenesis: From Seed Germination to Flowering
• Understanding the Molecular Basis of Plant-Pathogen Interactions: Host Defense Mechanisms

Ecology And Biodiversity

Ecology, a pivotal branch of botany, examines the relationships between organisms and their environments. In the context of plants, ecological studies shed light on how they interact with other living organisms, the physical and chemical characteristics of their habitats, and the impact of environmental factors on their growth and survival. Understanding the connections between plants and their surroundings is essential for elucidating ecological processes and conserving biodiversity.

Plants, as primary producers, play a foundational role in ecosystems by converting sunlight into energy through photosynthesis. Their interactions with soil microorganisms, herbivores, pollinators, and other plants contribute to the dynamic balance of ecosystems. Ecological studies in botany explore the flow of energy and nutrients within ecosystems, the coevolution of plants with other organisms, and the broader impact of these interactions on biodiversity.

Ecosystem Interactions

Botany papers frequently delve into the complex interactions between plants and their biotic and abiotic environments. Ecosystem interactions encompass a wide range of topics, including plant-animal interactions, mutualistic relationships, competition for resources, and the role of plants in shaping their ecosystems.

Research in this area may focus on the relationships within plant communities, exploring how different species coexist and compete for resources. Additionally, studies may investigate the role of plants in providing habitat and sustenance for other organisms, such as pollinators, herbivores, and decomposers. 

Conservation Biology

Conservation biology is a critical facet of botany that addresses the preservation of plant species, ecosystems, and biodiversity. Botany papers in conservation biology explore the threats facing plant populations, the impact of habitat loss, climate change, and invasive species, and strategies for mitigating these challenges.

Researchers may investigate the distribution and abundance of rare or endangered plant species, assess the effectiveness of protected areas, and develop conservation plans to safeguard plant diversity. Conservation-oriented botany papers contribute valuable insights into the sustainable management of natural resources, restoration ecology, and the protection of plant species facing the risk of extinction.

Plant Adaptations To Environmental Factors

Plants have evolved a myriad of adaptations to cope with diverse environmental conditions. Botany papers exploring plant adaptations delve into the mechanisms that enable plants to thrive in specific habitats, resist environmental stressors, and respond to changing conditions.

Topics may include physiological adaptations, such as drought tolerance and salt resistance, as well as morphological adaptations, like specialized root structures or leaf modifications. 

The research paper we write have:

• Precision and Clarity
• Zero Plagiarism
• High-level Encryption
• Authentic Sources

Ecology And Biodiversity Research Paper Topics

Genetics and genomics.

Plant genetics and genomics constitute a fascinating area of botany that explores the hereditary traits and molecular mechanisms governing plant development, evolution, and adaptation. Genetics delves into the study of individual genes, their inheritance patterns, and the variations that occur within populations, while genomics encompasses the detailed analysis of an organism’s entire set of genes (genome) and their functions.

Genetic Diversity

Genetic diversity is a fundamental aspect of plant biology that explores the variety of genetic material within a population or species. Botany papers often delve into the factors influencing genetic diversity, such as reproductive mechanisms, population size, and environmental pressures. Researchers study the distribution of genetic variations among plant populations to assess their adaptability, resilience, and potential responses to environmental changes.

Understanding genetic diversity is crucial for plant conservation, breeding programs, and the development of crops with improved traits. Botany papers in this domain contribute to our knowledge of the factors shaping genetic diversity and its implications for the long-term survival and evolution of plant species.

Molecular Markers And Genetic Mapping

Molecular markers and genetic mapping play a pivotal role in plant genetics by aiding in the identification and mapping of specific genes or genomic regions associated with particular traits. Botany papers may focus on the development and application of molecular markers, such as DNA sequences or protein variants, to track genetic variations within plant populations.

Genetic mapping involves creating maps that illustrate the locations of genes on a plant’s chromosomes. These maps provide insights into the inheritance patterns of traits and assist in the selection of desirable traits for breeding programs. Botany papers in this area contribute to the refinement of genetic maps, the discovery of quantitative trait loci (QTLs), and the advancement of marker-assisted breeding techniques.

Genetically Modified Organisms (GMOs)

The development and application of genetically modified organisms (GMOs) in agriculture and research are prominent topics in plant genetics. Botany papers related to GMOs explore the introduction of foreign genes into plant genomes to confer specific traits, such as resistance to pests, tolerance to environmental stress, or improved nutritional content.

Researchers in this field investigate the molecular mechanisms behind genetic modifications, assess the potential environmental and ecological impacts of GMOs, and explore ethical considerations associated with their use. Botany papers contribute to the ongoing dialogue surrounding the development and regulation of GMOs, addressing concerns related to biodiversity, food security, and the coexistence of genetically modified and non-modified crops.

Genetics And Genomics Research Paper Topics

• Genome-Wide Association Studies (GWAS): Applications in Unraveling Complex Traits
• CRISPR/Cas9 Technology: Current Advances and Ethical Implications in Genetic Engineering
• Functional Genomics: Integrating Genotype and Phenotype for a Comprehensive Understanding
• Epigenetic Modifications and Their Influence on Gene Expression in Development and Disease
• Population Genomics: Tracking Genetic Variation Across Different Populations
• Genetic Basis of Human Diseases: Insights from Genomic Medicine
• Comparative Genomics of Model Organisms: Unraveling Evolutionary Relationships
• The Role of Non-Coding RNAs in Gene Regulation and Genome Function
• Evolutionary Genomics: Studying Genetic Changes Over Geological Time Scales
• Personalized Genomics: Tailoring Medical Treatments Based on Individual Genetic Profiles

Plant Pathology

Plant pathology is a specialized field within botany that focuses on the study of plant diseases, their causes, and their impact on plant health and productivity. Just as animals can suffer from diseases, plants are susceptible to various pathogens, including fungi, bacteria, viruses, nematodes, and other microorganisms. Plant diseases can manifest as visible symptoms, such as wilting, discoloration, lesions, and deformities, ultimately affecting plant growth, development, and yield.

Identification And Control Of Plant Diseases

Botany papers in plant pathology often focus on the identification and control of plant diseases. Identification involves recognizing the causal agents of diseases, understanding the symptoms they induce, and distinguishing between different types of diseases. Researchers use a combination of field observations, laboratory tests, and molecular techniques to accurately identify pathogens and diagnose diseases.

Interactions Between Plants And Pathogens

The interactions between plants and pathogens form a central theme in botany papers related to plant pathology. Researchers delve into the molecular and biochemical mechanisms that govern the recognition and response of plants to invading pathogens. This includes the study of plant defence mechanisms, the activation of immune responses, and the ways in which pathogens evade or suppress plant defences.

Plant Pathology Research Paper Topics

• Emerging Plant Pathogens: Investigation and Management Strategies
• Role of Fungicides in Controlling Crop Diseases: Efficacy and Environmental Impact
• Molecular Mechanisms of Plant-Pathogen Interactions: Insights into Disease Resistance
• Epidemiology of Plant Viruses: Spread, Impact, and Control Measures
• Biological Control of Plant Pathogens: Harnessing Microbial Antagonists
• Genetic Resistance in Plants: Breeding for Disease Resistance in Crops
• Impact of Climate Change on Plant Disease Dynamics and Distribution
• Understanding Soil-Borne Pathogens: Management Approaches and Soil Health
• Emergence and Evolution of Fungal Pathogens: Genetic Diversity and Adaptation
• Integrated Disease Management in Agriculture: Combining Biological, Chemical, and Cultural Strategies

Ethnobotany

Ethnobotany is a multidisciplinary field that explores the relationships between plants and people, particularly focusing on the traditional knowledge and uses of plants by different cultures, especially indigenous communities. This interdisciplinary approach combines elements of anthropology, botany, ecology, and pharmacology to investigate how plants play a significant role in the cultural, spiritual, economic, and medicinal aspects of human societies.

The relevance of ethnobotany lies in its ability to preserve and document traditional ecological knowledge (TEK) held by indigenous and local communities. By understanding the traditional uses of plants, ethnobotanists contribute to the conservation of biodiversity, sustainable resource management, and the recognition of indigenous rights. Ethnobotanical studies also provide valuable insights into the potential applications of plant resources in various fields, including medicine, agriculture, and cultural practices.

Traditional Uses Of Plants By Indigenous Communities

Botany papers in ethnobotany often explore the traditional uses of plants by indigenous communities. Researchers delve into the rich tapestry of knowledge passed down through generations, documenting the uses of plants for food, shelter, clothing, tools, and various cultural practices. Ethnobotanical studies aim to catalogue and understand the diversity of plant uses in different societies, shedding light on the sustainable harvesting practices and conservation strategies employed by indigenous groups.

Through fieldwork and interviews with local communities, botany papers in this area contribute to the preservation of traditional knowledge, fostering collaboration between scientists and indigenous peoples. This interdisciplinary approach helps bridge the gap between scientific understanding and conventional wisdom, promoting the sustainable use of plant resources.

Medicinal Plants And Their Properties

A prominent focus within ethnobotany is the study of medicinal plants and their properties. Indigenous cultures have relied on plants for centuries to address various health and well-being needs. Botany papers in this field investigate the medicinal uses of plants, exploring the active compounds, therapeutic properties, and cultural significance associated with traditional healing practices.

Researchers may conduct pharmacological studies to validate the efficacy of medicinal plants, identifying potential compounds for drug development. Additionally, botany papers in ethnobotany contribute to the understanding of how different cultures approach healthcare, emphasizing the importance of integrating traditional medicine with modern healthcare practices for holistic and culturally sensitive healthcare strategies.

Botany Research Paper Topics

Here is a list of thirty botany research paper topics to help you start your journey in research.

• Impact of Climate Change on Plant Physiology: A Molecular Perspective
• Role of Mycorrhizal Fungi in Plant Nutrient Uptake and Health
• Genetic Modification of Crops for Enhanced Resistance to Pests and Diseases
• Exploring the Diversity of Plant Secondary Metabolites and Their Medicinal Properties
• Molecular Mechanisms of Plant Adaptation to Abiotic Stress
• The Ecology and Conservation of Endangered Plant Species
• Effects of Urbanization on Plant Biodiversity in Metropolitan Areas
• The Evolutionary Significance of Seed Dispersal Mechanisms in Plants
• Understanding the Interactions Between Plants and Insect Pollinators
• Applications of CRISPR/Cas9 Technology in Plant Genome Editing
• Role of Plant Hormones in Growth and Development
• Investigating the Impact of Invasive Plant Species on Native Ecosystems
• Phylogenetic Analysis of Medicinal Plants: Unraveling Evolutionary Relationships
• Study of Plant-Microbe Interactions in Rhizosphere Ecology
• The Role of Plants in Phytoremediation of Soil Contaminants
• Comparative Analysis of Plant Adaptations in Arid and Rainforest Environments
• Molecular Basis of Plant-Microbe Communication in Symbiotic Relationships
• Exploring the Genetic Basis of Plant Resistance to Herbivores
• Effects of Light Pollution on Plant Physiology and Growth
• Role of Epigenetics in Plant Development and Stress Response
• Analyzing the Impact of Fungal Pathogens on Agricultural Crop Yields
• Phytochemical Analysis and Pharmacological Potential of Ethnobotanical Plants
• Investigating the Influence of Plant Root Microbiome on Soil Health
• The Role of Plants in Carbon Sequestration and Climate Change Mitigation
• Comparative Genomics of C4 and CAM Plants: Unraveling Photosynthetic Strategies
• Molecular Basis of Plant Immune Responses to Pathogens
• Biotechnological Approaches for Sustainable Agriculture: Focus on Crop Improvement
• The Relationship Between Plant Diversity and Ecosystem Stability
• The Impact of Agricultural Practices on Soil Microbial Diversity and Plant Health
• Using Remote Sensing Technology for Monitoring and Managing Plant Ecosystems

Frequently Asked Questions

What is the citation style for the canadian journal of botany.

The Canadian Journal of Botany follows the citation style outlined in the Canadian Guide to Uniform Legal Citation (McGill Guide). It provides guidelines for citing legal and academic sources, ensuring consistency and clarity in citations for articles and papers.

What are journals in botany?

Journals in botany are periodical publications that disseminate original research, reviews, and scholarly articles related to plant biology. These journals serve as platforms for scientists and researchers to share their findings, advancements, and insights within the field of botany.

Where can I study botany in Ontario?

In Ontario, you can study botany at various institutions. Some options include the University of Toronto, McMaster University, University of Guelph, and York University. Check their biology or life sciences departments for specific botany-related programs and courses.

What is the impact factor of the American Journal of Botany?

American Journal of Botany boasts a strong impact factor of 3.325 (2023), placing it among the top journals in its field.

You May Also Like

Should you use MLA or APA citation style in your dissertation, thesis, or research paper? Choose by reading this comprehensive blog.

Find out if you need permission to publish your dissertation in canada. Understand copyright, university rules, and third-party content.

Learn everything about meta synthesis literature review in this comprehensive guide. From definition and process to its types and challenges.

Ready to place an order?

USEFUL LINKS

Learning resources, company details.

• How It Works

Automated page speed optimizations for fast site performance

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals

Plant physiology articles from across Nature Portfolio

Plant physiology is a sub-discipline of botany concerned with the physical, chemical and biological functioning of plants.

Latest Research and Reviews

Reply to: Critical comment on the assumptions leading to 24-chain microfibrils in wood

• Hwan-Ching Tai
• Cheng-Si Tsao
• Jer-Horng Lin

Silicon–calcium fertilizer increased rice yield and quality by improving soil health

Central transcriptional regulator controls photosynthetic growth and carbon storage in response to high light

Researchers identify unique transcriptional regulation that controls photosynthetic response, growth and biochemical carbon storage in high light for two variants of the same algae species, offering a glimpse into diel control of plant and crop yields.

• Seth Steichen
• Arnav Deshpande
• Lieve M. L. Laurens

Biosynthesis of copper nanoparticles using Solenostemma argel and their effect on enhancing salt tolerance in barley plants

• Hassan O. Shaikhaldein
• Fahad Al-Qurainy
• Abdulrahman Al-Hashimi

Thiourea improves yield and quality traits of Brassica napus L. by upregulating the antioxidant defense system under high temperature stress

• Muhammad Ahmad
• Ejaz Ahmad Waraich
• Mohamed S. Elshikh

High temperature and nib acidification during cacao-controlled fermentation improve cadmium transfer from nibs to testa and the liquor’s flavor

• Ivan D. Camargo
• Lucero G. Rodriguez-Silva
• Lucas F. Quintana-Fuentes

News and Comment

The importance of early human choices of wild plants in determining crop physiology

Leaf ecophysiological traits of crops are primarily inherited from their wild progenitors, challenging the conventional assumption that the origins of fast physiology lie only in early domestication and modern breeding.

How to establish a GAPLESS Casparian strip

To control the movement of water and nutrients, vascular plants seal the paracellular space between adjacent endodermal cells with a tight junction-like complex comprising the Casparian strip and Casparian strip membrane domain. In rice, GAPLESS proteins mediate the attachment of these two components and enable nutrient homeostasis.

• Milica Nenadić
• Joop E. M. Vermeer

Opening the gates

A new study reveals that epigenetic mechanism mediates temperature control of callose synthase expression to regulate opening of plasmodesmata and facilitate bud sprouting in lilies.

• Rishikesh P. Bhalerao

The glycerate transporter NPF8.4 links photorespiration and nitrogen flux in plants

Photorespiration is known to be involved in carbon flux in plants, enabling the carbon lost during RuBisCO oxygenation to be recovered. We show that NPF8.4 is a transporter responsible for sequestering the photorespiratory carbon intermediate glycerate into vacuoles during nitrogen depletion, elucidating a novel function for photorespiration in nitrogen flux.

Two bHLH transcription factors affect sprouting by regulating the level of ABA

For plants, the decision to germinate is a gamble on their subsequent survival. Xu et al. have now discovered a mechanism that determines the choice between germination and dormancy by regulating the level of ABA.

• Hideki Yoshida
• Makoto Matsuoka

Two nitrate sensors, how many more?

Nitrate is a nutrient and a signal. Membrane protein NRT1.1 reflects this duality as both a nitrate transporter and sensor. A new perception mechanism has just been discovered: transcription factor NLP7 is also a nitrate sensor. Thus, two distinct but interacting systems perceive nitrate. Are there others?

• Jordan Courrèges-Clercq
• Gabriel Krouk

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Botanists Use Machine Learning to Accelerate Research

A new artificial intelligence program called ARADEEPOPSIS will help botanists rapidly classify plant phenotypes.

A team of scientists in Austria has created a new, user-friendly artificial intelligence program to speed up their research by automating the analysis of huge numbers of plant images. They made the initial version of the source code publicly available in April 2020.

The study of plants involves identifying both their genotype (genetic makeup) and their phenotype (observable physical characteristics). Accessing the genomic sequence of an organism is a fundamental part of the study of biology. It allows researchers to make connections between a certain phenotype, such as height or color, and the genes responsible for it, says Patrick Hüther, a scientist who was then at the Gregor Mendel Institute of Molecular Plant Biology (GMI) at the Austrian Academy of Sciences in Vienna (the team is now at Ludwig-Maximilians University in Munich). Hüther is co-lead author of a research article on the development of this new artificial intelligence program, dubbed “ARADEEPOPSIS.”

Weekly Newsletter

Get your fix of JSTOR Daily’s best stories in your inbox each Thursday.

Privacy Policy   Contact Us You may unsubscribe at any time by clicking on the provided link on any marketing message.

Phenotyping plants is an essential part of agricultural, environmental, and pharmaceutical research.

With an increasing world population and the looming challenges of climate change, perfecting the science of growing food is more important than ever. Farm operators are well acquainted with influencing plant traits through a combination of genetic analysis and phenotyping in the field to produce desired characteristics in their crops. Although phenotyping is an increasing focus in agriculture, at least one study notes there’s also a growing need for large amounts of phenotype data to be processed more quickly—and in a format that researchers can easily interpret.

Likewise, understanding plants’ relationship to their habitat contributes to scientists’ knowledge about the environment. For example, one study found that the differences found in the phenotype and genotype of a plant that grows on both the coast and in interior areas do not necessarily correlate with the plant’s location. Biologists also use plants to study human diseases. Researchers have developed plant models that can predict the genes involved in human congenital diseases by comparing the plant phenotypes to phenotypes in humans and other species, identifying nonobvious similarities.

Depending on the scope of a study, collecting genotype and phenotype data can result in a mountain of information, particularly because plant development is often studied over a period of weeks or months. But, in terms of accuracy and efficiency, the technology that decodes plant DNA has far outstripped the tech that catalogs plant images. The lopsided data collection methods can result in a “ phenotype bottle neck ”—a backlog of thousands of images waiting to be analyzed. This bottleneck, in turn, delays researchers’ ability to analyze the data and draw conclusions.

In 2018, scientists from GMI started developing their own solution to this problem—an easy-to-use software program that could quickly process large numbers of plant images and account for color variations and other differences among plants specimens.

The name “ARADEEPOPSIS” comes from Arabidopsis Deep-Learning-Based Optimal Semantic Image Segmentation. “Arabidopsis” ( Arabidopsis thaliana ) is a fast-growing plant frequently used as a model organism by researchers. “Deep learning” refers to a teachable, multi-layered type of artificial intelligence inspired by the function of the human brain that spots patterns and interprets data.

The impetus initially came from GMI researcher Niklas Schandry’s own phenotype bottleneck, when he found himself faced with 150,000 plant images to analyze as part of a study to understand how different types of soil affect the way plants grow. Existing image analysis programs could quickly process the images but could only identify the plants’ green areas. This limitation was a problem since Schandry’s research found that certain soil types caused plants to turn yellow and brown, he explains.

Going through thousands of images to identify even a small set of plant characteristics could easily take a botanist weeks or months. “It’s a very dull task and hard to do reliably,” Schandry notes.

Then Hüther, Schandry’s fellow scientist at GMI, happened to read a Google AI blog post on semantic image segmentation, which assigns a descriptive label to every pixel in an image. Fortunately, Google made the semantic image segmentation model publicly available, so Hüther started playing around with the code. Ultimately, he repurposed the code for plant phenotyping by teaching the software how to identify Arabidopsis specimens. “There was a lot of trial and error at first, but eventually I figured out how to turn it into an end-to-end pipeline that also other researchers can use to analyze their images,” says Hüther.

Using deep learning methodology, ARADEEPOPSIS accurately analyzes Arabidopsis rosettes—the plant’s circular arrangement of leaves as seen when viewed from overhead—regardless of the plant’s color variations. Importantly for many botanists’ work, ARADEEPOPSIS can reliably distinguish between healthy and unhealthy leaves. The program also takes into account variations in plant appearance, image quality, and background composition.

So, how much time and effort can ARADEEPOPSIS save researchers? Quite a bit.

Hüther estimates that, depending on the computer hosting it, ARADEEPOPSIS can analyze 100,000 images in one day, which includes extracting a total of 78 phenotype-related parameters from each image. If an individual takes 10 minutes to identify 78 phenotypic parameters for a single image, that person will need to work 40 hours a week for approximately eight years to complete the analysis of 100,000 images, he says.

Not that any researchers in their right minds would take on such a workload. Programs to automate phenotyping for large numbers of plant images already do exist, including PlantCV, open-source software developed by the Donald Danforth Plant Science Center in St. Louis. However, PlantCV requires users to have some computer programming expertise, points out Hüther.

“One of our main goals really was to build something that was very accessible and easy to use and we thus focused on full automation, something that the machine learning methodology enabled us to achieve,” he says. ARADEEPOPSIS “merely requires input images of plants and returns a rather huge table with measurements along with a visual presentation of the result, allowing for quick and easy quality control.”

Hüther, Schandry, two GMI colleagues, and a colleague from the Max Planck Institute of Developmental Biology in Tübingen, Germany, published an article about developing ARADEEPOPSIS in the scientific journal The Plant Cell in December 2020. They made the first version of the source code publicly available on Github in early 2020.

Currently, ARADEEPOPSIS is configured to analyze Arabidopsis plants and other members of the same plant family, but the machine learning program can be trained to analyze other types of plants and adapted to other researchers’ needs, says Schandry. Training ARADEEPOPSIS proved to be a very time-consuming task that included teaching the machine learning program to differentiate between “green,” “not green” and “partially green,” he says.

Potential future applications of ARADEEPOPSIS could be wide-ranging, according to Anne C. Rea, assistant features editor at The Plant Cell . ARADEEPOPSIS is customizable and more accurate than existing tools. It is also highly versatile because it can handle extremely large numbers of diverse images of varying quality and background compositions and performs a wide variety of different types of measurements, Rea writes in her overview of ARADEEPOPSIS for the journal.

Schandry and Hüther and are also looking at future possibilities. Schandry says he hopes to develop a mobile version of ARADEEPOPSIS, which would be very useful in the field for botanists.

“I am very eager to see where this will lead to, hopefully beyond the model plant Arabidopsis thaliana ,” adds Hüther. “Even if that means we have to find a new name for the software.”

Support JSTOR Daily! Join our new membership program on Patreon today.

JSTOR is a digital library for scholars, researchers, and students. JSTOR Daily readers can access the original research behind our articles for free on JSTOR.

Get Our Newsletter

More stories.

• Aurorae and the Green of the Night Sky

• IceCube Detector Confirms Deep-Space “Ghost Particle” Phenomenon

• How Two Rebel Physicists Changed Quantum Theory

How the Universe Forges Stars from Cosmic Clouds

Recent posts.

• Heritage Bilinguals and the Second-Language Classroom
• The Uneven Costs of Cross-Country Connectivity

Support JSTOR Daily

Sign up for our weekly newsletter.

Articles on Botany

Displaying 1 - 20 of 95 articles.

Why do some trees lose their leaves and others don’t? The Conversation’s Curious Kids podcast

Eloise Stevens , The Conversation

Digging into the colonial roots of gardening

Vinita Srivastava , The Conversation and Ateqah Khaki , The Conversation

Curious Kids: why do trees have bark?

Gregory Moore , The University of Melbourne

Cranberries can bounce, float and pollinate themselves: The saucy science of a Thanksgiving classic

Serina DeSalvio , Texas A&M University

Take a break from your screen and look at plants − botanizing is a great way to engage with life around you

Jacob S. Suissa , University of Tennessee and Ben Goulet-Scott , Harvard University

French botanist Théodore Leschenault travelled to Australia in 1800-1803 . His recently recovered journal contains a wealth of intriguing information

Paul Gibbard , The University of Western Australia

Why does grass grow more slowly in winter?

Colonialism has shaped scientific plant collections around the world – here’s why that matters

Daniel Park , Purdue University

The world’s first flowers were pollinated by insects

Ruby E. Stephens , Macquarie University ; Hervé Sauquet , UNSW Sydney ; Lily Dun , UNSW Sydney ; Rachael Gallagher , Western Sydney University , and Will Cornwell , UNSW Sydney

Native raspberries, limes and geraniums: how did these curious plants end up in Australia?

Decolonize your garden: This long weekend, dig into the complicated roots of gardening — Listen

Learn to think like a plant: five questions to think about if you want to keep your houseplants healthy

Chris Thorogood , University of Oxford

I’ve created a monstera! How to care for the ‘Swiss cheese plant’ in your life

Climate change threatens spring wildflowers by speeding up the time when trees leaf out above them

Richard B. Primack , Boston University ; Benjamin R. Lee , University of Pittsburgh , and Tara K. Miller , University of Virginia

Once the Callery pear tree was landscapers’ favorite – now states are banning this invasive species and urging homeowners to cut it down

Ryan W. McEwan , University of Dayton

Some houseplants take in nutrients from roots outside the soil – and it may change how we care for them

Amanda Rasmussen , University of Nottingham

A new discovery shows major flowering plants are 150 million years older than previously thought

Byron Lamont , Curtin University

I spent a year squeezing leaves to measure their water content. Here’s what I learned

Tomás I. Fuenzalida , Australian National University

Botanists are disappearing – just when the world needs them most

Sebastian Stroud , University of Leeds

How to grow plants on the moon – new study

Monica Grady , The Open University

Related Topics

• Climate change
• Horticulture
• Native plants
• Photosynthesis
• Plant science

Top contributors

Senior Research Associate, School of Ecosystem and Forest Sciences, The University of Melbourne

Vice President of Academic Affairs and Dean of the College, Grinnell College

Professeur, Biologie et Biochimie végétales, IUF, Université de Lorraine

Founder of Msit No’kmaq

PhD Candidate, Social Justice Education, Ontario Institute for Studies in Education, University of Toronto

Henslow Research Fellow, University of Cambridge

Chair of ARC Centre of Excellence for Quantum Biotechnology, The University of Queensland

Research Associate Professor in Evolutionary Biology, The University of Western Australia

Senior Research Professor, Curtin University

Professor of Planetary and Space Sciences, The Open University

Associate Professor in Ecology and Evolution, UNSW Sydney

Research botanist at the Botanic Gardens and State Herbarium of South Australia/Environment Institute, University of Adelaide

Author and Research Fellow, UNSW Sydney

Professor of Plant Science, Lancaster University

Senior Zoologist and Botanical Curator, Queensland Herbarium

• X (Twitter)
• Unfollow topic Follow topic

• Search by keyword
• Search by citation

Page 1 of 10

Novel therapeutic activities of dragon blood from palm tree Daemonorops draco for the treatment of chronic diabetic wounds

The clinical efficacy of Jinchuang Ointment, a traditional Chinese medicine (TCM), in treating chronic non-healing diabetic wounds has been demonstrated over the past decades. Both in vitro and in vivo angioge...

• View Full Text

Dissecting wheat above-ground architecture for enhanced water use efficiency and grain yield in the subtropics

Growing wheat under climate change scenarios challenges, scientists to develop drought and heat-tolerant genotypes. The adaptive traits should therefore be explored and engineered for this purpose. Thus, this ...

Taxonomic resurrection of Saxifraga lancangensis (Saxifragaceae)

Accurate species delimitation is fundamental for testing evolutionary theory and provides essential implications for conservation management. The arctic-alpine genus Saxifraga L. (Saxifragaceae) is taxonomically ...

The complete chloroplast genome and phylogentic results support the species position of Swertia banzragczii and Swertia marginata (Gentianaceae) in Mongolia

Swertia banzragczii and S. marginata are important medicinal species in Mongolia. However, their taxonomic positions and genetic backgrounds remain unknown. In this study, we explored the complete chloroplast gen...

Gas exchange and chlorophyll fluorescence responses of Camellia sinensis grown under various cultivations in different seasons

Sod culture (SC) and conventional agriculture (CA) represent two distinct field management approaches utilized in the cultivation of tea plants in Taiwan. In this study, we employed gas exchange and chlorophyl...

Dynamic of land use and vegetation change in the eastern bank of Bénoué (North Cameroon)

The eastern part of the Benoue River bank is undergoing degradation marked by a significant decrease in vegetation cover and woody resources due to anthropogenic activities and climatic. The main objective of ...

Hypoglycemic effects of dracorhodin and dragon blood crude extract from Daemonorops draco

Dragon blood is a red fruit resin from the palm tree Daemonorops draco and is a herbal ingredient used in the traditional Chinese medicine, “Jinchuang Ointment,” which is used to treat non-healing diabetic wounds...

An uncut copy of Scleromyceti Sueciae : lost and then found

A copy of Scleromyceti Sueciae , a work on which the nomenclature of many fungi is based was known to occur in Scotland’s Glasgow University Botany Department but the buildings were devastated by fire in 2001 and ...

A comprehensive review on ecology, life cycle and use of Tecoma stans (bignoneaceae)

Tecoma stans is a widely distributed tall ornamental shrub in the plains of Indian subcontinent and is considered an invasive species across Argentina, Australia, South Africa, Pacific Islands and tropical region...

Dynamic organelle changes and autophagic processes in lily pollen germination

Pollen germination is a crucial process in the life cycle of flowering plants, signifying the transition of quiescent pollen grains into active growth. This study delves into the dynamic changes within organel...

Antibacterial, antioxidant, and anticancer potential of green fabricated silver nanoparticles made from Viburnum grandiflorum leaf extract

Recently, researchers are focusing on creating new tools to combat the antibiotic resistant bacteria and malignancy issues, which pose significant threats to humanity. Biosynthesized silver nanoparticles (AgNP...

A taxonomic revision of the genus Angelica (Apiaceae) in Taiwan with a new species A. aliensis

Angelica L. sensu lato is a taxonomically complex genus, and many studies have utilized morphological and molecular features to resolve its classification issues. In Taiwan, there are six taxa within Angelica , an...

An optimum study on the laser scanning confocal microscopy techniques for BiFC assay using plant protoplast

The bimolecular fluorescence complementation (BiFC) assay is commonly used for investigating protein–protein interactions. While several BiFC detection systems have been developed, there is a limited amount of...

Anther-derived microspore embryogenesis in pepper hybrids orobelle and Bomby

Traditional breeding methods have long been employed worldwide for the evaluation and development of pepper cultivars. However, these methods necessitate multiple generations of screening, line development, ev...

Chemical constituents from the medicinal herb-derived fungus Chaetomium globosum Km1226

Endophytic fungi have proven to be a rich source of novel natural products with a wide-array of biological activities and higher levels of structural diversity.

Taxonomic implications of leaf morphology and epidermal anatomy for 14 species of Gagea (Liliaceae) from Xinjiang, China

Leaf morphology and epidermal characters are important for phylogenetic and taxonomic studies of many plants, but there is currently insufficient data to use them to help distinguish species of Gagea , which is a ...

Lopadostoma , Oligostoma , and some Rosellinia specimens from the herbarium of the Swiss Federal Institute of Technology (ZT): the value of early fieldwork and the importance of keeping fungal collections

Morphology, hosts, and collecting sites of fungi assessed from herbarium material of special interest deserve to be brought to the attention of mycologists.

Five new Camillea (Xylariales) species described from French Guiana

The genus Camillea was created in 1849 from collections made in French Guiana with eight species included. Numerous species assigned to Camillea were subsequently discovered, especially in the forests of the Amaz...

Diverse Xylaria in the Ecuadorian Amazon and their mode of wood degradation

Xylaria is a diverse and ecologically important genus in the Ascomycota. This paper describes the xylariaceous fungi present in an Ecuadorian Amazon Rainforest and investigates the decay potential of selected Xyl...

Potential of algal-based products for the management of potato brown rot disease

Ralstonia solanacearum causes potato brown rot disease, resulting in lower crop’s production and quality. A sustainable and eco-friendly method for controlling the disease is required. Algae’s bioactive chemicals...

Changes in soil organic carbon and nitrogen stocks in organic farming practice and abandoned tea plantation

The restoration of conventional tea plantations and the adoption of organic farming practices could impact soil organic carbon (SOC) and nitrogen (N) stocks. This study investigated the soil properties, SOC an...

The orchid seed coat: a developmental and functional perspective

Orchid seeds are 'dust-like.' The seed coat is usually thin, with only one to a few cell layers. It originates from the integuments formed during ovule development. In orchids, the outer integument is primaril...

Climbing strategies of Taiwan climbers

The climbing strategies of lianas and herbaceous vines influence climber competition abilities and survival. The aim of this study was to investigate the climbing strategies of each plant species and observe t...

Vegetation diversity pattern during spring season in relation to topographic and edaphic variables in sub-tropical zone

The present study was conducted to explore the diversity pattern of spring vegetation under the influence of topographic and edaphic variables in sub-tropical zone, District Malakand. In the present vegetation...

L-DOPA induces iron accumulation in roots of Ipomoea aquatica and Arabidopsis thaliana in a pH-dependent manner

Iron deficiency is the leading cause of anemia worldwide, particularly in countries with predominant plant-based diets. Plants constitute the main source of dietary iron. Increasing their iron concentration co...

Investigation of phytotherapeutic potential of herbal mixtures and their effects on salbutamol induced cardiotoxicity and hyperlipidemia in rabbits

Cardiovascular diseases (CVDs) are the major cause of deaths all over the world. The high level of blood cholesterol and oxidative stress are major risk factors for heart diseases. The phytotherapeutics have a...

Using homemade stainless steel dendrometer band for long term tree growth measurements

Dendrometer bands have been proposed as an accurate method for measuring tree growth. However, the constrained observation window and the material used in them hamper long-term tree growth monitoring. This stu...

Xylaria furcata reconsidered and nine resembling species

Xylaria collections from termite nests with dichotomously branched stromata have been identified as X . furcata . However, Léveillé’s original material is no longer available, and the modern interpretation of X . fu...

Management of potato brown rot disease using chemically synthesized CuO-NPs and MgO-NPs

Potatoes are a crucial vegetable crop in Egypt in terms of production and consumption. However, the potato industry suffers significant annual losses due to brown rot disease. This study aimed to suppress Ralston...

Xylaria species associated with fallen leaves and petioles

Xylaria species growing on fallen leaves and petioles have not been treated systematically. One source of confusion in this group of Xylaria species has stemmed from X. filiformis , which is an ancient name publis...

Characterization and the comprehensive expression analysis of tobacco valine-glutamine genes in response to trichomes development and stress tolerance

Valine-glutamine genes (VQ) acted as transcription regulators and played the important roles in plant growth and development, and stress tolerance through interacting with transcription factors and other co-re...

Richer than Gold: the fungal biodiversity of Reserva Los Cedros, a threatened Andean cloud forest

Globally, many undescribed fungal taxa reside in the hyperdiverse, yet undersampled, tropics. These species are under increasing threat from habitat destruction by expanding extractive industry, in addition to...

Variation of growth and transcriptome responses to arbuscular mycorrhizal symbiosis in different foxtail millet lines

Arbuscular mycorrhizal fungi (AMF) have been applied to promote the growth of different crop species, but knowledge about the impacts of symbiosis on foxtail millet at the physiological and molecular levels ha...

Exploring the Xylariaceae and its relatives

The Xylariaceae and its relatives rank as one of the best-known members of the Ascomycota. They are now well recognized for their diversity, global distribution, ecological activities and their outstanding nov...

New insights into polyploid evolution and dynamic nature of Ludwigia section Isnardia (Onagraceae)

While polyploids are common in plants, the evolutionary history and natural dynamics of most polyploid groups are still unclear. Owing to plentiful earlier systematic studies, Ludwigia sect. Isnardia (comprising ...

Correction: MethylC‑analyzer: a comprehensive downstream pipeline for the analysis of genome‑wide DNA methylation

The original article was published in Botanical Studies 2023 64 :1

Transcriptome profiles reveal gene regulation of ginger flowering induced by photoperiod and light quality

Under natural conditions, ginger ( Zingiber officinale Rosc.) rarely blossom and has seed, which limits new variety breeding of ginger and industry development. In this study, the effects of different photoperiods...

Identification of qBK2.1 , a novel QTL controlling rice resistance against Fusarium fujikuroi

Bakanae disease caused by Fusarium fujikuroi is an increasing threat to rice production. The infected plants show symptoms such as elongation, slenderness, chlorosis, a large leaf angle, and even death. Bakanae d...

Morpho-anatomical, and chemical characterization of some calcareous Mediterranean red algae species

Climatic changes are anticipated to have a detrimental effect on calcifying marine species. Calcareous red algae may be especially vulnerable to seasonal variations since they are common and essential biologic...

Acid scarification as a potent treatment for an in vitro germination of mature endozoochorous Vanilla planifolia seeds

Vanilla planifolia is the most widely cultivated species of vanilla with high economic importance. However, seed germination under artificial conditions is difficult and yields low germination percentages. The se...

Redisposition of apiosporous genera Induratia and Muscodor in the Xylariales, following the discovery of an authentic strain of Induratia apiospora

The genus Induratia is based on Induratia apiospora , a xylarialean pyrenomycete from New Zealand with clypeate uniperitheciate stromata, hyaline apiospores and a nodulisporium-like anamorph. However, because of t...

Morphological characterization of intraspecific variation for trichome traits in tomato ( Solanum lycopersicum )

Trichomes, the hairlike protuberances in plants, have been well known to act as the first line of defense against herbivores, and abiotic stresses, along with other structural defenses such as spines, thorns, ...

Fungal communities on alpine cheese rinds in Southern Switzerland

The biodiversity of the mycobiota of soft cheese rinds such as Brie or Camembert has been extensively studied, but scant information is available on the fungi colonizing the rinds of cheese produced in the Sou...

Responses of photosynthesis and chlorophyll fluorescence during light induction in different seedling ages of Mahonia oiwakensis

The aim of this study was to determine the actual state of the photosynthetic apparatus and exhibit distinguishable differences in the chlorophyll fluorescence (ChlF) components in different seedling ages of M. o...

Alleviation of the adverse effects of NaCl stress on tomato seedlings ( Solanum lycopersicum L.) by Trichoderma viride through the antioxidative defense system

Trichoderma viride are well known for their biocontrol capabilities, but little is known about how they stimulate plant development and increase their resistance to salt stress. One of the main abiotic factors li...

Veronicastrum wulingense (Plantaginaceae), a new species from Southwestern Hubei, China

The genus Veronicastrum Heist. ex Fabr. are mainly distributed in East Asia, and only Veronicastrum virginicum (L.) Farw. is disjunctively distributed in eastern North America. The south area of China (extending ...

Living on the edge: morphological, karyological and genetic diversity studies of the Hungarian Plantago maxima populations and established ex situ collection

The analysis of genetic diversity of protected plant species can greatly support conservation efforts. Plantago maxima Juss. ex Jacq. is a perennial species distributed along the Eurasian steppe. The westernmost ...

MethylC-analyzer: a comprehensive downstream pipeline for the analysis of genome-wide DNA methylation

DNA methylation is a crucial epigenetic modification involved in multiple biological processes and diseases. Current approaches for measuring genome-wide DNA methylation via bisulfite sequencing (BS-seq) inclu...

The Correction to this article has been published in Botanical Studies 2023 64 :13

Biostimulation of tomato growth and biocontrol of Fusarium wilt disease using certain endophytic fungi

Tomato plant ( Solanum lycopersicum L.) suffers from numerous fungal pathogens that cause damage to yeild production qualitatively and quantitatively. One of the most destructive disease of tomato is Fusarium wilt...

First report of chemical composition and cytotoxicity evaluation of Foraminispora rugosa basidiomata from Brazil

Foraminispora rugosa is a species reported from Brazil, Venezuela, French Guiana, Costa Rica and Cuba. It is a basidiomycete in the Ganodermataceae family. In this study, both chemical composition and cytotoxicit...

• Editorial Board
• Sign up for article alerts and news from this journal

Annual Journal Metrics

2022 Citation Impact 3.4 - 2-year Impact Factor 3.7 - 5-year Impact Factor 1.143 - SNIP (Source Normalized Impact per Paper) 0.623 - SJR (SCImago Journal Rank)

2023 Speed 20 days submission to first editorial decision for all manuscripts (Median) 114 days submission to accept (Median)

2023 Usage  388,267 downloads 226 Altmetric mentions

• More about our metrics
• ISSN: 1999-3110 (electronic)

Loading metrics

Open Access

Peer-reviewed

Meta-Research Article

Meta-Research Articles feature data-driven examinations of the methods, reporting, verification, and evaluation of scientific research.

See Journal Information »

Assessing the evolution of research topics in a biological field using plant science as an example

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America, Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, Michigan, United States of America, DOE-Great Lake Bioenergy Research Center, Michigan State University, East Lansing, Michigan, United States of America

Roles Conceptualization, Investigation, Project administration, Supervision, Writing – review & editing

Affiliation Department of Plant Biology, Michigan State University, East Lansing, Michigan, United States of America

• Shin-Han Shiu, 
• Melissa D. Lehti-Shiu

• Published: May 23, 2024
• https://doi.org/10.1371/journal.pbio.3002612
• Peer Review
• Reader Comments

Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field. Using plant biology as an example, we used machine learning and language models to classify plant science citations into topics representing interconnected, evolving subfields. The changes in prevalence of topical records over the last 50 years reflect shifts in major research trends and recent radiation of new topics, as well as turnover of model species and vastly different plant science research trajectories among countries. Our approaches readily summarize the topical diversity and evolution of a scientific field with hundreds of thousands of relevant papers, and they can be applied broadly to other fields.

Citation: Shiu S-H, Lehti-Shiu MD (2024) Assessing the evolution of research topics in a biological field using plant science as an example. PLoS Biol 22(5): e3002612. https://doi.org/10.1371/journal.pbio.3002612

Academic Editor: Ulrich Dirnagl, Charite Universitatsmedizin Berlin, GERMANY

Received: October 16, 2023; Accepted: April 4, 2024; Published: May 23, 2024

Copyright: © 2024 Shiu, Lehti-Shiu. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The plant science corpus data are available through Zenodo ( https://zenodo.org/records/10022686 ). The codes for the entire project are available through GitHub ( https://github.com/ShiuLab/plant_sci_hist ) and Zenodo ( https://doi.org/10.5281/zenodo.10894387 ).

Funding: This work was supported by the National Science Foundation (IOS-2107215 and MCB-2210431 to MDL and SHS; DGE-1828149 and IOS-2218206 to SHS), Department of Energy grant Great Lakes Bioenergy Research Center (DE-SC0018409 to SHS). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: BERT, Bidirectional Encoder Representations from Transformers; br, brassinosteroid; ccTLD, country code Top Level Domain; c-Tf-Idf, class-based Tf-Idf; ChatGPT, Chat Generative Pretrained Transformer; ga, gibberellic acid; LOWESS, locally weighted scatterplot smoothing; MeSH, Medical Subject Heading; SHAP, SHapley Additive exPlanations; SJR, SCImago Journal Rank; Tf-Idf, Term frequency-Inverse document frequency; UMAP, Uniform Manifold Approximation and Projection

Introduction

The explosive growth of scientific data in recent years has been accompanied by a rapidly increasing volume of literature. These records represent a major component of our scientific knowledge and embody the history of conceptual and technological advances in various fields over time. Our ability to wade through these records is important for identifying relevant literature for specific topics, a crucial practice of any scientific pursuit [ 1 ]. Classifying the large body of literature into topics can provide a useful means to identify relevant literature. In addition, these topics offer an opportunity to assess how scientific fields have evolved and when major shifts in took place. However, such classification is challenging because the relevant articles in any topic or domain can number in the tens or hundreds of thousands, and the literature is in the form of natural language, which takes substantial effort and expertise to process [ 2 , 3 ]. In addition, even if one could digest all literature in a field, it would still be difficult to quantify such knowledge.

In the last several years, there has been a quantum leap in natural language processing approaches due to the feasibility of building complex deep learning models with highly flexible architectures [ 4 , 5 ]. The development of large language models such as Bidirectional Encoder Representations from Transformers (BERT; [ 6 ]) and Chat Generative Pretrained Transformer (ChatGPT; [ 7 ]) has enabled the analysis, generation, and modeling of natural language texts in a wide range of applications. The success of these applications is, in large part, due to the feasibility of considering how the same words are used in different contexts when modeling natural language [ 6 ]. One such application is topic modeling, the practice of establishing statistical models of semantic structures underlying a document collection. Topic modeling has been proposed for identifying scientific hot topics over time [ 1 ], for example, in synthetic biology [ 8 ], and it has also been applied to, for example, automatically identify topical scenes in images [ 9 ] and social network topics [ 10 ], discover gene programs highly correlated with cancer prognosis [ 11 ], capture “chromatin topics” that define cell-type differences [ 12 ], and investigate relationships between genetic variants and disease risk [ 13 ]. Here, we use topic modeling to ask how research topics in a scientific field have evolved and what major changes in the research trends have taken place, using plant science as an example.

Plant science corpora allow classification of major research topics

Plant science, broadly defined, is the study of photosynthetic species, their interactions with biotic/abiotic environments, and their applications. For modeling plant science topical evolution, we first identified a collection of plant science documents (i.e., corpus) using a text classification approach. To this end, we first collected over 30 million PubMed records and narrowed down candidate plant science records by searching for those with plant-related terms and taxon names (see Materials and methods ). Because there remained a substantial number of false positives (i.e., biomedical records mentioning plants in passing), a set of positive plant science examples from the 17 plant science journals with the highest numbers of plant science publications covering a wide range of subfields and a set of negative examples from journals with few candidate plant science records were used to train 4 types of text classification models (see Materials and methods ). The best text classification model performed well (F1 = 0.96, F1 of a naïve model = 0.5, perfect model = 1) where the positive and negative examples were clearly separated from each other based on prediction probability of the hold-out testing dataset (false negative rate = 2.6%, false positive rate = 5.2%, S1A and S1B Fig ). The false prediction rate for documents from the 17 plant science journals annotated with the Medical Subject Heading (MeSH) term “Plants” in NCBI was 11.7% (see Materials and methods ). The prediction probability distribution of positive instances with the MeSH term has an expected left-skew to lower values ( S1C Fig ) compared with the distributions of all positive instances ( S1A Fig ). Thus, this subset with the MeSH term is a skewed representation of articles from these 17 major plant science journals. To further benchmark the validity of the plant science records, we also conducted manual annotation of 100 records where the false positive and false negative rates were 14.6% and 10.6%, respectively (see Materials and methods ). Using 12 other plant science journals not included as positive examples as benchmarks, the false negative rate was 9.9% (see Materials and methods ). Considering the range of false prediction rate estimates with different benchmarks, we should emphasize that the model built with the top 17 plant science journals represents a substantial fraction of plant science publications but with biases. Applying the model to the candidate plant science record led to 421,658 positive predictions, hereafter referred to as “plant science records” ( S1D Fig and S1 Data ).

To better understand how the models classified plant science articles, we identified important terms from a more easily interpretable model (Term frequency-Inverse document frequency (Tf-Idf) model; F1 = 0.934) using Shapley Additive Explanations [ 14 ]; 136 terms contributed to predicting plant science records (e.g., Arabidopsis, xylem, seedling) and 138 terms contributed to non-plant science record predictions (e.g., patients, clinical, mice; Tf-Idf feature sheet, S1 Data ). Plant science records as well as PubMed articles grew exponentially from 1950 to 2020 ( Fig 1A ), highlighting the challenges of digesting the rapidly expanding literature. We used the plant science records to perform topic modeling, which consisted of 4 steps: representing each record as a BERT embedding, reducing dimensionality, clustering, and identifying the top terms by calculating class (i.e., topic)-based Tf-Idf (c-Tf-Idf; [ 15 ]). The c-Tf-Idf represents the frequency of a term in the context of how rare the term is to reduce the influence of common words. SciBERT [ 16 ] was the best model among those tested ( S2 Data ) and was used for building the final topic model, which classified 372,430 (88.3%) records into 90 topics defined by distinct combinations of terms ( S3 Data ). The topics contained 620 to 16,183 records and were named after the top 4 to 5 terms defining the topical areas ( Fig 1B and S3 Data ). For example, the top 5 terms representing the largest topic, topic 61 (16,183 records), are “qtl,” “resistance,” “wheat,” “markers,” and “traits,” which represent crop improvement studies using quantitative genetics.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

(A) Numbers of PubMed (magenta) and plant science (green) records between 1950 and 2020. (a, b, c) Coefficients of the exponential function, y = ae b . Data for the plot are in S1 Data . (B) Numbers of documents for the top 30 plant science topics. Each topic is designated by an index number (left) and the top 4–6 terms with the highest cTf-Idf values (right). Data for the plot are in S3 Data . (C) Two-dimensional representation of the relationships between plant science records generated by Uniform Manifold Approximation and Projection (UMAP, [ 17 ]) using SciBERT embeddings of plant science records. All topics panel: Different topics are assigned different colors. Outlier panel: UMAP representation of all records (gray) with outlier records in red. Blue dotted circles: areas with relatively high densities indicating topics that are below the threshold for inclusion in a topic. In the 8 UMAP representations on the right, records for example topics are in red and the remaining records in gray. Blue dotted circles indicate the relative position of topic 48.

https://doi.org/10.1371/journal.pbio.3002612.g001

Records with assigned topics clustered into distinct areas in a two-dimensional (2D) space ( Fig 1C , for all topics, see S4 Data ). The remaining 49,228 outlier records not assigned to any topic (11.7%, middle panel, Fig 1C ) have 3 potential sources. First, some outliers likely belong to unique topics but have fewer records than the threshold (>500, blue dotted circles, Fig 1C ). Second, some of the many outliers dispersed within the 2D space ( Fig 1C ) were not assigned to any single topic because they had relatively high prediction scores for multiple topics ( S2 Fig ). These likely represent studies across subdisciplines in plant science. Third, some outliers are likely interdisciplinary studies between plant science and other domains, such as chemistry, mathematics, and physics. Such connections can only be revealed if records from other domains are included in the analyses.

Topical clusters reveal closely related topics but with distinct key term usage

Related topics tend to be located close together in the 2D representation (e.g., topics 48 and 49, Fig 1C ). We further assessed intertopical relationships by determining the cosine similarities between topics using cTf-Idfs ( Figs 2A and S3 ). In this topic network, some topics are closely related and form topic clusters. For example, topics 25, 26, and 27 collectively represent a more general topic related to the field of plant development (cluster a , lower left in Fig 2A ). Other topic clusters represent studies of stress, ion transport, and heavy metals ( b ); photosynthesis, water, and UV-B ( c ); population and community biology (d); genomics, genetic mapping, and phylogenetics ( e , upper right); and enzyme biochemistry ( f , upper left in Fig 2A ).

(A) Graph depicting the degrees of similarity (edges) between topics (nodes). Between each topic pair, a cosine similarity value was calculated using the cTf-Idf values of all terms. A threshold similarity of 0.6 was applied to illustrate the most related topics. For the full matrix presented as a heatmap, see S4 Fig . The nodes are labeled with topic index numbers and the top 4–6 terms. The colors and width of the edges are defined based on cosine similarity. Example topic clusters are highlighted in yellow and labeled a through f (blue boxes). (B, C) Relationships between the cTf-Idf values (see S3 Data ) of the top terms for topics 26 and 27 (B) and for topics 25 and 27 (C) . Only terms with cTf-Idf ≥ 0.6 are labeled. Terms with cTf-Idf values beyond the x and y axis limit are indicated by pink arrows and cTf-Idf values. (D) The 2D representation in Fig 1C is partitioned into graphs for different years, and example plots for every 5-year period since 1975 are shown. Example topics discussed in the text are indicated. Blue arrows connect the areas occupied by records of example topics across time periods to indicate changes in document frequencies.

https://doi.org/10.1371/journal.pbio.3002612.g002

Topics differed in how well they were connected to each other, reflecting how general the research interests or needs are (see Materials and methods ). For example, topic 24 (stress mechanisms) is the most well connected with median cosine similarity = 0.36, potentially because researchers in many subfields consider aspects of plant stress even though it is not the focus. The least connected topics include topic 21 (clock biology, 0.12), which is surprising because of the importance of clocks in essentially all aspects of plant biology [ 18 ]. This may be attributed, in part, to the relatively recent attention in this area.

Examining topical relationships and the cTf-Idf values of terms also revealed how related topics differ. For example, topic 26 is closely related to topics 27 and 25 (cluster a on the lower left of Fig 2A ). Topics 26 and 27 both contain records of developmental process studies mainly in Arabidopsis ( Fig 2B ); however, topic 26 is focused on the impact of light, photoreceptors, and hormones such as gibberellic acids (ga) and brassinosteroids (br), whereas topic 27 is focused on flowering and floral development. Topic 25 is also focused on plant development but differs from topic 27 because it contains records of studies mainly focusing on signaling and auxin with less emphasis on Arabidopsis ( Fig 2C ). These examples also highlight the importance of using multiple top terms to represent the topics. The similarities in cTf-Idfs between topics were also useful for measuring the editorial scope (i.e., diverse, or narrow) of journals publishing plant science papers using a relative topic diversity measure (see Materials and methods ). For example, Proceedings of the National Academy of Sciences , USA has the highest diversity, while Theoretical and Applied Genetics has the lowest ( S4 Fig ). One surprise is the relatively low diversity of American Journal of Botany , which focuses on plant ecology, systematics, development, and genetics. The low diversity is likely due to the relatively larger number of cellular and molecular science records in PubMed, consistent with the identification of relatively few topical areas relevant to studies at the organismal, population, community, and ecosystem levels.

Investigation of the relative prevalence of topics over time reveals topical succession

We next asked whether relationships between topics reflect chronological progression of certain subfields. To address this, we assessed how prevalent topics were over time using dynamic topic modeling [ 19 ]. As shown in Fig 2D , there is substantial fluctuation in where the records are in the 2D space over time. For example, topic 44 (light, leaves, co, synthesis, photosynthesis) is among the topics that existed in 1975 but has diminished gradually since. In 1985, topic 39 (Agrobacterium-based transformation) became dense enough to be visualized. Additional examples include topics 79 (soil heavy metals), 42 (differential expression), and 82 (bacterial community metagenomics), which became prominent in approximately 2005, 2010, and 2020, respectively ( Fig 2D ). In addition, animating the document occupancy in the 2D space over time revealed a broad change in patterns over time: Some initially dense areas became sparse over time and a large number of topics in areas previously only loosely occupied at the turn of the century increased over time ( S5 Data ).

While the 2D representations reveal substantial details on the evolution of topics, comparison over time is challenging because the number of plant science records has grown exponentially ( Fig 1A ). To address this, the records were divided into 50 chronological bins each with approximately 8,400 records to make cross-bin comparisons feasible ( S6 Data ). We should emphasize that, because of the way the chronological bins were split, the number of records for each topic in each bin should be treated as a normalized value relative to all other topics during the same period. Examining this relative prevalence of topics across bins revealed a clear pattern of topic succession over time (one topic evolved into another) and the presence of 5 topical categories ( Fig 3 ). The topics were categorized based on their locally weighted scatterplot smoothing (LOWESS) fits and ordered according to timing of peak frequency ( S7 and S8 Data , see Materials and methods ). In Fig 3 , the relative decrease in document frequency does not mean that research output in a topic is dwindling. Because each row in the heatmap is normalized based on the minimum and maximum values within each topic, there still can be substantial research output in terms of numbers of publications even when the relative frequency is near zero. Thus, a reduced relative frequency of a topic reflects only a below-average growth rate compared with other topical areas.

(A-E) A heat map of relative topic frequency over time reveals 5 topical categories: (A) stable, (B) early, (C) transitional, (D) sigmoidal, and (E) rising. The x axis denotes different time bins with each bin containing a similar number of documents to account for the exponential growth of plant science records over time. The sizes of all bins except the first are drawn to scale based on the beginning and end dates. The y axis lists different topics denoted by the label and top 4 to 5 terms. In each cell, the prevalence of a topic in a time bin is colored according to the min-max normalized cTf-Idf values for that topic. Light blue dotted lines delineate different decades. The arrows left of a subset of topic labels indicate example relationships between topics in topic clusters. Blue boxes with labels a–f indicate topic clusters, which are the same as those in Fig 2 . Connecting lines indicate successional trends. Yellow circles/lines 1 – 3: 3 major transition patterns. The original data are in S5 Data .

https://doi.org/10.1371/journal.pbio.3002612.g003

The first topical category is a stable category with 7 topics mostly established before the 1980s that have since remained stable in terms of prevalence in the plant science records (top of Fig 3A ). These topics represent long-standing plant science research foci, including studies of plant physiology (topics 4, 58, and 81), genetics (topic 61), and medicinal plants (topic 53). The second category contains 8 topics established before the 1980s that have mostly decreased in prevalence since (the early category, Fig 3B ). Two examples are physiological and morphological studies of hormone action (topic 45, the second in the early category) and the characterization of protein, DNA, and RNA (topic 18, the second to last). Unlike other early topics, topic 78 (paleobotany and plant evolution studies, the last topic in Fig 3B ) experienced a resurgence in the early 2000s due to the development of new approaches and databases and changes in research foci [ 20 ].

The 33 topics in the third, transitional category became prominent in the 1980s, 1990s, or even 2000s but have clearly decreased in prevalence ( Fig 3C ). In some cases, the early and the transitional topics became less prevalent because of topical succession—refocusing of earlier topics led to newer ones that either show no clear sign of decrease (the sigmoidal category, Fig 3D ) or continue to increase in prevalence (the rising category, Fig 3E ). Consistent with the notion of topical succession, topics within each topic cluster ( Fig 2 ) were found across topic categories and/or were prominent at different time periods (indicated by colored lines linking topics, Fig 3 ). One example is topics in topic cluster b (connected with light green lines and arrows, compare Figs 2 and 3 ); the study of cation transport (topic 47, the third in the transitional category), prominent in the 1980s and early 1990s, is connected to 5 other topics, namely, another transitional topic 29 (cation channels and their expression) peaking in the 2000s and early 2010s, sigmoidal topics 24 and 28 (stress response, tolerance mechanisms) and 30 (heavy metal transport), which rose to prominence in mid-2000s, and the rising topic 42 (stress transcriptomic studies), which increased in prevalence in the mid-2010s.

The rise and fall of topics can be due to a combination of technological or conceptual breakthroughs, maturity of the field, funding constraints, or publicity. The study of transposable elements (topic 62) illustrates the effect of publicity; the rise in this field coincided with Barbara McClintock’s 1983 Nobel Prize but not with the publication of her studies in the 1950s [ 21 ]. The reduced prevalence in early 2000 likely occurred in part because analysis of transposons became a central component of genome sequencing and annotation studies, rather than dedicated studies. In addition, this example indicates that our approaches, while capable of capturing topical trends, cannot be used to directly infer major papers leading to the growth of a topic.

Three major topical transition patterns signify shifts in research trends

Beyond the succession of specific topics, 3 major transitions in the dynamic topic graph should be emphasized: (1) the relative decreasing trend of early topics in the late 1970s and early 1980s; (2) the rise of transitional topics in late 1980s; and (3) the relative decreasing trend of transitional topics in the late 1990s and early 2000s, which coincided with a radiation of sigmoidal and rising topics (yellow circles, Fig 3 ). The large numbers of topics involved in these transitions suggest major shifts in plant science research. In transition 1, early topics decreased in relative prevalence in the late 1970s to early 1980s, which coincided with the rise of transitional topics over the following decades (circle 1, Fig 3 ). For example, there was a shift from the study of purified proteins such as enzymes (early topic 48, S5A Fig ) to molecular genetic dissection of genes, proteins, and RNA (transitional topic 35, S5B Fig ) enabled by the wider adoption of recombinant DNA and molecular cloning technologies in late 1970s [ 22 ]. Transition 2 (circle 2, Fig 3 ) can be explained by the following breakthroughs in the late 1980s: better approaches to create transgenic plants and insertional mutants [ 23 ], more efficient creation of mutant plant libraries through chemical mutagenesis (e.g., [ 24 ]), and availability of gene reporter systems such as β-glucuronidase [ 25 ]. Because of these breakthroughs, molecular genetics studies shifted away from understanding the basic machinery to understanding the molecular underpinnings of specific processes, such as molecular mechanisms of flower and meristem development and the action of hormones such as auxin (topic 27, S5C Fig ); this type of research was discussed as a future trend in 1988 [ 26 ] and remains prevalent to this date. Another example is gene silencing (topic 12), which became a focal area of study along with the widespread use of transgenic plants [ 27 ].

Transition 3 is the most drastic: A large number of transitional, sigmoidal, and rising topics became prevalent nearly simultaneously at the turn of the century (circle 3, Fig 3 ). This period also coincides with a rapid increase in plant science citations ( Fig 1A ). The most notable breakthroughs included the availability of the first plant genome in 2000 [ 28 ], increasing ease and reduced cost of high-throughput sequencing [ 29 ], development of new mass spectrometry–based platforms for analyzing proteins [ 30 ], and advancements in microscopic and optical imaging approaches [ 31 ]. Advances in genomics and omics technology also led to an increase in stress transcriptomics studies (42, S5D Fig ) as well as studies in many other topics such as epigenetics (topic 11), noncoding RNA analysis (13), genomics and phylogenetics (80), breeding (41), genome sequencing and assembly (60), gene family analysis (23), and metagenomics (82 and 55).

In addition to the 3 major transitions across all topics, there were also transitions within topics revealed by examining the top terms for different time bins (heatmaps, S5 Fig ). Taken together, these observations demonstrate that knowledge about topical evolution can be readily revealed through topic modeling. Such knowledge is typically only available to experts in specific areas and is difficult to summarize manually, as no researcher has a command of the entire plant science literature.

Analysis of taxa studied reveals changes in research trends

Changes in research trends can also be illustrated by examining changes in the taxa being studied over time ( S9 Data ). There is a strong bias in the taxa studied, with the record dominated by research models and economically important taxa ( S6 Fig ). Flowering plants (Magnoliopsida) are found in 93% of records ( S6A Fig ), and the mustard family Brassicaceae dominates at the family level ( S6B Fig ) because the genus Arabidopsis contributes to 13% of plant science records ( Fig 4A ). When examining the prevalence of taxa being studied over time, clear patterns of turnover emerged similar to topical succession ( Figs 4B , S6C, and S6D ; Materials and methods ). Given that Arabidopsis is mentioned in more publications than other species we analyzed, we further examined the trends for Arabidopsis publications. The increase in the normalized number (i.e., relative to the entire plant science corpus) of Arabidopsis records coincided with advocacy of its use as a model system in the late 1980s [ 32 ]. While it remains a major plant model, there has been a decrease in overall Arabidopsis publications relative to all other plant science publications since 2011 (blue line, normalized total, Fig 4C ). Because the same chronological bins, each with same numbers of records, from the topic-over-time analysis ( Fig 3 ) were used, the decrease here does not mean that there were fewer Arabidopsis publications—in fact, the number of Arabidopsis papers has remained steady since 2011. This decrease means that Arabidopsis-related publications represent a relatively smaller proportion of plant science records. Interestingly, this decrease took place much earlier (approximately 2005) and was steeper in the United States (red line, Fig 4C ) than in all countries combined (blue line, Fig 4C ).

(A) Percentage of records mentioning specific genera. (B) Change in the prevalence of genera in plant science records over time. (C) Changes in the normalized numbers of all records (blue) and records from the US (red) mentioning Arabidopsis over time. The lines are LOWESS fits with fraction parameter = 0.2. (D) Topical over (red) and under (blue) representation among 5 genera with the most plant science records. LLR: log 2 likelihood ratios of each topic in each genus. Gray: topic-species combination not significantly enriched at the 5% level based on enrichment p -values adjusted for multiple testing with the Benjamini–Hochberg method [ 33 ]. The data used for plotting are in S9 Data . The statistics for all topics are in S10 Data .

https://doi.org/10.1371/journal.pbio.3002612.g004

Assuming that the normalized number of publications reflects the relative intensity of research activities, one hypothesis for the relative decrease in focus on Arabidopsis is that advances in, for example, plant transformation, genetic manipulation, and genome research have allowed the adoption of more previously nonmodel taxa. Consistent with this, there was a precipitous increase in the number of genera being published in the mid-90s to early 2000s during which approaches for plant transgenics became established [ 34 ], but the number has remained steady since then ( S7A Fig ). The decrease in the proportion of Arabidopsis papers is also negatively correlated with the timing of an increase in the number of draft genomes ( S7B Fig and S9 Data ). It is plausible that genome availability for other species may have contributed to a shift away from Arabidopsis. Strikingly, when we analyzed US National Science Foundation records, we found that the numbers of funded grants mentioning Arabidopsis ( S7C Fig ) have risen and fallen in near perfect synchrony with the normalized number of Arabidopsis publication records (red line, Fig 4C ). This finding likely illustrates the impact of funding on Arabidopsis research.

By considering both taxa information and research topics, we can identify clear differences in the topical areas preferred by researchers using different plant taxa ( Fig 4D and S10 Data ). For example, studies of auxin/light signaling, the circadian clock, and flowering tend to be carried out in Arabidopsis, while quantitative genetic studies of disease resistance tend to be done in wheat and rice, glyphosate research in soybean, and RNA virus research in tobacco. Taken together, joint analyses of topics and species revealed additional details about changes in preferred models over time, and the preferred topical areas for different taxa.

Countries differ in their contributions to plant science and topical preference

We next investigated whether there were geographical differences in topical preference among countries by inferring country information from 330,187 records (see Materials and methods ). The 10 countries with the most records account for 73% of the total, with China and the US contributing to approximately 18% each ( Fig 5A ). The exponential growth in plant science records (green line, Fig 1A ) was in large part due to the rapid rise in annual record numbers in China and India ( Fig 5B ). When we examined the publication growth rates using the top 17 plant science journals, the general patterns remained the same ( S7D Fig ). On the other hand, the US, Japan, Germany, France, and Great Britain had slower rates of growth compared with all non-top 10 countries. The rapid increase in records from China and India was accompanied by a rapid increase in metrics measuring journal impact ( Figs 5C and S8 and S9 Data ). For example, using citation score ( Fig 5C , see Materials and methods ), we found that during a 22-year period China (dark green) and India (light green) rapidly approached the global average (y = 0, yellow), whereas some of the other top 10 countries, particularly the US (red) and Japan (yellow green), showed signs of decrease ( Fig 5C ). It remains to be determined whether these geographical trends reflect changes in priority, investment, and/or interest in plant science research.

(A) Numbers of plant science records for countries with the 10 highest numbers. (B) Percentage of all records from each of the top 10 countries from 1980 to 2020. (C) Difference in citation scores from 1999 to 2020 for the top 10 countries. (D) Shown for each country is the relationship between the citation scores averaged from 1999 to 2020 and the slope of linear fit with year as the predictive variable and citation score as the response variable. The countries with >400 records and with <10% missing impact values are included. Data used for plots (A–D) are in S11 Data . (E) Correlation in topic enrichment scores between the top 10 countries. PCC, Pearson’s correlation coefficient, positive in red, negative in blue. Yellow rectangle: countries with more similar topical preferences. (F) Enrichment scores (LLR, log likelihood ratio) of selected topics among the top 10 countries. Red: overrepresentation, blue: underrepresentation. Gray: topic-country combination that is not significantly enriched at the 5% level based on enrichment p -values adjusted for multiple testing with the Benjamini–Hochberg method (for all topics and plotting data, see S12 Data ).

https://doi.org/10.1371/journal.pbio.3002612.g005

Interestingly, the relative growth/decline in citation scores over time (measured as the slope of linear fit of year versus citation score) was significantly and negatively correlated with average citation score ( Fig 5D ); i.e., countries with lower overall metrics tended to experience the strongest increase in citation scores over time. Thus, countries that did not originally have a strong influence on plant sciences now have increased impact. These patterns were also observed when using H-index or journal rank as metrics ( S8 Fig and S11 Data ) and were not due to increased publication volume, as the metrics were normalized against numbers of records from each country (see Materials and methods ). In addition, the fact that different metrics with different caveats and assumptions yielded consistent conclusions indicates the robustness of our observations. We hypothesize that this may be a consequence of the ease in scientific communication among geographically isolated research groups. It could also be because of the prevalence of online journals that are open access, which makes scientific information more readily accessible. Or it can be due to the increasing international collaboration. In any case, the causes for such regression toward the mean are not immediately clear and should be addressed in future studies.

We also assessed how the plant research foci of countries differ by comparing topical preference (i.e., the degree of enrichment of plant science records in different topics) between countries. For example, Italy and Spain cluster together (yellow rectangle, Fig 5E ) partly because of similar research focusing on allergens (topic 0) and mycotoxins (topic 54) and less emphasis on gene family (topic 23) and stress tolerance (topic 28) studies ( Fig 5F , for the fold enrichment and corrected p -values of all topics, see S12 Data ). There are substantial differences in topical focus between countries ( S9 Fig ). For example, research on new plant compounds associated with herbal medicine (topic 69) is a focus in China but not in the US, but the opposite is true for population genetics and evolution (topic 86) ( Fig 5F ). In addition to revealing how plant science research has evolved over time, topic modeling provides additional insights into differences in research foci among different countries, which are informative for science policy considerations.

In this study, topic modeling revealed clear transitions among research topics, which represent shifts in research trends in plant sciences. One limitation of our study is the bias in the PubMed-based corpus. The cellular, molecular, and physiological aspects of plant sciences are well represented, but there are many fewer records related to evolution, ecology, and systematics. Our use of titles/abstracts from the top 17 plant science journals as positive examples allowed us to identify papers we typically see in these journals, but this may have led to us missing “outlier” articles, which may be the most exciting. Another limitation is the need to assign only one topic to a record when a study is interdisciplinary and straddles multiple topics. Furthermore, a limited number of large, inherently heterogeneous topics were summarized to provide a more concise interpretation, which undoubtedly underrepresents the diversity of plant science research. Despite these limitations, dynamic topic modeling revealed changes in plant science research trends that coincide with major shifts in biological science. While we were interested in identifying conceptual advances, our approach can identify the trend but the underlying causes for such trends, particularly key records leading to the growth in certain topics, still need to be identified. It also remains to be determined which changes in research trends lead to paradigm shifts as defined by Kuhn [ 35 ].

The key terms defining the topics frequently describe various technologies (e.g., topic 38/39: transformation, 40: genome editing, 59: genetic markers, 65: mass spectrometry, 69: nuclear magnetic resonance) or are indicative of studies enabled through molecular genetics and omics technologies (e.g., topic 8/60: genome, 11: epigenetic modifications, 18: molecular biological studies of macromolecules, 13: small RNAs, 61: quantitative genetics, 82/84: metagenomics). Thus, this analysis highlights how technological innovation, particularly in the realm of omics, has contributed to a substantial number of research topics in the plant sciences, a finding that likely holds for other scientific disciplines. We also found that the pattern of topic evolution is similar to that of succession, where older topics have mostly decreased in relative prevalence but appear to have been superseded by newer ones. One example is the rise of transcriptome-related topics and the correlated, reduced focus on regulation at levels other than transcription. This raises the question of whether research driven by technology negatively impacts other areas of research where high-throughput studies remain challenging.

One observation on the overall trends in plant science research is the approximately 10-year cycle in major shifts. One hypothesis is related to not only scientific advances but also to the fashion-driven aspect of science. Nonetheless, given that there were only 3 major shifts and the sample size is small, it is difficult to speculate as to why they happened. By analyzing the country of origin, we found that China and India have been the 2 major contributors to the growth in the plant science records in the last 20 years. Our findings also show an equalizing trend in global plant science where countries without a strong plant science publication presence have had an increased impact over the last 20 years. In addition, we identified significant differences in research topics between countries reflecting potential differences in investment and priorities. Such information is important for discerning differences in research trends across countries and can be considered when making policy decisions about research directions.

Materials and methods

Collection and preprocessing of a candidate plant science corpus.

For reproducibility purposes, a random state value of 20220609 was used throughout the study. The PubMed baseline files containing citation information ( ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/ ) were downloaded on November 11, 2021. To narrow down the records to plant science-related citations, a candidate citation was identified as having, within the titles and/or abstracts, at least one of the following words: “plant,” “plants,” “botany,” “botanical,” “planta,” and “plantarum” (and their corresponding upper case and plural forms), or plant taxon identifiers from NCBI Taxonomy ( https://www.ncbi.nlm.nih.gov/taxonomy ) or USDA PLANTS Database ( https://plants.sc.egov.usda.gov/home ). Note the search terms used here have nothing to do with the values of the keyword field in PubMed records. The taxon identifiers include all taxon names including and at taxonomic levels below “Viridiplantae” till the genus level (species names not used). This led to 51,395 search terms. After looking for the search terms, qualified entries were removed if they were duplicated, lacked titles and/or abstracts, or were corrections, errata, or withdrawn articles. This left 1,385,417 citations, which were considered the candidate plant science corpus (i.e., a collection of texts). For further analysis, the title and abstract for each citation were combined into a single entry. Text was preprocessed by lowercasing, removing stop-words (i.e., common words), removing non-alphanumeric and non-white space characters (except Greek letters, dashes, and commas), and applying lemmatization (i.e., grouping inflected forms of a word as a single word) for comparison. Because lemmatization led to truncated scientific terms, it was not included in the final preprocessing pipeline.

Definition of positive/negative examples

Upon closer examination, a large number of false positives were identified in the candidate plant science records. To further narrow down citations with a plant science focus, text classification was used to distinguish plant science and non-plant science articles (see next section). For the classification task, a negative set (i.e., non-plant science citations) was defined as entries from 7,360 journals that appeared <20 times in the filtered data (total = 43,329, journal candidate count, S1 Data ). For the positive examples (i.e., true plant science citations), 43,329 plant science citations (positive examples) were sampled from 17 established plant science journals each with >2,000 entries in the filtered dataset: “Plant physiology,” “Frontiers in plant science,” “Planta,” “The Plant journal: for cell and molecular biology,” “Journal of experimental botany,” “Plant molecular biology,” “The New phytologist,” “The Plant cell,” “Phytochemistry,” “Plant & cell physiology,” “American journal of botany,” “Annals of botany,” “BMC plant biology,” “Tree physiology,” “Molecular plant-microbe interactions: MPMI,” “Plant biology,” and “Plant biotechnology journal” (journal candidate count, S1 Data ). Plant biotechnology journal was included, but only 1,894 records remained after removal of duplicates, articles with missing info, and/or withdrawn articles. The positive and negative sets were randomly split into training and testing subsets (4:1) while maintaining a 1:1 positive-to-negative ratio.

Text classification based on Tf and Tf-Idf

Instead of using the preprocessed text as features for building classification models directly, text embeddings (i.e., representations of texts in vectors) were used as features. These embeddings were generated using 4 approaches (model summary, S1 Data ): Term-frequency (Tf), Tf-Idf [ 36 ], Word2Vec [ 37 ], and BERT [ 6 ]. The Tf- and Tf-Idf-based features were generated with CountVectorizer and TfidfVectorizer, respectively, from Scikit-Learn [ 38 ]. Different maximum features (1e4 to 1e5) and n-gram ranges (uni-, bi-, and tri-grams) were tested. The features were selected based on the p- value of chi-squared tests testing whether a feature had a higher-than-expected value among the positive or negative classes. Four different p- value thresholds were tested for feature selection. The selected features were then used to retrain vectorizers with the preprocessed training texts to generate feature values for classification. The classification model used was XGBoost [ 39 ] with 5 combinations of the following hyperparameters tested during 5-fold stratified cross-validation: min_child_weight = (1, 5, 10), gamma = (0.5, 1, 1.5, 2.5), subsample = (0.6, 0.8, 1.0), colsample_bytree = (0.6, 0.8, 1.0), and max_depth = (3, 4, 5). The rest of the hyperparameters were held constant: learning_rate = 0.2, n_estimators = 600, objective = binary:logistic. RandomizedSearchCV from Scikit-Learn was used for hyperparameter tuning and cross-validation with scoring = F1-score.

Because the Tf-Idf model had a relatively high model performance and was relatively easy to interpret (terms are frequency-based, instead of embedding-based like those generated by Word2Vec and BERT), the Tf-Idf model was selected as input to SHapley Additive exPlanations (SHAP; [ 14 ]) to assess the importance of terms. Because the Tf-Idf model was based on XGBoost, a tree-based algorithm, the TreeExplainer module in SHAP was used to determine a SHAP value for each entry in the training dataset for each Tf-Idf feature. The SHAP value indicates the degree to which a feature positively or negatively affects the underlying prediction. The importance of a Tf-Idf feature was calculated as the average SHAP value of that feature among all instances. Because a Tf-Idf feature is generated based on a specific term, the importance of the Tf-Idf feature indicates the importance of the associated term.

Text classification based on Word2Vec

The preprocessed texts were first split into train, validation, and test subsets (8:1:1). The texts in each subset were converted to 3 n-gram lists: a unigram list obtained by splitting tokens based on the space character, or bi- and tri-gram lists built with Gensim [ 40 ]. Each n-gram list of the training subset was next used to fit a Skip-gram Word2Vec model with vector_size = 300, window = 8, min_count = (5, 10, or 20), sg = 1, and epochs = 30. The Word2Vec model was used to generate word embeddings for train, validate, and test subsets. In the meantime, a tokenizer was trained with train subset unigrams using Tensorflow [ 41 ] and used to tokenize texts in each subset and turn each token into indices to use as features for training text classification models. To ensure all citations had the same number of features (500), longer texts were truncated, and shorter ones were zero-padded. A deep learning model was used to train a text classifier with an input layer the same size as the feature number, an attention layer incorporating embedding information for each feature, 2 bidirectional Long-Short-Term-Memory layers (15 units each), a dense layer (64 units), and a final, output layer with 2 units. During training, adam, accuracy, and sparse_categorical_crossentropy were used as the optimizer, evaluation metric, and loss function, respectively. The training process lasted 30 epochs with early stopping if validation loss did not improve in 5 epochs. An F1 score was calculated for each n-gram list and min_count parameter combination to select the best model (model summary, S1 Data ).

Text classification based on BERT models

Two pretrained models were used for BERT-based classification: DistilBERT (Hugging face repository [ 42 ] model name and version: distilbert-base-uncased [ 43 ]) and SciBERT (allenai/scibert-scivocab-uncased [ 16 ]). In both cases, tokenizers were retrained with the training data. BERT-based models had the following architecture: the token indices (512 values for each token) and associated masked values as input layers, pretrained BERT layer (512 × 768) excluding outputs, a 1D pooling layer (768 units), a dense layer (64 units), and an output layer (2 units). The rest of the training parameters were the same as those for Word2Vec-based models, except training lasted for 20 epochs. Cross-validation F1-scores for all models were compared and used to select the best model for each feature extraction method, hyperparameter combination, and modeling algorithm or architecture (model summary, S1 Data ). The best model was the Word2Vec-based model (min_count = 20, window = 8, ngram = 3), which was applied to the candidate plant science corpus to identify a set of plant science citations for further analysis. The candidate plant science records predicted as being in the positive class (421,658) by the model were collectively referred to as the “plant science corpus.”

Plant science record classification

In PubMed, 1,384,718 citations containing “plant” or any plant taxon names (from the phylum to genus level) were considered candidate plant science citations. To further distinguish plant science citations from those in other fields, text classification models were trained using titles and abstracts of positive examples consisting of citations from 17 plant science journals, each with >2,000 entries in PubMed, and negative examples consisting of records from journals with fewer than 20 entries in the candidate set. Among 4 models tested the best model (built with Word2Vec embeddings) had a cross validation F1 of 0.964 (random guess F1 = 0.5, perfect model F1 = 1, S1 Data ). When testing the model using 17,330 testing set citations independent from the training set, the F1 remained high at 0.961.

We also conducted another analysis attempting to use the MeSH term “Plants” as a benchmark. Records with the MeSH term “Plants” also include pharmaceutical studies of plants and plant metabolites or immunological studies of plants as allergens in journals that are not generally considered plant science journals (e.g., Acta astronautica , International journal for parasitology , Journal of chromatography ) or journals from local scientific societies (e.g., Acta pharmaceutica Hungarica , Huan jing ke xue , Izvestiia Akademii nauk . Seriia biologicheskaia ). Because we explicitly labeled papers from such journals as negative examples, we focused on 4,004 records with the “Plants” MeSH term published in the 17 plant science journals that were used as positive instances and found that 88.3% were predicted as the positive class. Thus, based on the MeSH term, there is an 11.7% false prediction rate.

We also enlisted 5 plant science colleagues (3 advanced graduate students in plant biology and genetic/genome science graduate programs, 1 postdoctoral breeder/quantitative biologist, and 1 postdoctoral biochemist/geneticist) to annotate 100 randomly selected abstracts as a reviewer suggested. Each record was annotated by 2 colleagues. Among 85 entries where the annotations are consistent between annotators, 48 were annotated as negative but with 7 predicted as positive (false positive rate = 14.6%) and 37 were annotated as positive but with 4 predicted as negative (false negative rate = 10.8%). To further benchmark the performance of the text classification model, we identified another 12 journals that focus on plant science studies to use as benchmarks: Current opinion in plant biology (number of articles: 1,806), Trends in plant science (1,723), Functional plant biology (1,717), Molecular plant pathology (1,573), Molecular plant (1,141), Journal of integrative plant biology (1,092), Journal of plant research (1,032), Physiology and molecular biology of plants (830), Nature plants (538), The plant pathology journal (443). Annual review of plant biology (417), and The plant genome (321). Among the 12,611 candidate plant science records, 11,386 were predicted as positive. Thus, there is a 9.9% false negative rate.

Global topic modeling

BERTopic [ 15 ] was used for preliminary topic modeling with n-grams = (1,2) and with an embedding initially generated by DistilBERT, SciBERT, or BioBERT (dmis-lab/biobert-base-cased-v1.2; [ 44 ]). The embedding models converted preprocessed texts to embeddings. The topics generated based on the 3 embeddings were similar ( S2 Data ). However, SciBERT-, BioBERT-, and distilBERT-based embedding models had different numbers of outlier records (268,848, 293,790, and 323,876, respectively) with topic index = −1. In addition to generating the fewest outliers, the SciBERT-based model led to the highest number of topics. Therefore, SciBERT was chosen as the embedding model for the final round of topic modeling. Modeling consisted of 3 steps. First, document embeddings were generated with SentenceTransformer [ 45 ]. Second, a clustering model to aggregate documents into clusters using hdbscan [ 46 ] was initialized with min_cluster_size = 500, metric = euclidean, cluster_selection_method = eom, min_samples = 5. Third, the embedding and the initialized hdbscan model were used in BERTopic to model topics with neighbors = 10, nr_topics = 500, ngram_range = (1,2). Using these parameters, 90 topics were identified. The initial topic assignments were conservative, and 241,567 records were considered outliers (i.e., documents not assigned to any of the 90 topics). After assessing the prediction scores of all records generated from the fitted topic models, the 95-percentile score was 0.0155. This score was used as the threshold for assigning outliers to topics: If the maximum prediction score was above the threshold and this maximum score was for topic t , then the outlier was assigned to t . After the reassignment, 49,228 records remained outliers. To assess if some of the outliers were not assigned because they could be assigned to multiple topics, the prediction scores of the records were used to put records into 100 clusters using k- means. Each cluster was then assessed to determine if the outlier records in a cluster tended to have higher prediction scores across multiple topics ( S2 Fig ).

Topics that are most and least well connected to other topics

The most well-connected topics in the network include topic 24 (stress mechanisms, median cosine similarity = 0.36), topic 42 (genes, stress, and transcriptomes, 0.34), and topic 35 (molecular genetics, 0.32, all t test p -values < 1 × 10 −22 ). The least connected topics include topic 0 (allergen research, median cosine similarity = 0.12), topic 21 (clock biology, 0.12), topic 1 (tissue culture, 0.15), and topic 69 (identification of compounds with spectroscopic methods, 0.15; all t test p- values < 1 × 10 −24 ). Topics 0, 1, and 69 are specialized topics; it is surprising that topic 21 is not as well connected as explained in the main text.

Analysis of documents based on the topic model

Topical diversity among top journals with the most plant science records

Using a relative topic diversity measure (ranging from 0 to 10), we found that there was a wide range of topical diversity among 20 journals with the largest numbers of plant science records ( S3 Fig ). The 4 journals with the highest relative topical diversities are Proceedings of the National Academy of Sciences , USA (9.6), Scientific Reports (7.1), Plant Physiology (6.7), and PLOS ONE (6.4). The high diversities are consistent with the broad, editorial scopes of these journals. The 4 journals with the lowest diversities are American Journal of Botany (1.6), Oecologia (0.7), Plant Disease (0.7), and Theoretical and Applied Genetics (0.3), which reflects their discipline-specific focus and audience of classical botanists, ecologists, plant pathologists, and specific groups of geneticists.

Dynamic topic modeling

The codes for dynamic modeling were based on _topic_over_time.py in BERTopics and modified to allow additional outputs for debugging and graphing purposes. The plant science citations were binned into 50 subsets chronologically (for timestamps of bins, see S5 Data ). Because the numbers of documents increased exponentially over time, instead of dividing them based on equal-sized time intervals, which would result in fewer records at earlier time points and introduce bias, we divided them into time bins of similar size (approximately 8,400 documents). Thus, the earlier time subsets had larger time spans compared with later time subsets. If equal-size time intervals were used, the numbers of documents between the intervals would differ greatly; the earlier time points would have many fewer records, which may introduce bias. Prior to binning the subsets, the publication dates were converted to UNIX time (timestamp) in seconds; the plant science records start in 1917-11-1 (timestamp = −1646247600.0) and end in 2021-1-1 (timestamp = 1609477201). The starting dates and corresponding timestamps for the 50 subsets including the end date are in S6 Data . The input data included the preprocessed texts, topic assignments of records from global topic modeling, and the binned timestamps of records. Three additional parameters were set for topics_over_time, namely, nr_bin = 50 (number of bins), evolution_tuning = True, and global_tuning = False. The evolution_tuning parameter specified that averaged c-Tf-Idf values for a topic be calculated in neighboring time bins to reduce fluctuation in c-Tf-Idf values. The global_tuning parameter was set to False because of the possibility that some nonexisting terms could have a high c-Tf-Idf for a time bin simply because there was a high global c-Tf-Idf value for that term.

The binning strategy based on similar document numbers per bin allowed us to increase signal particularly for publications prior to the 90s. This strategy, however, may introduce more noise for bins with smaller time durations (i.e., more recent bins) because of publication frequencies (there can be seasonal differences in the number of papers published, biased toward, e.g., the beginning of the year or the beginning of a quarter). To address this, we examined the relative frequencies of each topic over time ( S7 Data ), but we found that recent time bins had similar variances in relative frequencies as other time bins. We also moderated the impact of variation using LOWESS (10% to 30% of the data points were used for fitting the trend lines) to determine topical trends for Fig 3 . Thus, the influence of the noise introduced via our binning strategy is expected to be minimal.

Topic categories and ordering

The topics were classified into 5 categories with contrasting trends: stable, early, transitional, sigmoidal, and rising. To define which category a topic belongs to, the frequency of documents over time bins for each topic was analyzed using 3 regression methods. We first tried 2 forecasting methods: recursive autoregressor (the ForecasterAutoreg class in the skforecast package) and autoregressive integrated moving average (ARIMA implemented in the pmdarima package). In both cases, the forecasting results did not clearly follow the expected trend lines, likely due to the low numbers of data points (relative frequency values), which resulted in the need to extensively impute missing data. Thus, as a third approach, we sought to fit the trendlines with the data points using LOWESS (implemented in the statsmodels package) and applied additional criteria for assigning topics to categories. When fitting with LOWESS, 3 fraction parameters (frac, the fraction of the data used when estimating each y-value) were evaluated (0.1, 0.2, 0.3). While frac = 0.3 had the smallest errors for most topics, in situations where there were outliers, frac = 0.2 or 0.1 was chosen to minimize mean squared errors ( S7 Data ).

The topics were classified into 5 categories based on the slopes of the fitted line over time: (1) stable: topics with near 0 slopes over time; (2) early: topics with negative (<−0.5) slopes throughout (with the exception of topic 78, which declined early on but bounced back by the late 1990s); (3) transitional: early positive (>0.5) slopes followed by negative slopes at later time points; (4) sigmoidal: early positive slopes followed by zero slopes at later time points; and (5) rising: continuously positive slopes. For each topic, the LOWESS fits were also used to determine when the relative document frequency reached its peak, first reaching a threshold of 0.6 (chosen after trial and error for a range of 0.3 to 0.9), and the overall trend. The topics were then ordered based on (1) whether they belonged to the stable category or not; (2) whether the trends were decreasing, stable, or increasing; (3) the time the relative document frequency first reached 0.6; and (4) the time that the overall peak was reached ( S8 Data ).

Taxa information

To identify a taxon or taxa in all plant science records, NCBI Taxonomy taxdump datasets were downloaded from the NCBI FTP site ( https://ftp.ncbi.nlm.nih.gov/pub/taxonomy/new_taxdump/ ) on September 20, 2022. The highest-level taxon was Viridiplantae, and all its child taxa were parsed and used as queries in searches against the plant science corpus. In addition, a species-over-time analysis was conducted using the same time bins as used for dynamic topic models. The number of records in different time bins for top taxa are in the genus, family, order, and additional species level sheet in S9 Data . The degree of over-/underrepresentation of a taxon X in a research topic T was assessed using the p -value of a Fisher’s exact test for a 2 × 2 table consisting of the numbers of records in both X and T, in X but not T, in T but not X, and in neither ( S10 Data ).

For analysis of plant taxa with genome information, genome data of taxa in Viridiplantae were obtained from the NCBI Genome data-hub ( https://www.ncbi.nlm.nih.gov/data-hub/genome ) on October 28, 2022. There were 2,384 plant genome assemblies belonging to 1,231 species in 559 genera (genome assembly sheet, S9 Data ). The date of the assembly was used as a proxy for the time when a genome was sequenced. However, some species have updated assemblies and have more recent data than when the genome first became available.

Taxa being studied in the plant science records

Flowering plants (Magnoliopsida) are found in 93% of records, while most other lineages are discussed in <1% of records, with conifers and related species being exceptions (Acrogynomsopermae, 3.5%, S6A Fig ). At the family level, the mustard (Brassicaceae), grass (Poaceae), pea (Fabaceae), and nightshade (Solanaceae) families are in 51% of records ( S6B Fig ). The prominence of the mustard family in plant science research is due to the Brassica and Arabidopsis genera ( Fig 4A ). When examining the prevalence of taxa being studied over time, clear patterns of turnovers emerged ( Figs 4B , S6C, and S6D ). While the study of monocot species (Liliopsida) has remained steady, there was a significant uptick in the prevalence of eudicot (eudicotyledon) records in the late 90s ( S6C Fig ), which can be attributed to the increased number of studies in the mustard, myrtle (Myrtaceae), and mint (Lamiaceae) families among others ( S6D Fig ). At the genus level, records mentioning Gossypium (cotton), Phaseolus (bean), Hordeum (wheat), and Zea (corn), similar to the topics in the early category, were prevalent till the 1980s or 1990s but have mostly decreased in number since ( Fig 4B ). In contrast, Capsicum , Arabidopsis , Oryza , Vitus , and Solanum research has become more prevalent over the last 20 years.

Geographical information for the plant science corpus

The geographical information (country) of authors in the plant science corpus was obtained from the address (AD) fields of first authors in Medline XML records accessible through the NCBI EUtility API ( https://www.ncbi.nlm.nih.gov/books/NBK25501/ ). Because only first author affiliations are available for records published before December 2014, only the first author’s location was considered to ensure consistency between records before and after that date. Among the 421,658 records in the plant science corpus, 421,585 had Medline records and 421,276 had unique PMIDs. Among the records with unique PMIDs, 401,807 contained address fields. For each of the remaining records, the AD field content was split into tokens with a “,” delimiter, and the token likely containing geographical info (referred to as location tokens) was selected as either the last token or the second to last token if the last token contained “@” indicating the presence of an email address. Because of the inconsistency in how geographical information was described in the location tokens (e.g., country, state, city, zip code, name of institution, and different combinations of the above), the following 4 approaches were used to convert location tokens into countries.

The first approach was a brute force search where full names and alpha-3 codes of current countries (ISO 3166–1), current country subregions (ISO 3166–2), and historical country (i.e., country that no longer exists, ISO 3166–3) were used to search the address fields. To reduce false positives using alpha-3 codes, a space prior to each code was required for the match. The first approach allowed the identification of 361,242, 16,573, and 279,839 records with current country, historical country, and subregion information, respectively. The second method was the use of a heuristic based on common address field structures to identify “location strings” toward the end of address fields that likely represent countries, then the use of the Python pycountry module to confirm the presence of country information. This approach led to 329,025 records with country information. The third approach was to parse first author email addresses (90,799 records), recover top-level domain information, and use country code Top Level Domain (ccTLD) data from the ISO 3166 Wikipedia page to define countries (72,640 records). Only a subset of email addresses contains country information because some are from companies (.com), nonprofit organizations (.org), and others. Because a large number of records with address fields still did not have country information after taking the above 3 approaches, another approach was implemented to query address fields against a locally installed Nominatim server (v.4.2.3, https://github.com/mediagis/nominatim-docker ) using OpenStreetMap data from GEOFABRIK ( https://www.geofabrik.de/ ) to find locations. Initial testing indicated that the use of full address strings led to false positives, and the computing resource requirement for running the server was high. Thus, only location strings from the second approach that did not lead to country information were used as queries. Because multiple potential matches were returned for each query, the results were sorted based on their location importance values. The above steps led to an additional 72,401 records with country information.

Examining the overlap in country information between approaches revealed that brute force current country and pycountry searches were consistent 97.1% of the time. In addition, both approaches had high consistency with the email-based approach (92.4% and 93.9%). However, brute force subregion and Nominatim-based predictions had the lowest consistencies with the above 3 approaches (39.8% to 47.9%) and each other. Thus, a record’s country information was finalized if the information was consistent between any 2 approaches, except between the brute force subregion and Nominatim searches. This led to 330,328 records with country information.

Topical and country impact metrics

To determine annual country impact, impact scores were determined in the same way as that for annual topical impact, except that values for different countries were calculated instead of topics ( S8 Data ).

Topical preferences by country

To determine topical preference for a country C , a 2 × 2 table was established with the number of records in topic T from C , the number of records in T but not from C , the number of non- T records from C , and the number of non- T records not from C . A Fisher’s exact test was performed for each T and C combination, and the resulting p -values were corrected for multiple testing with the Bejamini–Hochberg method (see S12 Data ). The preference of T in C was defined as the degree of enrichment calculated as log likelihood ratio of values in the 2 × 2 table. Topic 5 was excluded because >50% of the countries did not have records for this topic.

The top 10 countries could be classified into a China–India cluster, an Italy–Spain cluster, and remaining countries (yellow rectangles, Fig 5E ). The clustering of Italy and Spain is partly due to similar research focusing on allergens (topic 0) and mycotoxins (topic 54) and less emphasis on gene family (topic 23) and stress tolerance (topic 28) studies ( Figs 5F and S9 ). There are also substantial differences in topical focus between countries. For example, plant science records from China tend to be enriched in hyperspectral imaging and modeling (topic 9), gene family studies (topic 23), stress biology (topic 28), and research on new plant compounds associated with herbal medicine (topic 69), but less emphasis on population genetics and evolution (topic 86, Fig 5F ). In the US, there is a strong focus on insect pest resistance (topic 75), climate, community, and diversity (topic 83), and population genetics and evolution but less focus on new plant compounds. In summary, in addition to revealing how plant science research has evolved over time, topic modeling provides additional insights into differences in research foci among different countries.

Supporting information

S1 fig. plant science record classification model performance..

(A–C) Distributions of prediction probabilities (y_prob) of (A) positive instances (plant science records), (B) negative instances (non-plant science records), and (C) positive instances with the Medical Subject Heading “Plants” (ID = D010944). The data are color coded in blue and orange if they are correctly and incorrectly predicted, respectively. The lower subfigures contain log10-transformed x axes for the same distributions as the top subfigure for better visualization of incorrect predictions. (D) Prediction probability distribution for candidate plant science records. Prediction probabilities plotted here are available in S13 Data .

https://doi.org/10.1371/journal.pbio.3002612.s001

S2 Fig. Relationships between outlier clusters and the 90 topics.

(A) Heatmap demonstrating that some outlier clusters tend to have high prediction scores for multiple topics. Each cell shows the average prediction score of a topic for records in an outlier cluster. (B) Size of outlier clusters.

https://doi.org/10.1371/journal.pbio.3002612.s002

S3 Fig. Cosine similarities between topics.

(A) Heatmap showing cosine similarities between topic pairs. Top-left: hierarchical clustering of the cosine similarity matrix using the Ward algorithm. The branches are colored to indicate groups of related topics. (B) Topic labels and names. The topic ordering was based on hierarchical clustering of topics. Colored rectangles: neighboring topics with >0.5 cosine similarities.

https://doi.org/10.1371/journal.pbio.3002612.s003

S4 Fig. Relative topical diversity for 20 journals.

The 20 journals with the most plant science records are shown. The journal names were taken from the journal list in PubMed ( https://www.nlm.nih.gov/bsd/serfile_addedinfo.html ).

https://doi.org/10.1371/journal.pbio.3002612.s004

S5 Fig. Topical frequency and top terms during different time periods.

(A-D) Different patterns of topical frequency distributions for example topics (A) 48, (B) 35, (C) 27, and (D) 42. For each topic, the top graph shows the frequency of topical records in each time bin, which are the same as those in Fig 3 (green line), and the end date for each bin is indicated. The heatmap below each line plot depicts whether a term is among the top terms in a time bin (yellow) or not (blue). Blue dotted lines delineate different decades (see S5 Data for the original frequencies, S6 Data for the LOWESS fitted frequencies and the top terms for different topics/time bins).

https://doi.org/10.1371/journal.pbio.3002612.s005

S6 Fig. Prevalence of records mentioning different taxonomic groups in Viridiplantae.

(A, B) Percentage of records mentioning specific taxa at the ( A) major lineage and (B) family levels. (C, D) The prevalence of taxon mentions over time at the (C) major lineage and (E) family levels. The data used for plotting are available in S9 Data .

https://doi.org/10.1371/journal.pbio.3002612.s006

S7 Fig. Changes over time.

(A) Number of genera being mentioned in plant science records during different time bins (the date indicates the end date of that bin, exclusive). (B) Numbers of genera (blue) and organisms (salmon) with draft genomes available from National Center of Biotechnology Information in different years. (C) Percentage of US National Science Foundation (NSF) grants mentioning the genus Arabidopsis over time with peak percentage and year indicated. The data for (A–C) are in S9 Data . (D) Number of plant science records in the top 17 plant science journals from the USA (red), Great Britain (GBR) (orange), India (IND) (light green), and China (CHN) (dark green) normalized against the total numbers of publications of each country over time in these 17 journals. The data used for plotting can be found in S11 Data .

https://doi.org/10.1371/journal.pbio.3002612.s007

S8 Fig. Change in country impact on plant science over time.

(A, B) Difference in 2 impact metrics from 1999 to 2020 for the 10 countries with the highest number of plant science records. (A) H-index. (B) SCImago Journal Rank (SJR). (C, D) Plots show the relationships between the impact metrics (H-index in (C) , SJR in (D) ) averaged from 1999 to 2020 and the slopes of linear fits with years as the predictive variable and impact metric as the response variable for different countries (A3 country codes shown). The countries with >400 records and with <10% missing impact values are included. The data used for plotting can be found in S11 Data .

https://doi.org/10.1371/journal.pbio.3002612.s008

S9 Fig. Country topical preference.

Enrichment scores (LLR, log likelihood ratio) of topics for each of the top 10 countries. Red: overrepresentation, blue: underrepresentation. The data for plotting can be found in S12 Data .

https://doi.org/10.1371/journal.pbio.3002612.s009

S1 Data. Summary of source journals for plant science records, prediction models, and top Tf-Idf features.

Sheet–Candidate plant sci record j counts: Number of records from each journal in the candidate plant science corpus (before classification). Sheet—Plant sci record j count: Number of records from each journal in the plant science corpus (after classification). Sheet–Model summary: Model type, text used (txt_flag), and model parameters used. Sheet—Model performance: Performance of different model and parameter combinations on the validation data set. Sheet–Tf-Idf features: The average SHAP values of Tf-Idf (Term frequency-Inverse document frequency) features associated with different terms. Sheet–PubMed number per year: The data for PubMed records in Fig 1A . Sheet–Plant sci record num per yr: The data for the plant science records in Fig 1A .

https://doi.org/10.1371/journal.pbio.3002612.s010

S2 Data. Numbers of records in topics identified from preliminary topic models.

Sheet–Topics generated with a model based on BioBERT embeddings. Sheet–Topics generated with a model based on distilBERT embeddings. Sheet–Topics generated with a model based on SciBERT embeddings.

https://doi.org/10.1371/journal.pbio.3002612.s011

S3 Data. Final topic model labels and top terms for topics.

Sheet–Topic label: The topic index and top 10 terms with the highest cTf-Idf values. Sheets– 0 to 89: The top 50 terms and their c-Tf-Idf values for topics 0 to 89.

https://doi.org/10.1371/journal.pbio.3002612.s012

S4 Data. UMAP representations of different topics.

For a topic T , records in the UMAP graph are colored red and records not in T are colored gray.

https://doi.org/10.1371/journal.pbio.3002612.s013

S5 Data. Temporal relationships between published documents projected onto 2D space.

The 2D embedding generated with UMAP was used to plot document relationships for each year. The plots from 1975 to 2020 were compiled into an animation.

https://doi.org/10.1371/journal.pbio.3002612.s014

S6 Data. Timestamps and dates for dynamic topic modeling.

Sheet–bin_timestamp: Columns are: (1) order index; (2) bin_idx–relative positions of bin labels; (3) bin_timestamp–UNIX time in seconds; and (4) bin_date–month/day/year. Sheet–Topic frequency per timestamp: The number of documents in each time bin for each topic. Sheets–LOWESS fit 0.1/0.2/0.3: Topic frequency per timestamp fitted with the fraction parameter of 0.1, 0.2, or 0.3. Sheet—Topic top terms: The top 5 terms for each topic in each time bin.

https://doi.org/10.1371/journal.pbio.3002612.s015

S7 Data. Locally weighted scatterplot smoothing (LOWESS) of topical document frequencies over time.

There are 90 scatter plots, one for each topic, where the x axis is time, and the y axis is the document frequency (blue dots). The LOWESS fit is shown as orange points connected with a green line. The category a topic belongs to and its order in Fig 3 are labeled on the top left corner. The data used for plotting are in S6 Data .

https://doi.org/10.1371/journal.pbio.3002612.s016

S8 Data. The 4 criteria used for sorting topics.

Peak: the time when the LOWESS fit of the frequencies of a topic reaches maximum. 1st_reach_thr: the time when the LOWESS fit first reaches a threshold of 60% maximal frequency (peak value). Trend: upward (1), no change (0), or downward (−1). Stable: whether a topic belongs to the stable category (1) or not (0).

https://doi.org/10.1371/journal.pbio.3002612.s017

S9 Data. Change in taxon record numbers and genome assemblies available over time.

Sheet–Genus: Number of records mentioning a genus during different time periods (in Unix timestamp) for the top 100 genera. Sheet–Genus: Number of records mentioning a family during different time periods (in Unix timestamp) for the top 100 families. Sheet–Genus: Number of records mentioning an order during different time periods (in Unix timestamp) for the top 20 orders. Sheet–Species levels: Number of records mentioning 12 selected taxonomic levels higher than the order level during different time periods (in Unix timestamp). Sheet–Genome assembly: Plant genome assemblies available from NCBI as of October 28, 2022. Sheet–Arabidopsis NSF: Absolute and normalized numbers of US National Science Foundation funded proposals mentioning Arabidopsis in proposal titles and/or abstracts.

https://doi.org/10.1371/journal.pbio.3002612.s018

S10 Data. Taxon topical preference.

Sheet– 5 genera LLR: The log likelihood ratio of each topic in each of the top 5 genera with the highest numbers of plant science records. Sheets– 5 genera: For each genus, the columns are: (1) topic; (2) the Fisher’s exact test p -value (Pvalue); (3–6) numbers of records in topic T and in genus X (n_inT_inX), in T but not in X (n_inT_niX), not in T but in X (n_niT_inX), and not in T and X (n_niT_niX) that were used to construct 2 × 2 tables for the tests; and (7) the log likelihood ratio generated with the 2 × 2 tables. Sheet–corrected p -value: The 4 values for generating LLRs were used to conduct Fisher’s exact test. The p -values obtained for each country were corrected for multiple testing.

https://doi.org/10.1371/journal.pbio.3002612.s019

S11 Data. Impact metrics of countries in different years.

Sheet–country_top25_year_count: number of total publications and publications per year from the top 25 countries with the most plant science records. Sheet—country_top25_year_top17j: number of total publications and publications per year from the top 25 countries with the highest numbers of plant science records in the 17 plant science journals used as positive examples. Sheet–prank: Journal percentile rank scores for countries (3-letter country codes following https://www.iban.com/country-codes ) in different years from 1999 to 2020. Sheet–sjr: Scimago Journal rank scores. Sheet–hidx: H-Index scores. Sheet–cite: Citation scores.

https://doi.org/10.1371/journal.pbio.3002612.s020

S12 Data. Topical enrichment for the top 10 countries with the highest numbers of plant science publications.

Sheet—Log likelihood ratio: For each country C and topic T, it is defined as log((a/b)/(c/d)) where a is the number of papers from C in T, b is the number from C but not in T, c is the number not from C but in T, d is the number not from C and not in T. Sheet: corrected p -value: The 4 values, a, b, c, and d, were used to conduct Fisher’s exact test. The p -values obtained for each country were corrected for multiple testing.

https://doi.org/10.1371/journal.pbio.3002612.s021

S13 Data. Text classification prediction probabilities.

This compressed file contains the PubMed ID (PMID) and the prediction probabilities (y_pred) of testing data with both positive and negative examples (pred_prob_testing), plant science candidate records with the MeSH term “Plants” (pred_prob_candidates_with_mesh), and all plant science candidate records (pred_prob_candidates_all). The prediction probability was generated using the Word2Vec text classification models for distinguishing positive (plant science) and negative (non-plant science) records.

https://doi.org/10.1371/journal.pbio.3002612.s022

Acknowledgments

We thank Maarten Grootendorst for discussions on topic modeling. We also thank Stacey Harmer, Eva Farre, Ning Jiang, and Robert Last for discussion on their respective research fields and input on how to improve this study and Rudiger Simon for the suggestion to examine differences between countries. We also thank Mae Milton, Christina King, Edmond Anderson, Jingyao Tang, Brianna Brown, Kenia Segura Abá, Eleanor Siler, Thilanka Ranaweera, Huan Chen, Rajneesh Singhal, Paulo Izquierdo, Jyothi Kumar, Daniel Shiu, Elliott Shiu, and Wiggler Catt for their good ideas, personal and professional support, collegiality, fun at parties, as well as the trouble they have caused, which helped us improve as researchers, teachers, mentors, and parents.

• View Article
• PubMed/NCBI
• Google Scholar
• 2. Blei DM, Lafferty JD. Topic Models. In: Srivastava A, Sahami M, editors. Text Mining. Cambridge: Chapman and Hall/CRC; 2009. pp. 71–93.
• 7. ChatGPT. [cited 2023 Aug 25]. Available from: https://chat.openai.com
• 9. Fei-Fei L, Perona P. A Bayesian hierarchical model for learning natural scene categories. 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05); 2005. pp. 524–531 vol. 2. https://doi.org/10.1109/CVPR.2005.16
• 19. Blei DM, Lafferty JD. Dynamic topic models. Proceedings of the 23rd International Conference on Machine learning. New York, NY, USA: Association for Computing Machinery; 2006. pp. 113–120. https://doi.org/10.1145/1143844.1143859
• 35. Kuhn T. The Structure of Scientific Revolution. Chicago: University of Chicago Press; 1962.
• 36. CiteSeer | Proceedings of the second international conference on Autonomous agents. [cited 2023 Aug 23]. Available from: https://dl.acm.org/doi/10.1145/280765.280786
• 39. Chen T, Guestrin C. XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM; 2016. pp. 785–794. https://doi.org/10.1145/2939672.2939785
• 40. Řehůřek R, Sojka P. Software Framework for Topic Modelling with Large Corpora. Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks. Valletta, Malta: ELRA; 2010. pp. 45–50.
• 42. Hugging Face–The AI community building the future. 2023 Aug 19 [cited 2023 Aug 25]. Available from: https://huggingface.co/

Advertisement

Botanical gardens as valuable resources in plant sciences

• Review Paper
• Published: 02 January 2020
• Volume 31 , pages 2905–2926, ( 2022 )

Cite this article

• Leila Faraji 1 &
• Mojtaba Karimi   ORCID: orcid.org/0000-0003-4598-0172 2  

2708 Accesses

14 Citations

2 Altmetric

Explore all metrics

Botanical gardens are collections of plants cultivated in a closed space to be utilized for scientific inquiry, recreation, conservation, botanical and horticultural education and also for public landscape aesthetics. Due to their richness in plant diversity and also their facilities, botanical gardens can have remarkable roles in agricultural studies and plant sciences. In addition, botanical gardens are very important regarding to their roles in creating green space in urban spaces, tourist attractions, economical objects and well-being aspects of peoples. Accordingly, in this study, the roles of botanical gardens were reviewed regarding to biodiversity and genetic studies, seed science, plant protection, soil and water researches, ecological evaluation, climate change, research and educations. These topics were also discussed regarding to their usage in agriculture and plant science studies. Furthermore, some scientific potentials of botanical gardens for future studies have been also taken into account.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Alien flora of Mongolia: species richness, introduction dynamics and spatial patterns

Traditional Farming Practices and Its Consequences

Ecology and Use of Lantana camara in India

Adams RP (1993) The conservation and utilization of genes from endangered and extinct plants: DNA Bank-Net. In: Gustafson JP, Appels R, Raven P (eds) Gene Conservation and Exploitation. Springer, Boston, pp 35–52

Chapter   Google Scholar  

Andersen BA, Nicolaisen M, Nielsen SL (2002) Alternative hosts for potato mop-top virus, genus pomovirus and its vectorspongospora subterranea f. Sp. Subterranea. Potato Res 45:37–43

Article   Google Scholar  

Aptroot A, Honegger R (2006) Lichens in the new botanical garden of the University of Zürich, Switzerland. Bot Helv 116:135–148

Ashton PS (1988) Conservation of biological diversity in botanical gardens. Biodiversity 15:269–278

Google Scholar  

Aviezer I, Lev-Yadun S (2015) Pod and seed defensive coloration (camouflage and mimicry) in the genus Pisum . Isr J Plant Sci 62:39–51. https://doi.org/10.1080/07929978.2014.958392

Bakalin VA (2013) New taxa of solenostoma and plectocolea and other taxonomic novelties based on study of collections in the New York botanical garden herbarium. Pol Bot J 58:127–142

Bellardi M, Rubies-Autonell C, Bianchi A (2003) First report of a disease of peony caused by Alfalfa mosaic virus. Plant Dis 87:99–99

Article   CAS   PubMed   Google Scholar  

Bolmgren K, Lönnberg K (2005) Herbarium data reveal an association between fleshy fruit type and earlier flowering time. Int J Plant Sci 166:663–670

Bowers JE (2007) Has climatic warming altered spring flowering date of Sonoran Desert shrubs? Southwest Nat 52:347–356

Britton NL (2016) Botanical gardens. In: Genoways HH, Andrei MA (eds) Museum origins. Routledge, Abingdon, pp 277–282

Brownlee MT, Hallo JC, Krohn BD (2013) Botanical garden visitors' perceptions of local climate impacts: awareness, concern, and behavioral responses. Manag Leis 18:97–117

Busch J, Lösch R (1999) The gas exchange of Carex species from eutrophic wetlands and its dependence on microclimatic and soil wetness conditions. Phys Chem Earth, Part B 24:117–120

Chen J, Cannon CH, Hu H (2009) Tropical botanical gardens: at the in situ ecosystem management frontier. Trends Plant Sci 14:584–589

Chiarugi A (1953) Le date di fondazione dei primi Orti Botanici del Mondo: PISA (Estate 1543); Padova (7 Luglio 1545); Firenze (1° Dicembre 1545) Plant Biosystem 60:785–839

Cornish C, Driver F, Nesbitt M (2017) The Economic Botany Collection at Kew: Analysis of Accessions Data. Mobile Museum Working Paper 1 (June 2017)

Crane PR et al (2019) The Shenzhen declaration on plant sciences—uniting plant sciences and society to build a green, sustainable Earth. Plants, People, Planet 1:59–61

Davis K (2008) A CBD manual for botanic gardens. Botanic Gardens Conservation International, London

Davis CC, Willis CG, Connolly B, Kelly C, Ellison AM (2015) Herbarium records are reliable sources of phenological change driven by climate and provide novel insights into species' phenological cueing mechanisms. Am J Bot 102:1599–1609

Article   PubMed   Google Scholar  

De Carvalho M et al (2004) A review of the genus Semele (Ruscaceae) systematics in Madeira. Bot J Linn Soc 146:483–497

Del Prete C, Dallai D, Sgarbi E, Maffettone L (2006) The Modena Botanic Garden: plant conservation and habitat management strategies. In: Gafta D, Akeroyd J (eds) Nature Conservation. Springer, New York, pp 369–379

DeMarie E III (1996) The value of plant collections. Public Gard 11:7–31

Deng Q et al (2012) Effects of precipitation increase on soil respiration: a three-year field experiment in subtropical forests in China. PLoS ONE 7:e41493

Article   CAS   PubMed   PubMed Central   Google Scholar  

Dongming L, Qingwen Z, Hongfeng C, Yousheng W, Fuwu X (2003) Common Disease of Medicinal Plants in South China Botanical Garden. J Chin Med Mater 26(12):851–853

Dosmann MS (2006) Research in the garden: averting the collections crisis. Bot Rev 72:207–234

Droege G et al (2013) The global genome biodiversity network (GGBN) data portal. Nucleic Acids Res 42:D607–D612

Article   PubMed   PubMed Central   Google Scholar  

Engelmann F, Engels JMM (2002) Technologies and strategies for ex situ conservation. In: Brown A, Jackson M (eds) Managing plant genetic diversity. CAB International /IPGRI, Wallingford, pp 89–104

FAO FaAOTsotwspgrF, Rome Global Strategy for Plant Conservation (2002) Secretariat of the Convention on Biological Diversity (CBD, UNEP) in association with Botanic Gardens Conservation International (BGCI)

Falk JH (2005) Free-choice environmental learning: framing the discussion. Environ Educ Res 11:265–280

Fiz O, Vargas P, Alarcón M, Aedo C, García JL, Aldasoro JJ (2008) Phylogeny and historical biogeography of Geraniaceae in relation to climate changes and pollination ecology. Syst Bot 33:326–342

Foster JB (1999) The vulnerable planet: A short economic history of the environment. NYU Press, New York

Frankel OH, Brown AH, Burdon JJ (1995) The conservation of plant biodiversity. Cambridge University Press, Cambridge

Galbraith DA, Rapley WA (2005) Research at Canadian zoos and botanical gardens. Mus Manage Curatorship 20:313–331

Galera H, Ratyńska H (1999) Greenhouse weeds in the botanical garden of PAS in Warsaw-Powsin. Acta Soc Bot Pol 68:227–236

Gasperi-Campani A, Barbieri L, Lorenzoni E, Stirpe F (1977) Inhibition of protein synthesis by seed-extracts a screening study. FEBS Lett 76:173–176

Godefroid S, Van de Vyver A, Stoffelen P, Robbrecht E, Vanderborght T (2011) Testing the viability of seeds from old herbarium specimens for conservation purposes. Taxon 60:565–569

Gond SK, Mishra A, Sharma VK, Verma SK, Kumar J, Kharwar RN, Kumar A (2012) Diversity and antimicrobial activity of endophytic fungi isolated from Nyctanthes arbor-tristis, a well-known medicinal plant of India. Mycoscience 53:113–121

Goszczyński W, Golan K (2011) Scale insects on ornamental plants in confined spaces. Aphids and Other Hemipterous Insects 17:107–119

Gratani L, Crescente MF, Varone L, Fabrini G, Digiulio E (2008) Growth pattern and photosynthetic activity of different bamboo species growing in the Botanical Garden of Rome. Flora-Morphol, Distrib, Funct Ecol Plants 203:77–84

Greene EL (1910) Landmarks of botanical history: a study of certain epochs in the development of the science of botany, vol 54. Smithsonian institution, Washington

Griffiths M, Huxley A (1992) The new Royal Horticultural Society dictionary of gardening. Macmillan, London

Gyllenhaal C, Soejarto DD, Farnsworth NR, HUFT MJ (1990) The value of herbaria. Nature 347:704

Häder D-P, Griebenow K (1988) Orientation of the green flagellate, Euglena gracilis , in a vertical column of water. FEMS Microbiol Ecol 4:159–167

Hawksworth D (1995a) The resource base for biodiversity assessments. Global biodiversity assessment, pp 548–605

Hawksworth DL (1995b) Biodiversity: measurement and estimation, vol 345. Springer, New York

Hayden A (1910) The algal flora of the Missouri botanical garden. Missouri Bot Garden Annu Rep 1910:25–48

He H, Chen J (2012) Educational and enjoyment benefits of visitor education centers at botanical gardens. Biol Conserv 149:103–112

Herben T, Nováková Z, Klimešová J, Hrouda L (2012) Species traits and plant performance: functional trade-offs in a large set of species in a botanical garden. J Ecol 100:1522–1533

Heywood VH (1987) Changing role of the botanic garden. In: Botanic gardens and the world conservation strategy: proceedings of an International Conference 26–30 November 1985 held at Las Palmas de Gran Canaria/edited by D. Bramwell...[et al.], 1987. London: Academic Press

Heywood V (1991a) Botanic gardens and the conservation of medicinal plants Conservation of medicinal plants. Cambridge University Press, Cambridge, pp 213–228

Book   Google Scholar  

Heywood VH (1991b) Developing a strategy for germplasm conservation in botanic gardens. In: Heywood VH, Wyse Jackson PS (eds) Tropical botanic gardens - their role in conservation and development. Academic Press, pp 11–23

Heywood V (1992) Conservation of germplasm of wild species Conservation of Biodiversity for Sustainable Development. Scandinavian University Press, Oslo, pp 189–203

Hodkinson TR, Waldren S, Parnell JA, Kelleher CT, Salamin K, Salamin N (2007) DNA banking for plant breeding, biotechnology and biodiversity evaluation. J Plant Res 120:17–29

Hurka H (1994) Conservation genetics and the role of botanical gardens. In: Loeschcke V, Jain SK, Tomiuk J (eds) Conservation genetics. Springer, Berlin, pp 371–380

Hurka H, Neuffer B, Friesen N (2003) Plant genetic resources in botanical gardens. In: Forkmann G, Michaelis S (eds) XXI International Eucarpia 740 Symposium on Classical versus Molecular Breeding of Ornamentals-Part II 651. Acta Horticulturae, Leuven, pp 35–44

Hussain F, Shah SM (2009) Diversity and ecological characteristics of weeds of wheat fields of University of Peshawar Botanical Garden at Azakhel, District Nowshera. Pakistan. Pak J Weed Sci Res 15:4

Jain M, Johnson TS, Krishnan P (2012) Biotechnological approaches to conserve the wealth of nature: endangered and rare medicinal plant species, a review. J Nat Rem 12:93–102

CAS   Google Scholar  

Jalili A et al (2010) Climate change, unpredictable cold waves and possible brakes on plant migration. Global Ecol Biogeogr 19:642–648

Kahtz AW (1995) Impact of environmental education classes at Missouri Botanical Garden on attitude and knowledge change of elementary school children. HortTechnology 5:338–340

Karlson DT, Stirm VE, Shirazi A, Ashworth EN (2004) Phylogenetic analyses in Cornus substantiate ancestry of xylem supercooling freezing behavior and reveal lineage of desiccation related proteins. Plant Physiol 135:1654–1665

Knapp S (2019) People and plants: the unbreakable bond. Plants, People, Planet 1:20–26

Kneebone S, Willison J (2007) A global snapshot of botanic garden education provision. In: Building a sustainable future: the role of botanic gardens. Proceedings of the 3rd Global Botanic Gardens Congress, Wuhan, China, 16–20 April 2007. Botanic Gardens Conservation International, pp 1–14

Koczor S, Bagarus AK, Karap AK, Varga Á, Orosz A (2013) A rapidly spreading potential pest, orientus ishidae identified in Hungary. Bull Insectol 66:221–224

Komala Z, Przybos E (2000) Further investigations on the zooplankton of water bodies in the botanical garden of the Jagiellonian University in Kraków. Folia Biologica-Krakow 48:49–52

Kranz HD, Huss VA (1996) Molecular evolution of pteridophytes and their relationship to seed plants: evidence from complete 18S rRNA gene sequences. Plant Syst Evol 202:1–11

Article   CAS   Google Scholar  

Kreyling J, Schmid S, Aas G (2015) Cold tolerance of tree species is related to the climate of their native ranges. J Biogeogr 42:156–166

Krishnan S, Novy A (2016) The role of botanic gardens in the twenty-first century. CAB Rev 11:1–10

Krishnan S, Moreau T, Kuehny J, Novy A, Greene SL, Khoury CK (2019) Resetting the table for people and plants: Botanic gardens and research organizations collaborate to address food and agricultural plant blindness. Plants, People, Planet. https://doi.org/10.1002/ppp3.34

Lange O, Reichenberger H, Walz H (1997) Continuous monitoring of CO 2 exchange of lichens in the field: short-term enclosure with an automatically operating cuvette. Lichenol 29:259–274

Lavoie C, Lachance D (2006) A new herbarium-based method for reconstructing the phenology of plant species across large areas. Am J Bot 93:512–516

Lewis A, Affolter J (1999) The state botanical garden of Georgia: a living laboratory for student education. HortTechnology 9:570–572

Li D-Z, Pritchard HW (2009) The science and economics of ex situ plant conservation. Trends Plant Sci 14:614–621

Li X, Yin X (2004) Seed dispersal by birds in Nanjing Botanical Garden Mem. Sun Yat.-Sen in spring and summer. Acta Ecol Sin 24:1452–1458

Li X, Yin X, He S (2001) Tree fruits eaten by birds in Nanjing Botanical Garden Mem. Sun Yat-Sen in autumn and winter. Chin J Zool 36:20–24

Linington SH, Pritchard HW (2001) Gene banks. Elsevier, pp 641–653

Lu X, Siemann E, Shao X, Wei H, Ding J (2013) Climate warming affects biological invasions by shifting interactions of plants and herbivores. Global Change Biol 19:2339–2347

Lighty RW (1984) Toward a more rational approach to plant collections. The Longwood program seminars 16:5–9

Ma L, Fang X (2006) Effects of global warming on seasonal tourism for the last 20 years in Beijing: a case study on the peach flower stanza of Beijing botanical garden. Adv Earth Sci 21:313–319

Mariko S, Kachi N, Si I, Furukawa A (1992) Germination ecology of coastal plants in relation to salt environment. Ecol Res 7:225–233

Marler TE, Lindström AJ, Terry LI (2012) Chilades pandava damage among 85 Cycas species in a common garden setting. HortScience 47:1832–1836

Martinez SI, Biber-Klemm S (2010) Scientists—Take action for access to biodiversity. Curr Opin Environ Sustain 2:27–33

Maunder M (1994) Botanic gardens: future challenges and responsibilities. Biodiver Conserv 3:97–103

Maunder M, Higgens S, Culham A (2001) The effectiveness of botanic garden collections in supporting plant conservation: a European case study. Biodiver Conserv 10:383–401

Maxted N, Ford-Lloyd B, Hawkes J (2000) Complementary conservation strategies. In: Maxted N, Ford-Lloyd BV, Hawkes JG (eds) Plant genetic conservation. Springer, Dordrecht, pp 15–39

McCarthy HR, Pataki DE, Jenerette GD (2011) Plant water-use efficiency as a metric of urban ecosystem services. Ecol Appl 21:3115–3127

Miller A, Novy A, Glover J, Kellogg E, Maul J, Raven P, Jackson PW (2015) Expanding the role of botanical gardens in the future of food. Nat Plants 1:15078

Miller-Rushing AJ, Katsuki T, Primack RB, Ishii Y, Lee SD, Higuchi H (2007) Impact of global warming on a group of related species and their hybrids: cherry tree (Rosaceae) flowering at Mt. Takao. Japan. Am J Bot 94:1470–1478

Morari F, Giardini L (2001) Estimating evapotranspiration in the Padova botanical garden. Irrig Sci 20:127–137

Moreau T, Novy A (2018) Public education and outreach opportunities for crop wild relatives in North America. In: Greene S, Williams K, Khoury C, Kantar M, Marek L (eds) North American Crop Wild Relatives, vol 1. Springer, Berlin, pp 311–324

Nesbitt M (2014) Use of herbarium specimens in ethnobotany. In: Salick J, Konchar K, Nesbitt M (eds) Curating Biocultural Collections. Kew Publishing, Royal Botanic Gardens, Kew, pp 313–328

O'Donnell K, Sharrock S (2017) The contribution of botanic gardens to ex situ conservation through seed banking. Plant Diver 39:373–378

O'Donnell K, Sharrock S (2018) Botanic gardens complement agricultural gene bank in collecting and conserving plant genetic diversity. Biopreservation and Biobanking 16:384–390

Olaitan AF, Abiodun T (2011) Comparative toxicity of botanical and synthetic insecticides against major field insect pests of cowpea (Vigna unquiculata (L.) Walp). J Nat Prod Plant Resour 1:86–95

Olivares E, Medina E (1992) Water and nutrient relations of woody perennials from tropical dry forests. J Veg Sci 3:383–392. https://doi.org/10.2307/3235764

Onyango M, Onyango J. Conservation and seed production of African leafy vegetables at Maseno University botanic garden, Kenya. In: African Crop Science Confereence Proceedings, 2005. pp 1201–1204.

Panahi P, Jamzad Z, Pourhashemi M (2009) Acorn production of Zagros forests oaks and their qualitative characteristics in Zagros section of National Botanical Garden of Iran. J Forest Wood Prod 62:45–57

Panahi P, Pourhashemi M, Nejad MH (2011) Estimation of leaf biomass and leaf carbon sequestration of pistacia atlantica in National Botanical Garden of Iran. Iran J Forest 3:1–12

Pautasso M, Parmentier I (2007) Are the living collections of the world’s botanical gardens following species-richness patterns observed in natural ecosystems? Bot Helv 117:15–28

Pinheiro MH, de Almeida Neto LC, Monteiro R (2006) Urban areas and isolated remnants of natural habitats: an action proposal for botanical gardens. Human Exploitation and Biodiversity Conservation. Springer, Berlin, pp 407–424

Prance G (2000) The conservation of botanical diversity. Plant Genetic Conservation. Springer, Berlin, pp 3–14

Primack RB, Miller-Rushing AJ (2009) The role of botanical gardens in climate change research. New Phytol 182:303–313

Pyke GH, Ehrlich PR (2010) Biological collections and ecological/environmental research: a review, some observations and a look to the future. Biol Rev 85:247–266

Qiu J (2009) Where the rubber meets the garden. Nature Publishing Group, Berlin

Rae DA (1996) Botanic gardens and their live plant collections: present and future roles. The University of Edinburgh, Edinburgh

Rakow DA, Lee SA (2015) Western botanical gardens: history and evolution. Hortic Rev 43:269

Rauer G, Deutschland BfN (2000) Beitrag der deutschen Botanischen Gärten zur Erhaltung der biologischen Vielfalt und genetischer Ressourcen: Bestandsaufnahme und Entwicklungskonzept; Abschlußbericht des gleichlautenden F+ E-Vorhabens 808 05 070 des Bundesamtes für Naturschutz. Bundesamt für Naturschutz

Raven PH (1981) Research in botanical gardens. Bot Jahrb 102:52–72

Sanyal A, Sarkar B (1993) Ecology of soil oribatid mites in three contrasting sites at botanical garden, Howrah, West Bengal. Environ Ecol Kalyani 11:427–434

Schaal B (2019) Plants and people: our shared history and future. Plants, People, Planet 1:14–19

Schoen DJ, Brown AH (2001) The Conservation of Wild Plant Species in Seed Banks: attention to both taxonomic coverage and population biology will improve the role of seed banks as conservation tools. Bioscience 51:960–966

Schreiber L, Krimm U, Knoll D, Sayed M, Auling G, Kroppenstedt RM (2005) Plant–microbe interactions: identification of epiphytic bacteria and their ability to alter leaf surface permeability. New Phytol 166:589–594

Schultes RE (1977) The odyssey of the cultivated rubber tree. Endeavour 1:133–138

Schwartz MD (2003) Phenology: an integrative environmental science. Springer, Berlin

Schwartz MW, Thorne JH, Viers JH (2006) Biotic homogenization of the California flora in urban and urbanizing regions. Biol Conserv 127:282–291

Sellmann D (2014) Environmental education on climate change in a botanical garden: adolescents’ knowledge, attitudes and conceptions. Environ Educ Res 20:286–287

Sellmann D, Bogner FX (2013a) Climate change education: Quantitatively assessing the impact of a botanical garden as an informal learning environment. Environ Educ Res 19:415–429

Sellmann D, Bogner FX (2013b) Effects of a 1-day environmental education intervention on environmental attitudes and connectedness with nature. Eur J Psychol Educ 28:1077–1086

Sharrock SL (2011) The biodiversity benefits of botanic gardens. Trends Ecol Evol 26:433

Sharrock S (2013) Botanic gardens and food security–the results of bgci's survey. BGJournal 10:3–7

Shi G, Zhou Z, Xie Z (2011) Cupressus foliage shoots and associated seed cones from the Oligocene Ningming Formation of Guangxi South China. Rev. Palaeobot Palynol 166:325–334

Sim J (2001) Botanic garden Encyclopedia of Gardens: History and Design. Fitzroy Dearborn, Chicago, pp 172–175

Singh S, Singh J, Vig AP (2016) Earthworm as ecological engineers to change the physico-chemical properties of soil: soil vs vermicast. Ecol Eng 90:1–5

Smith P (2016) Guest essay: building a global system for the conservation of all plant diversity: a vision for botanic gardens and Botanic Gardens Conservation International. Sibbaldia 14:5–13

Smith P (2019) The challenge for botanic garden science. Plants, People, Planet 1:38–43

Sohrabi E, Maafi ZT, Panahi P, Barooti S (2015) First report of northern root-knot nematode, meloidogyne hapla, parasitic on Oaks, Quercus brantii and Quercus infectoria in Iran. J Nematol 47:86

CAS   PubMed   PubMed Central   Google Scholar  

Stacey R, Cartwright C, McEwan C (2006) Chemical characterization of ancient mesoamerican ‘copal’resins: preliminary results. Archaeometry 48:323–340

Stearn WT (1971) Sources of information about botanic gardens and herbaria. Biol J Linn Soc 3:225–233

Stevens A-D (2007) Botanical gardens and their role in ex situ conservation and research. Phyton 46:211–214

Tang ZH, Cao M, Sheng LX, Ma XF, Walsh A, Zhang SY (2008) Seed dispersal of Morus macroura (Moraceae) by two frugivorous bats in Xishuangbanna, SW China. Biotropica 40:127–131

Thiers B (2018) Index herbariorum: a global directory of public herbaria and associated staff. New York Botanical Garden's Virtual, Herbarium

Thomas P, Tripp K (1998) Ex situ conservation of conifers: a collaborative model for biodiversity preservation. Publ garden 13:5–9

Tilman D (2000) Causes, consequences and ethics of biodiversity. Nature 405:208

Tregunna E, Smith B, Berry J, Downton W (1970) Some methods for studying the photosynthetic taxonomy of the angiosperms. Can J Bot 48:1209–1214

Tunnicliffe SD (2001) Talking about plants-comments of primary school groups looking at plant exhibits in a botanical garden. J Biol Educ 36:27–34

Ul'chenko N, Glushenkova A, Belolipov I (1998) Seed lipids of four species of the family Onagraceae. Chem Nat Compd 34:650–651

Varshney V (2004) Tragic Potion: tribals lose out as herbal drug is stuck in IPR jam. Down to earth: science and environment online 12

von den Driesch M, Lobin W, Helminger T, Gröger A, Van den Wollenberg B (2005) The International Plant Exchange Network (IPEN): an instrument of botanic gardens to fulfil the ABS provisions. In: Feit U, von den Driesch M, Lobin W (eds), pp 32–43

Von Reis S, Lipp FJ (1982) New plant sources for drugs and foods from the New York Botanical Garden Herbarium. Harvard University Press, Cambridge

Waldman M, Shevah Y (2000) Biological diversity—an overview. In: Belkin S (ed) Environmental Challenges. Springer, Dordrecht, pp 299–310

Walters C, Reilley AA, Reeves PA, Baszczak J, Richards CM (2006) The utility of aged seeds in DNA banks. Seed Sci Res 16:169–178

Wania A, Kühn I, Klotz S (2006) Plant richness patterns in agricultural and urban landscapes in Central Germany—spatial gradients of species richness. Landsc Urban Plan 75:97–110

Watson GW, Heywood V, Crowley W (1993) North American botanic gardens. Hort Rev 15:1–62

Wiegand F, Kubisch A, Heyne T (2013) Out-of-school learning in the botanical garden: guided or self-determined learning at workstations? Stud Educ Eval 39:161–168

Wilcox BA (1984) In situ conservation of genetic resources: determinants of minimum area requirements National parks, conservation and development: the role of protected areas in sustaining society Smithsonian Institution Press, Washington, DC, pp. 639–647.

Williams SJ, Jones JP, Gibbons JM, Clubbe C (2015) Botanic gardens can positively influence visitors’ environmental attitudes. Biodivers Conserv 24:1609–1620

Willison J (2006) Education for sustainable development: guidelines for action in botanic gardens. Botanic Gardens Conservation International, Richmond

WRI IaU (1992) (World Research Institute, International Union for Conservation of Nature and Natural Resources, United Nations Environment Program). Global biodiversity strategy: guidelines for action to save, study and use Earth’s biotic wealth sustainable and equitably. WIR, World Research Institute, Washington DC

Wyse J, Sutherland L (2000) International agenda for botanic gardens in conservation. Botanic gardens conservation international

Xiang L et al (2016) Biocontrol potential of endophytic fungi in medicinal plants from Wuhan Botanical Garden in China. Biol Control 94:47–55. https://doi.org/10.1016/j.biocontrol.2015.12.002

Xiao HF, Feng YL, Schaefer DA, Yang XD (2014) Soil fungi rather than bacteria were modified by invasive plants, and that benefited invasive plant growth. Plant Soil 378:253–264

Yang Q, Han L, Xu Z (2005) Status of and strategy for ex-situ conservation of rare and endangered plants in Chinese botanical gardens. Rural Eco-Environ 21:62–66

Zelenika I, Moreau T, Lane O, Zhao J (2018) Sustainability education in a botanical garden promotes environmental knowledge, attitudes and willingness to act. Environ Educ Res 24:1581–1596

Zhao J, Zhang Y, Song F, Xu Z, Xiao L (2013) Phenological response of tropical plants to regional climate change in Xishuangbanna, south-western China. J Trop Ecol 29:161–172

Zheng G (1991) Physiological, biochemical and ultrastructural aspects of imbibitional chilling injury in seeds: a review of work carried out at the Beijing Botanical Garden. Seed Sci Res 1:127–134

Zohner CM, Renner SS (2014) Common garden comparison of the leaf-out phenology of woody species from different native climates, combined with herbarium records, forecasts long-term change. Ecol Lett 17:1016–1025

Zubek S, Błaszkowski J, Buchwald W (2012) Fungal root endophyte associations of medicinal plants. Nova Hedwigia 94:525–540

Zuntini AR, Fonseca LHM, Lohmann LG (2013) Primers for phylogeny reconstruction in Bignonieae (Bignoniaceae) using herbarium samples. Appl Plant Sci 1:1300018

Download references

Author information

Authors and affiliations.

Department of Architecture, Shahrekord branch, Islamic Azad University, Shahrekord, Chaharmahal Bakhtiari Province, Iran

Leila Faraji

Department of Agronomy, Faculty of Agriculture, Shahrekord University, Shahrekord, Chaharmahal Bakhtiari Province, Iran

Mojtaba Karimi

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Mojtaba Karimi .

Additional information

Communicated by Daniel Sanchez Mata.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article belongs to the Topical Collection: Ex-situ conservation.

Rights and permissions

Reprints and permissions

About this article

Faraji, L., Karimi, M. Botanical gardens as valuable resources in plant sciences. Biodivers Conserv 31 , 2905–2926 (2022). https://doi.org/10.1007/s10531-019-01926-1

Download citation

Received : 03 September 2019

Revised : 09 December 2019

Accepted : 24 December 2019

Published : 02 January 2020

Issue Date : October 2022

DOI : https://doi.org/10.1007/s10531-019-01926-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Climate change
• Research botanic designing
• Find a journal
• Publish with us
• Track your research

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Appl Plant Sci
• v.10(4); Jul-Aug 2022

Advances, applications, and prospects in aquatic botany

Julia a. cherry.

1 Department of Biological Sciences, University of Alabama, Tuscaloosa Alabama, 35487 USA

2 New College, University of Alabama, Tuscaloosa Alabama, 35487 USA

Gregory J. Pec

3 Department of Biology, University of Nebraska at Kearney, Kearney Nebraska, 68849 USA

Aquatic ecosystems, both freshwater and marine, compose a rich diversity of habitats that are increasingly recognized as vital to sustaining ecological stability and supporting human economic activity (Hofstra et al.,  2020 ). Within these critical ecosystems, macrophytes, both native and invasive, represent less than 1% of the total vascular plant diversity, but they play vital roles in aquatic ecosystem structure (i.e., habitat heterogeneity and biodiversity) and function (i.e., nutrient and water cycling) (Havel et al.,  2015 ; Geist and Hawkins,  2016 ; Hofstra et al.,  2020 ). Despite their ecological importance, aquatic plants are among the most threatened groups of species worldwide due to land‐use change, modified water regimes, and effects of climate warming (Chambers et al.,  2008 ; Hilt et al.,  2017 ). These threats can have profound effects on aquatic plant diversity, productivity, and function, and, in turn, how we manage, protect, and conserve these systems.

In recent decades, technological advances in analytical and survey methodologies have more readily been applied to aquatic plant research and provide an important means to enhance understanding of aquatic plant distribution and survivorship as well as biotic interactions with invasive species and abiotic interactions with the environment (O'Hare et al.,  2018 ). For example, cost reductions and minimization of repeat sampling of sensitive species and/or habitat have allowed for the broader use of stable isotope analysis in aquatic systems (e.g., Glibert et al.,  2019 ), while continued developments in ecological modeling and computational biology have improved our understanding of complex interactions with aquatic plant species (e.g., Wood et al.,  2014 ; Boothroyd et al.,  2015 ; Verschoren et al.,  2016 ). In this special issue of Applications in Plant Sciences , “Advances, applications, and prospects in aquatic botany,” we present four papers that explore current methods and challenges in two key areas of aquatic plant research: (i) biodiversity and conservation and (ii) aquatic invasive species management.

Our first paper in this issue (Tyrrell et al.,  2022 ) presents a novel trait‐based approach to monitoring macrophyte systems. Historically, compositional‐ and diversity‐based surveys were challenging due to the lack of taxonomic resolution and overall sampling effort. Methodological improvements have increased our ability to identify, map, and relate diversity metrics to quality indices of the aquatic environment (Visser et al.,  2015 ; Spears et al.,  2016 ). However, these metrics are often local or regional in focus due to the strong influence of the physico‐chemical environment as well as less generalizable when using simplistic taxonomic‐based approaches (McGill et al.,  2006 ; O'Hare et al.,  2018 ). Here, Tyrrell et al. ( 2022 ) explore the possibility of adapting macrophyte‐based metrics (i.e., growth‐form trophic affinity derived from species trophic affinity) from one geographic region (Europe) to evaluate trophic water conditions in another geographic region (Canada). They demonstrate that adopting aquatic plant growth form instead of taxonomic identity provides an improved relationship with actual trophic water conditions. They suggest that this mechanistic index provides an alternative bioassessment application tool and offers the ability for inter‐regional or inter‐continental comparisons.

Our second paper in this section (Lane,  2022 ) looks more closely at plant community composition in estuaries, in particular tidal freshwater marshes (TFMs) in the upper reaches of an estuary. These habitats are vital for carbon storage, nutrient cycling, and habitat for migratory salmon and seabirds. However, due to the loss of TFMs from human developments, there is an increased need to better understand and conserve these habitats (Mueller et al.,  2016 ; Chalifour et al.,  2019 ). Specifically, studies on aquatic plant recruitment from seed in TFMs represent a significant knowledge gap. Lane ( 2022 ) highlights the importance of germination ecology in TFMs and reports on how marsh organs can be used to study germination processes in tidal conditions. The author looks at the effects of artificial and natural chilling as well as the presence and/or absence of near‐neighbor aquatic transplants on germination of five TFM species based on their habitat prevalence and commercial availability. Lane ( 2022 ) illustrates an easy and cost‐effective field‐based approach that can be applied to different locations and environmental conditions, and provides insight into identifying species‐specific seed recruitment niches for restoration or conservation applications.

Aquatic invasive species management

Generally, the pace of current biological invasions exceeds that of previous events that occurred over geological time scales (Ricciardi,  2007 ). Invasive species in aquatic ecosystems have a variety of impacts on biodiversity and ecosystem function. Although some aquatic invasive species can have little to no effect on the environment (e.g., Havel et al.,  2005 ), many have significant negative effects on other species and the environment generally (e.g., Bunn et al.,  1998 ). As a result, aquatic invasive species pose challenges to the restoration or conservation of many aquatic habitats. Our first paper in this section (Van De Verg and Smith,  2022 ) outlines a novel, field‐based methodology using a common biodegradable chemical for mitigating an invasive macroalga. Here, Van De Verg and Smith ( 2022 ) administer differing concentrations of hydrogen peroxide into individual basal attachments of the invasive seaweed Avrainvillea lacerata within an impacted reef flat. They found a significant reduction in relative electron transport rate maxima (a measure of photosynthesis) following injection of hydrogen peroxide, and the authors discuss the possible utility of this method at larger scales.

Along with the impact aquatic invasive species have on species composition and abundance, they are also known to restructure food webs, particularly in freshwater ecosystems (see Havel et al.,  2015 and references therein). However, little is known about food web impacts of aquatic invasive plants on higher trophic level changes. Our remaining contribution to this issue, by Wigginton et al. ( 2022 ), highlights the use of stable isotopes and Bayesian mixed modeling to examine the role of an invasive aquatic plant on resource use of song sparrows. They demonstrate that song sparrows showed reliance on the seeds of the invasive plant Lepidium latifolium as well as seasonal differences in resource use. The use of advanced tools (i.e., stable isotope analysis and Bayesian mixed modeling) has important implications for invasive plant control and management, as attempts to control invasive plants could have negative or unintended consequences on other species that rely on them for trophic support.

Overall, these papers present work at the cutting edge of aquatic botanical research. Our understanding of aquatic plant biology and ecology has never been greater, particularly with the increased range of new techniques and approaches becoming more readily available. Historic “wait‐and‐see” approaches to biodiversity, invasive species control, and conservation are not a viable option. More rapid, cost‐effective, and robust methods and approaches—as highlighted in this special issue—are critical for the preservation of current aquatic ecosystems and the services they provide. We hope that you find these articles both informative and inspirational in this dynamic and ever‐changing field of aquatic botany.

AUTHOR CONTRIBUTIONS

G.J.P. prepared the first draft of the manuscript. J.A.C. and G.J.P. edited the subsequent drafts. Both authors approved the final version of the manuscript.

ACKNOWLEDGMENTS

The authors thank Dr. Theresa Culley (previous editor‐in‐chief of Applications in Plant Sciences ), Dr. Briana L. Gross (current editor‐in‐chief of Applications in Plant Sciences ), and Beth Parada (managing editor of Applications in Plant Sciences ) for their editorial assistance and expertise. We would also like to thank all the authors who contributed to this special issue.

Cherry, J. A. , and Pec G. J.. 2022. Advances, applications, and prospects in aquatic botany . Applications in Plant Sciences 10 ( 4 ): e11488. 10.1002/aps3.11488 [ CrossRef ] [ Google Scholar ]

This article is part of the special issue, “Advances, Applications, and Prospects in Aquatic Botany.”

• Boothroyd, R. , Hardy R., Warburton J., and Marjoribanks T.. 2015. The importance of accurately representing submerged vegetation morphology in the numerical prediction of complex river flow . Earth Surface Processes and Landforms 41 : 567–576. [ Google Scholar ]
• Bunn, S. E. , Davies P. M., Kellaway D. M., and Prosser I. P.. 1998. Influence of invasive macrophytes on channel morphology and hydrology in an open tropical lowland stream, and potential control by riparian shading . Freshwater Biology 39 : 171–178. [ Google Scholar ]
• Chalifour, L. , Scott D. C., MacDuffee M., Iacarella J. C., Martin T. G., and Baum J. K.. 2019. Habitat use by juvenile salmon, other migratory fish, and resident fish species underscores the importance of estuarine habitat mosaics . Marine Ecology Progress Series 625 : 145–162. [ Google Scholar ]
• Chambers, P. A. , Lacoul P., Murphy K. J., and Thomaz S. M.. 2008. Global diversity of aquatic macrophytes in freshwater . Hydrobiologia 595 : 9–26. [ Google Scholar ]
• Geist, J. , and Hawkins S. J.. 2016. Habitat recovery and restoration in aquatic ecosystems: Current progress and future challenges . Aquatic Conservation: Marine and Freshwater Ecosystems 26 : 942–962. [ Google Scholar ]
• Glibert, P. M. , Middelburg J. J., McClelland J. W., and Vander Zanden M. J.. 2019. Stable isotope tracers: Enriching our perspectives and questions on sources, fates, rates, and pathways of major elements in aquatic systems . Limnology and Oceanography 64 : 950–981. [ Google Scholar ]
• Havel, J. E. , Shurin J. B., and Jones J. R.. 2005. Environmental limits to a rapidly spreading exotic cladoceran . Écoscience 12 : 376–385. [ Google Scholar ]
• Havel, J. E. , Kovalenko K. E., Thomaz S. M., Amalfitano S., and Kats L. B.. 2015. Aquatic invasive species: Challenges for the future . Hydrobiologia 750 : 147–170. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hilt, S. , Brothers S., Jeppesen E., Veraart A. J., and Kosten S.. 2017. Translating regime shifts in shallow lakes into changes in ecosystem functions and services . BioScience 67 : 928–936. [ Google Scholar ]
• Hofstra, D. , Schoelynck J., Ferrell J., Coetzee J., de Winton M., Bickel T. O., Champion P., et al. 2020. On the move: New insights on the ecology and management of native and alien macrophytes . Aquatic Botany 162 : 103190. [ Google Scholar ]
• Lane, S. L. 2022. Using marsh organs to test seed recruitment in tidal freshwater marshes . Applications in Plant Sciences 10 ( 4 ): e11474. 10.1002/aps3.11474 [ CrossRef ] [ Google Scholar ]
• McGill, B. J. , Enquist B. J., Weiher E., and Westoby M.. 2006. Rebuilding community ecology from functional traits . Trends in Ecology & Evolution 21 : 178–185. [ PubMed ] [ Google Scholar ]
• Mueller, P. , Jensen K., and Megonigal J. P.. 2016. Plants mediate soil organic matter decomposition in response to sea level rise . Global Change Biology 22 : 404–414. [ PubMed ] [ Google Scholar ]
• O'Hare, M. T. , Aguiar F. C., Asaeda T., Bakker E. S., Chambers P. A., Clayton J. S., Elger A., et al. 2018. Plants in aquatic ecosystems: Current trends and future directions . Hydrobiologia 812 : 1–11. [ Google Scholar ]
• Ricciardi, A. 2007. Are modern biological invasions an unprecedented form of global change? Conservation Biology 21 : 329–336. [ PubMed ] [ Google Scholar ]
• Spears, B. M. , Mackay E. B., Yasseri S., Gunn I. D. M., Waters K. E., Andrews C., Cole S., et al. 2016. A meta‐analysis of water quality and aquatic macrophyte responses in 18 lakes treated with lanthanum modified bentonite (Phoslock®) . Water Research 97 : 111–121. [ PubMed ] [ Google Scholar ]
• Tyrrell, C. D. , Chambers P. A., and Culp J. M.. 2022. Harnessing aquatic plant growth form to apply European nutrient‐enrichment bioindicators to Canadian waters . Applications in Plant Sciences 10 ( 4 ): e11487. 10.1002/aps3.11487 [ CrossRef ] [ Google Scholar ]
• Van De Verg, S. E. , and Smith C. M.. 2022. Protocol to control the invasive alga Avrainvillea lacerata in a shallow Hawaiian reef flat . Applications in Plant Sciences 10 ( 4 ): e11489. 10.1002/aps3.11489 [ CrossRef ] [ Google Scholar ]
• Verschoren, V. , Meire D., Schoelynck J., Buis K., Bal K. D., Troch P., Meire P., and Temmerman S.. 2016. Resistance and reconfiguration of natural flexible submerged vegetation in hydrodynamic river modelling . Journal of Environmental Fluid Mechanics 16 : 245–265. [ Google Scholar ]
• Visser, F. , Buis K., Verschoren V., and Meire P.. 2015. Depth estimation of submerged aquatic vegetation in clear water streams using low‐altitude optical remote sensing . Sensors 15 : 25287–25312. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Wigginton, R. D. , Van Grootheest C., Spautz H., Grenier J. L., and Whitcraft C. R.. 2022. Stable isotope mixing models demonstrate the role of an invasive plant in wetland songbird food webs . Applications in Plant Sciences 10 ( 4 ): e11486. 10.1002/aps3.11486 [ CrossRef ] [ Google Scholar ]
• Wood, K. A. , Stillman R. A., Daunt F., and O'Hare M. T.. 2014. Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management . PLoS ONE 9 : e104034. [ PMC free article ] [ PubMed ] [ Google Scholar ]

Numbers, Facts and Trends Shaping Your World

Read our research on:

Full Topic List

Regions & Countries

Publications

• Our Methods
• Short Reads
• Tools & Resources

Read Our Research On:

Internet & Technology

6 facts about americans and tiktok.

62% of U.S. adults under 30 say they use TikTok, compared with 39% of those ages 30 to 49, 24% of those 50 to 64, and 10% of those 65 and older.

Many Americans think generative AI programs should credit the sources they rely on

Americans’ use of chatgpt is ticking up, but few trust its election information, whatsapp and facebook dominate the social media landscape in middle-income nations, sign up for our internet, science, and tech newsletter.

New findings, delivered monthly

Electric Vehicle Charging Infrastructure in the U.S.

64% of Americans live within 2 miles of a public electric vehicle charging station, and those who live closest to chargers view EVs more positively.

When Online Content Disappears

A quarter of all webpages that existed at one point between 2013 and 2023 are no longer accessible.

A quarter of U.S. teachers say AI tools do more harm than good in K-12 education

High school teachers are more likely than elementary and middle school teachers to hold negative views about AI tools in education.

Teens and Video Games Today

85% of U.S. teens say they play video games. They see both positive and negative sides, from making friends to harassment and sleep loss.

Americans’ Views of Technology Companies

Most Americans are wary of social media’s role in politics and its overall impact on the country, and these concerns are ticking up among Democrats. Still, Republicans stand out on several measures, with a majority believing major technology companies are biased toward liberals.

22% of Americans say they interact with artificial intelligence almost constantly or several times a day. 27% say they do this about once a day or several times a week.

About one-in-five U.S. adults have used ChatGPT to learn something new (17%) or for entertainment (17%).

Across eight countries surveyed in Latin America, Africa and South Asia, a median of 73% of adults say they use WhatsApp and 62% say they use Facebook.

5 facts about Americans and sports

About half of Americans (48%) say they took part in organized, competitive sports in high school or college.

REFINE YOUR SELECTION

Research teams, signature reports.

The State of Online Harassment

Roughly four-in-ten Americans have experienced online harassment, with half of this group citing politics as the reason they think they were targeted. Growing shares face more severe online abuse such as sexual harassment or stalking

Parenting Children in the Age of Screens

Two-thirds of parents in the U.S. say parenting is harder today than it was 20 years ago, with many citing technologies – like social media or smartphones – as a reason.

Dating and Relationships in the Digital Age

From distractions to jealousy, how Americans navigate cellphones and social media in their romantic relationships.

Americans and Privacy: Concerned, Confused and Feeling Lack of Control Over Their Personal Information

Majorities of U.S. adults believe their personal data is less secure now, that data collection poses more risks than benefits, and that it is not possible to go through daily life without being tracked.

Americans and ‘Cancel Culture’: Where Some See Calls for Accountability, Others See Censorship, Punishment

Social media fact sheet, digital knowledge quiz, video: how do americans define online harassment.

1615 L St. NW, Suite 800 Washington, DC 20036 USA (+1) 202-419-4300 | Main (+1) 202-857-8562 | Fax (+1) 202-419-4372 |  Media Inquiries

Research Topics

• Email Newsletters

ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

© 2024 Pew Research Center

COVID guidelines caused millions to suffer. Now Fauci admits 'there was no science behind it.'

Dr. anthony fauci told members of congress that the covid guidelines he preached in 2020 had no scientific support..

When COVID-19 hit in 2020, I jotted down a makeshift "will" for my four kids under 12. It wasn't official, just a set of instructions for my children and other immediate family members in case anything happened to me. Bank accounts, passwords, and access to other valuable information the family might need were included.

It was the beginning of the pandemic and we had no idea just how serious things would get.

As a single parent, I worried that if I suddenly caught it and died, my children would languish. The virus was rampant, and the risk of dying seemed high and very real. Fear and anxiety took hold.

COVID-19 deaths weren't exactly uncommon. The pandemic killed more than a million Americans , and there have been about 104 million confirmed cases in the United States alone. A lot of decisions were rooted in fear and brought with them life-changing consequences. Statewide lockdowns, shuttered businesses, school closings: All were based initially on the social distancing rule of the Centers for Disease Control and Prevention.

We're now getting answers to questions those decisions raised.

In his testimony to the House Oversight and Accountability Committee on Monday, Dr. Anthony Fauci, former director of the National Institute of Allergy and Infectious Diseases and former chief medical adviser to President Donald Trump, said the 6-foot social distancing rule, which the CDC originally recommended, had not been backed by a clinical trial. This is despite constant claims that COVID-19 protocols were based on science.

These disclosures are damning and maddening for all of us who had structured our lives around these rules for years. As a result, millions of people suffered needlessly.

In testimony, Fauci admits COVID rules weren't based on science

On Monday, Fauci was also asked to clarify his comments during the two-day congressional testimony he gave in January. The transcript of that testimony was recently released.

He specifically responded on Monday to questions about the 6-foot rule: “It had little to do with me since I didn’t make the recommendation and my saying ‘there was no science behind it’ meant there was no clinical trial behind that ."

In January, Fauci told staff and members of the Select Subcommittee on the Coronavirus Pandemic that "there was no science behind" the 6-foot social distancing rule that state and local governments repeated for months if not years.

What about the next pandemic: The world desperately needs a pandemic agreement. Will we come together to save lives?

“You know, I don’t recall. It sort of just appeared. I don’t recall, like, a discussion of whether it should be 5 or 6 or whatever ,” Fauci said in January's testimony.

He also admitted in the January interview that there was little science that backed requiring children to wear masks in public and at schools for almost two years.

“Do you recall reviewing any studies or data supporting masking for children?” a staffer asked Fauci .

“You know, I might have," he answered, "but I don’t recall specifically that I did. I might have.”

These revelations are infuriating. Fauci repeated CDC-based COVID-19 protocols as the mouthpiece of President Trump's administration. Desperate for guidance, states, local governments, businesses, churches and schools instituted them.

Closing schools because of COVID guidelines hurt kids

The real effect of social distancing − which Fauci basically admitted Monday and in January's testimony was just an educated guess on how to deter COVID-19 − devastated America's economy, small businesses and families. It interrupted the fabric of American life. For what?

The CDC's now-infamous three weeks to " flatten the curve " turned into months for students and families living with the consequences. Here are some.

Closing schools was devastating to kids, especially poor or otherwise disadvantaged children. Remote learning wasn't as effective as in-person learning, especially in the first year, as teachers had no time to prepare. Kids fell behind their grade levels. Pandemic closings resulted in two decades of learning loss .

Operation Warp Speed: Trump has to disavow his COVID vaccine to keep voters from RFK Jr. and his anti-vax clout

Anxiety and depression skyrocketed , especially among adolescents and teens. Kids with learning disabilities were completely left behind.

Non-urgent but still important medical diagnoses and exams were halted altogether. (This went for adults, too.) When schools did reconvene, masks were treated as sacrosanct, and kids were forced to eat lunch several feet apart.

Children learning to read and write at the beginning of the pandemic are still behind even now. Never mind that kids rarely showed any adverse effects of COVID-19, let alone died from it.

This is not a matter of hindsight being 20/20, either. People, including myself , were calling for schools to open in the fall months after the pandemic began, predicting it would continue to be harmful.

The entire medical profession, well beyond Fauci's purview, seemed to struggle to understand how to mitigate the virus while continuing to provide medical care to those in need. While most providers pushed everyone to get vaccinated, screenings and routine care were pushed off for fear of COVID-19, even though they themselves were vaccinated.

At one point during the first year of COVID-19, one of my daughters became extremely ill. I phoned our pediatrician. Even though the staff was vaccinated, they would only see newborns. Her pediatrician refused to examine my daughter in person, and we tested negative for COVID-19 three times. She lost weight and refused to eat, sleeping all day.

After about 10 days, she eventually recovered. We still have no idea what illness she had, but her pediatrician's treatment, based on COVID-19 guidelines, made no sense.

Hundreds of providers endangered patients based on ideas that had no basis in research. We're only now learning just how much delaying cancer treatments out of the fear of spreading COVID-19 will cost people.

We cannot forget what we learned during the pandemic

Schools were just one example. The economic data, representing millions of families, is no more comforting.

In the second quarter of 2020, 1.2 million jobs were destroyed. In June 2021,  6.2 million people did not work at all or worked fewer hours because their employers closed or lost business. Family-owned businesses were lost, savings wiped, all for rules that had no real scientific basis.

Elderly loved ones, the most susceptible to COVID-19, died alone in hospital beds, with no one holding their hands and whispering last prayers. If funerals were held at all, expressions of affection was banned.

On Monday, Fauci did concede that some COVID-19 preventative measures may have gone too far and led to harmful outcomes. He said it is "very, very clear" that public health officials in the future should consider "the potential collateral negative effects" of controversial ideas like requiring masks and ask "how we can do better next time."

Still, even this seems too little too late.

While COVID-19 measures were set in place immediately, as hundreds, if not thousands, were at risk of dying from the disease, it became clear within months that the disease disproportionately targeted elderly people and hardly affected kids at all.

An adaptable administration led by Fauci, the CDC and the National Institutes of Health would have observed such shifts and lifted strict lockdowns of schools and businesses. A healthy society quarantines the sick, not the young. A robust economy never shuts down its economy and hopes it will thrive.

Because we live in Texas, which remained largely open save for a couple of months, my kids and I watched as friends and family struggled through the pandemic with shuttered businesses and schools. The contrast between living in a state where responsible freedom was encouraged compared with places where local governments kept businesses and schools closed was obvious and remains cemented in my mind.

COVID-19 was four years ago now, but as time marches on, we must never forget its valuable lessons so we don't repeat those mistakes again.

Nicole Russell is an opinion columnist with USA TODAY.   She lives in Texas with her four kids.

• Search Menu
• Sign in through your institution
• Advance articles
• Darwin Reviews
• Special Issues
• Expert View
• Flowering Newsletter Reviews
• Technical Innovations
• Editor's Choice
• Virtual Issues
• Community Resources
• Reasons to submit
• Author Guidelines
• Peer Reviewers
• Submission Site
• Open Access
• About Journal of Experimental Botany
• About the Society for Experimental Biology
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Permissions
• Self-Archiving Policy
• Dispatch Dates
• Journal metrics
• Journals on Oxford Academic
• Books on Oxford Academic

Browse issues

Cover image

Volume 75, Issue 11, 7 June 2024

Extra botany, green ripe fruit in tomato: unraveling the genetic tapestry from cultivated to wild varieties.

This article comments on:

Cui L, Zheng F, Li C, Li G, Ye J, Zhang Y, Wang T, Hong Z, Ye Z, Zhang J. 2024. Defective mutations in STAY-GREEN 1 , PHYTOENE SYNTHASE 1 , and MYB12 genes lead to formation of green ripe fruit in tomato. Journal of Experimental Botany 75, 3322–3336.

• View article

Take your sunscreen: plant photoreceptor systems in Serritaenia testaceovaginata

Busch A, Gerbracht JV, Davies K, Hoecker U, Hess S. 2024. Comparative transcriptomics elucidates the cellular responses of an aeroterrestrial zygnematophyte to UV radiation. Journal of Experimental Botany 75, 3624–3642.

The symbiosome—a transient organelle in evolution

Nodulating another way: what can we learn from lateral root base nodulation in legumes.

To improve our understanding of how legumes interact with nitrogen-fixing rhizobia, we highlight the importance of studying an original lateral root base nodulation process present in certain legumes.

DARWIN REVIEW

Shaping leaves through tale homeodomain transcription factors.

TALE homeodomain transcription factors are important regulators of development. They have fundamental roles in determining leaf shape and are important in generating the rich diversity of leaf shape found in nature.

FLOWERING NEWSLETTER REVIEW

Molecular and genetic regulation of petal number variation.

Increasing the number of petals can have high economic value in ornamental flowering plants, and this review considers recent advances in understanding the underlying molecular mechanisms behind this important trait.

REVIEW PAPERS

A word of caution: t-dna-associated mutagenesis in plant reproduction research.

T-DNA lines should be handled carefully as a high incidence of additional mutagenesis in T-DNA insertion lines can be misinterpreted as the phenotype of the gene knockout/down.

Integration of nitrate and abscisic acid signaling in plants

This review summarizes the interplay between nitrate and abscisic acid and provides research perspectives for breeding high nitrogen use efficiency and stress-tolerant crop varieties.

Cytoskeleton remodeling: a central player in plant–fungus interactions

This review discusses the role of cytoskeleton dynamics during plant–fungus interactions and highlights the importance and regulation of cytoskeleton remodeling during plant defense and fungal pathogenicity.

RESEARCH PAPERS

Crop molecular genetics, zmmpk6, a mitogen-activated protein kinase, regulates maize kernel weight.

Maize mitogen-activated protein kinase 6 (ZmMPK6) regulates kernel weight. In addition, ZmMPK6 also affects starch granules, starch content, protein content, and grain-filling characteristics.

• Supplementary data

Stress response membrane protein OsSMP2 negatively regulates rice tolerance to drought

OsSMP2 is a multi-stress response gene, particularly responsive to drought, and inhibiting or knocking out OsSMP2 can increase rice root elongation and enhance rice drought stress tolerance.

Growth and Development

Defective mutations in stay-green 1 , phytoene synthase 1 , and myb12 genes lead to formation of green ripe fruit in tomato.

SlSGR1, SlPSY1 , and SlMYB12 genes are essential for tomato fruit ripening and play important roles in fruit color changes in both cultivated and wild tomatoes.

Galactinol synthase 2 influences the metabolism of chlorophyll, carotenoids, and ethylene in tomato fruits

Knockout of GolS2 in tomato shows that galactinol synthase plays an important role in chlorophyll accumulation, chloroplast development, and ethylene metabolism in ripening fruits.

Development of pollinated and unpollinated ovules in Ginkgo biloba : unravelling the role of pollen in ovule tissue maturation

Pollen arrival induces several changes in the transcriptome profiles and auxin distribution in pollinated and unpollinated ovules of Ginkgo biloba , inhibiting programmed cell death and promoting the cell cycle regulation.

A tomato B-box protein regulates plant development and fruit quality through the interaction with PIF4, HY5, and RIN transcription factors

Through the interaction with master transcription factors of light signaling and ripening, tomato SlBBX20 protein regulates vegetative and reproductive growth, contributing to determining yield and fruit quality.

The beneficial rhizobacterium Bacillus velezensis SQR9 regulates plant nitrogen uptake via an endogenous signaling pathway

Volatile compounds from the PGPR strain Bacillus velezensis SQR9 up-regulate several key plant nitrogen-uptake genes, promoting the accumulation of nitrogenous compounds via a calcium-dependent plant endogenous nitrogen uptake pathway.

Dorsoventrally asymmetric expression of miR319 / TCP generates dorsal-specific venation patterning in petunia corolla tube

miR319-targeted TCP genes repress floral venation patterning by reducing AN4 gene expression. Regulation of TCP genes by miR319 is responsible for venation patterning formation in petunia dorsal corolla tube.

Photosynthesis and Metabolism

Non-foliar photosynthesis and nitrogen assimilation influence grain yield in durum wheat regardless of water conditions.

The contribution of photosynthetic non-foliar organs to grain filling and nitrogen assimilation are key factors for durum wheat yield in Mediterranean environments.

Chemical and transcriptomic analyses of leaf trichomes from Cistus creticus subsp. creticus reveal the biosynthetic pathways of certain labdane-type diterpenoids and their acetylated forms

Trichome transcriptomic analysis was utilized to identify and characterize enzymes responsible for the biosynthesis of the labdanes labda-7,13( Ε )-dien-15-yl diphosphate, labda-7,13( Ε )-dien-15-yl acetate, and labda-13( Ε )-ene-8 α -ol-15-yl acetate in Cistus creticus subsp. creticus.

Identification and characterization of two O -methyltransferases involved in biosynthesis of methylated 2-(2-phenethyl)chromones in agarwood

Two O -methyltransferases were characterized that are involved in biosynthesis of methylated 2-(2-phenethyl)chromones responsible for the fragrance and pharmacological properties of agarwood.

Plant—Environment Interactions

Application of the thermal death time model in predicting thermal damage accumulation in plants.

This study highlights the applicability of the thermal death time model to plants, unveiling a distinct thermal tolerance landscape, extending across species and traits for assessing thermal stress impacts.

Changes in carbohydrate distribution in cotton photosynthetic organs and increase in boll weight reduce yield loss under high temperature

Cotton boll weight is increased by sucrose synthesis and transport in the subtending leaf under high temperature (HT) and increased sucrose supply from the main-stem leaf and capsule wall after recovery from HT.

Mechanism of oxalate decarboxylase Oxd_S12 from Bacillus velezensis BvZ45-1 in defence against cotton verticillium wilt

Bacillus velezensis BvZ45-1 and its antibacterial protein (oxalate decarboxylase Oxd_S12) control verticillium wilt in cotton.

Anthocyanins act as a sugar-buffer and an alternative electron sink in response to starch depletion during leaf senescence: a case study on a typical anthocyanic tree species, Acer japonicum

Anthocyanins act as a sugar-buffer and an alternative electron sink during leaf senescence after cessation of starch synthesis to prevent sugar-mediated early senescence and photoinhibition.

A pathogenesis-related protein, PRP1, negatively regulates root nodule symbiosis in Lotus japonicus

The study reveals a key link between plant immunity and symbiosis, and highlights a critical role of PRP1 as a regulator that maintains the balance between these two processes, elucidating the intricate process of symbiosis in legume roots.

Plant ammonium sensitivity is associated with external pH adaptation, repertoire of nitrogen transporters, and nitrogen requirement

This study emphasizes the importance of ecophysiological requirements and the repertoire of nitrogen transporters in understanding plant sensitivity to ammonium, and enhances our knowledge of plant nitrogen nutrition.

Drought decreases cotton fiber strength by altering sucrose flow route

Drought restricted sucrose transport from outer cottonseed coat to fiber and directed more sucrose into callose and lignin rather than cellulose in fiber.

Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert

Our analysis provides a unique set of chemical reactions enriched in at least 50% of the Atacama plant species, supporting the role of convergent strategies to face extreme environmental conditions.

Higher order polyploids exhibit enhanced desiccation tolerance in the grass Microchloa caffra

We describe two diverging ecotypes of the resurrection grass Microchloa caffra occuring along an environmental aridity gradient . Our findings provide intriguing evidence that desiccation tolerance may be mediated by ploidy changes.

Comparative transcriptomics elucidates the cellular responses of an aeroterrestrial zygnematophyte to UV radiation

UV-induced gene expression points to a phenolic origin of extracellular sunscreen pigments in zygnematophyte algae, and highlights the importance of secreted peroxidases in the closest relatives of land plants.

The radiation of nodulated Chamaecrista species from the rainforest into more diverse habitats has been accompanied by a reduction in growth form and a shift from fixation threads to symbiosomes

Chamaecrista has shrunk from trees to shrubs as it has radiated from the rainforest into drier habitats; this has been accompanied by the adoption of more intimately efficient nodulating symbioses.

Correction to: Characterization of the cryptic interspecific hybrid Lemna×mediterranea by an integrated approach provides new insights into duckweed diversity

Email alerts.

• Recommend to your Library

Affiliations

• Online ISSN 1460-2431
• Print ISSN 0022-0957
• Copyright © 2024 Society for Experimental Biology
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.