High-Throughput Plant Phenotyping: Methods and Protocols (Methods in Molecular Biology, 2539)

✍ Scribed by Argelia Lorence (editor), Karina Medina Jimenez (editor)

• Publisher: Humana
• Year: 2022
• Tongue: English
• Leaves: 300
• Edition: 1st ed. 2022
• Category: Library

✦ Synopsis

This volume looks at a collection of the latest techniques used to quantify the genome-by-environment-by-management (GxExM) interactions in a variety of model and plant crops. The chapters in this book are organized into five parts. Part One discusses high-throughput plant phenotyping (HTPP) protocols for plants growing under controlled conditions. Part Two present novel algorithms for extracting data from seed images, color analysis from fruits, and other digital readouts from 2D objects. Part Three covers molecular imaging protocols using PET and X-ray approaches, and Part Four presents a collection of HTPP techniques for crops growing under field conditions. The last part focuses on molecular analysis, metabolomics, network analysis, and statistical methods for the quantitative genetic analysis of HTP data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and practical, High-Throughput Plant Phenotyping: Review and Protocols is a valuable resource for both novice and expert researchers looking to learn more about this important field.

Chapter 21 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

✦ Table of Contents

Preface
Contents
Contributors
Part I: HTP Protocols for Plants Growing Under Controlled Conditions
Chapter 1: High-Throughput Screening to Examine the Dynamic of Stay-Green by an Imaging System
1 Introduction
2 Materials
3 Methods
3.1 Image Acquisition (Scanalyzer PL)
3.2 Image Analysis
3.3 Statistical Analysis
4 Notes
References
Chapter 2: An Automated High-Throughput Phenotyping System for Marchantia polymorpha
1 Introduction
2 Materials
2.1 Marchantia polymorpha Gemmae
2.2 Equipment and Materials
2.3 Culture Media
2.4 Marchantia Growth Conditions
2.5 Image Acquisition
3 Methods
3.1 Gamborg B5 Media Preparation
3.2 Transferring Gemmae to the Culture Media
3.3 Imaging Acquisition
3.4 Image Analysis
4 Notes
References
Chapter 3: A Novel High-Throughput Phenotyping Hydroponic System for Nitrogen Deficiency Studies in Arabidopsis thaliana
1 Introduction
2 Materials
2.1 Arabidopsis Seeds
2.2 Half MS Media
2.3 MS Salts
2.4 Quick Pot 15 Trays and Solid Matrix
2.5 Image Acquisition and Analysis
3 Methods
3.1 Seed Sterilization, Tissue Culture, and Vernalization
3.2 Growth Conditions in Plates
3.3 Nutrient Solution Preparation
3.4 Profile Greens Grade Mixed with Nutrient Solution
3.5 Transfer and Establishment
3.6 Phenotyping
4 Notes
References
Chapter 4: Camelina sativa High-Throughput Phenotyping Under Normal and Salt Conditions Using a Plant Phenomics Platform
1 Introduction
2 Materials
2.1 Plant Growth
2.2 Phenotyping Equipment
2.3 Image and Statistical Software
3 Methods
3.1 Initial Preparation
3.2 Growing Conditions
3.3 Salt Treatment
3.4 Image Acquisition
3.5 Image Analysis
3.5.1 vis-side-1-0´´ andvis-side-1-90´´ Views
3.5.2 vis-top-1-1000´´ View 3.5.3vis-side-1-0-dk´´ View
3.5.4 vis-top-min1-1´´ View 3.5.5 Near-Infrared and Infrared Views 3.5.6 Morpho-colorimetric Features 3.5.7 Color Classification and Clustering 3.6 Data and Statistical Analysis 4 Notes References Chapter 5: A Straightforward High-Throughput Aboveground Phenotyping Platform for Small- to Medium-Sized Plants 1 Introduction 2 Materials 2.1 Light Studio 2.2 Imaging 2.3 Specimen Stage Used in Imaging 3 Methods 3.1 Setting Up the Studio 3.2 Setting Up the Camera 3.3 Setting Up the Plant Stage 3.4 Imaging 4 Notes References Chapter 6: Wireless Fixed Camera Network for Greenhouse-Based Plant Phenotyping 1 Introduction 2 Materials 3 Methods 3.1 Hardware Setup 3.2 Software and Management 3.3 Raspberry Pi Bramble Setup 3.4 Calculation of Distance Units 3.5 3D Reconstruction and Analysis in VisualSFM and CloudCompare 4 Notes References Chapter 7: Experimental Design for Controlled Environment High-Throughput Plant Phenotyping 1 Introduction 2 Overview of Experimental Design 2.1 Commonly Used Designs 2.2 Completely Randomized Design (design.crd) 2.3 Randomized Complete Block Design (design.rcbd) 2.4 Balanced Incomplete Block Design (design.bib) 2.5 Other Incomplete Designs 3 Analysis of DoE: PBIB 4 G2F Greenhouse Study 5 Conclusions References Part II: Novel Algorithms for HTP Chapter 8: High-Throughput Extraction of Seed Traits Using Image Acquisition and Analysis 1 Introduction 2 Materials 2.1 Imaging System 2.2 Auxiliary Items 2.3 Seeds 2.4 Software 3 Methods 3.1 Image Acquisition 3.2 Image Processing 4 Notes 4.1 Imaging System 4.2 Auxiliary Items 4.3 Software 4.4 Image Acquisition 4.5 Image Processing References Chapter 9: ColourQuant: A High-Throughput Technique to Extract and Quantify Color Phenotypes from Plant Images 1 Introduction 2 Materials 3 Methods 3.1 Image Acquisition 3.2 Object Segmentation 3.3 Color Analysis 3.3.1 Mean and Variance 3.3.2 Gaussian Density Estimator 3.3.3 Circular Deformation 4 Notes 5 Conclusions References Chapter 10: Using Cameras for Precise Measurement of Two-Dimensional Plant Features: CASS 1 Introduction 1.1 Camera Calibration 1.2 Using a Camera as a Scanner 2 Materials 3 Methods 4 Notes References Part III: Molecular Plant Imaging Chapter 11: Positron Emission Tomography (PET) for Molecular Plant Imaging 1 Introduction 2 Methods 2.1 Radiotracer and PET Imaging for Plants 2.2 Challenge in Quantitative Accuracy of PET Images When Imaging Plants 2.3 Administer Radiotracers to Plants 2.4 Static and Dynamic Imaging Studies 2.5 Protocols for Administering Radiotracer to Plants for PET Imaging 2.5.1 Administering Radioactive Liquid Solution Through Roots 2.5.2 Administering Radioactive Gas to Roots 2.5.3 Administering Radioactive Gas to Canopy Whole-Plant Labeling Single-Leaf Labeling Spot Labeling 3 Conclusions References Chapter 12: Phenotyping Complex Plant Structures with a Large Format Industrial Scale High-Resolution X-Ray Tomography Instrum... 1 Introduction 2 Materials 2.1 Instrumentation 2.2 Supplies 3 Methods 3.1 Fixturing 3.2 Scan Parameters 3.3 Data Export Options 4 Notes References Part IV: HTP Protocols for Plants Growing Under Field Conditions Chapter 13: Challenges for a Massive Implementation of Phenomics in Plant Breeding Programs 1 Introduction 2 The Relevance of High-Throughput Plant Physiology 3 Phenomics: A Multidisciplinary Approach, from the Genome up to the Phenome 4 The Environment as a Modulator of the Phenotype and the Impact in Trait Modeling 5 Spectral Reflectance Data Analyses 5.1 Spectral Signature Preprocessing 5.2 Attribute Selection 6 Generation of Predictive Models Through Spectral Signatures 6.1 Individual Wavelengths 6.2 SRIs 6.3 Predictive Models 7 Other Considerations to Accelerate the Development of Phenomics in Plant Breeding 7.1 Worldwide Standardization of Measurements 7.2 Phenomics inNon-cereal´´ Species
7.3 Aerial Platforms
7.4 Software Development
7.5 Joint Trials and Interdisciplinary Teams
7.6 Global Trials Could Compensate for the Number of Seasons Needed to Generate a Reliable Model
8 Conclusions
References
Chapter 14: Designing Experiments for Physiological Phenomics
1 Introduction
1.1 Defining a Phenotype and Why We Measure
1.2 History of Image-Based Data Collection
1.3 Approaches from Earth Science, Geography, and Ecology
2 Materials
2.1 Options for Plants
2.2 Potential Facilities
2.3 Example Data Collection Platforms
2.4 Potential Sensors
2.5 Ground Reference Tools
3 Methods
3.1 Consider the Starting Materials
3.2 Consider the Location and Environment
3.3 Consideration of Non-treatment Sources of Variation in Multi-environment Yield Trials
3.4 Plan Out the Experiment in Advance with a Timeline
3.5 Phenomic Inference: A Multi-objective Framework for Evaluating Unmanned Aerial Systems (UAS) Phenotyping Capabilities
4 Notes
References
Chapter 15: Design Considerations for In-Field Measurement of Plant Architecture Traits Using Ground-Based Platforms
1 Introduction
2 Field-Based Systems: Approach and Technical Description
2.1 Mobile Platform Form Factor
2.2 Vehicle Operation and Positioning
2.2.1 Mobile Ground Robots
2.2.2 Modified Tractors
2.2.3 Push Carts and Buggies
2.2.4 Vehicle Speed
2.3 Sensors for Measuring Plant Architecture
2.3.1 Time-of-Flight (ToF) Infrared Sensors
2.3.2 Stereo Camera Systems
2.3.3 Light Detection and Ranging (LIDAR)
2.4 Sensor Control and Data Acquisition
2.4.1 On-Board Computer System and Server
2.4.2 Image Capture
2.4.3 Sensor Synchronization
2.4.4 Data Storage
3 Materials and Equipment
3.1 Phenotyping System Hardware
3.2 Field Deployment Items
4 Field Deployment Methods
4.1 Data Acquisition Setup (Pre-deployment)
4.2 Hardware Setup and Deployment
5 Broad Overview of the Post-processing Workflow
6 Summary
7 Notes
References
Chapter 16: Design and Construction of Unmanned Ground Vehicles for Sub-canopy Plant Phenotyping
1 Introduction
2 Design Considerations
2.1 Application Constraints
2.2 Frame
2.3 Drivetrain
2.4 Electrical
2.5 On-Board Computer (CPU)
2.6 Navigation Sensors
2.7 Phenotyping Sensors
2.7.1 RGB Camera
2.7.2 Spectral Camera
2.7.3 Stereo Camera
2.7.4 Time-of-Flight (ToF) Sensor
2.7.5 RGBD Camera
2.7.6 LIDAR
2.8 Communication
2.9 Software
3 Construction of a Tracked Robot Platform
3.1 Materials
3.2 Tools
3.3 Mechanical Assembly
3.4 Electrical Assembly
3.5 Software Setup
4 Notes
References
Chapter 17: Nighttime Chlorophyll Fluorescence Imaging of Dark-Adapted Plants Using a Robotic Field Phenotyping Platform
1 Introduction
2 Materials
3 Methods
3.1 High-Throughput Chlorophyll Fluorescence Imaging of Experimental Field Trials for Dark-Adapted Measurements of Fv/Fm
3.2 Evaluation of the Influence of Variable Plant Heights
4 Notes
References
Part V: Molecular, Metabolomics, Network Analysis, and Quantitative Genetic Analysis of HTP Data
Chapter 18: A Method for Rapid and Reliable Molecular Detection of Drought-Response Genes in Sorghum bicolor (L.) Moench Roots
1 Introduction
2 Materials
2.1 Sorghum Germination and Growth for Drought Assays
2.2 RNA Purification and Reverse Transcription of Sorghum Root for qRT-PCR
2.3 qRT-PCR
3 Methods
3.1 Sorghum Germination and Sowing for Drought Assays
3.2 RNA Purification of Sorghum Roots for qRT-PCR
3.3 Reverse Transcription of Sorghum Root RNA
3.4 Evaluation of Sorghum Reference Genes in Root Tissues Under Drought Stress Conditions for qRT-PCR Data Normalization
3.4.1 Housekeeping Gene Identification
3.4.2 qRT-PCR Analysis for the Selected Housekeeping Genes
3.5 Differential Gene Identification and Experimental Validation to Stablish Drought Marker Genes in Sorghum Roots
3.5.1 Gene Identification
3.5.2 Primer Design
3.5.3 qRT-PCR Primer Efficiency Standard Curve Analysis
3.5.4 qRT-PCR Analysis for the Selected Putative Drought Marker Genes in Sorghum Roots
3.6 Mathematical Method for Relative Quantification of qRT-PCR Data (2-ΔΔct)
4 Notes
References
Chapter 19: High-Throughput Profiling of Metabolic Phenotypes Using High-Resolution GC-MS
1 Introduction
2 Materials
2.1 Consumables
2.2 Reagents
2.3 Equipment
2.4 GC-HR-TOF-MS System
2.5 Software
3 Methods
3.1 Sample Preparation and Metabolite Extraction
3.2 Derivatization
3.3 GC-MS Data Acquisition
3.4 Generation of Experiment-Specific Retention Index (RI) Calibration File
3.5 Peak Annotation by MassHunter Unknowns Analysis Software
3.6 Peak Quantification Using MassHunter Quantitative Analysis Software
3.7 Initial Normalization, Filtering, and Statistical Analysis
4 Notes
References
Chapter 20: Gene Co-expression Network Analysis and Linking Modules to Phenotyping Response in Plants
1 Introduction
2 Method
2.1 Construction of Co-expression Network
2.2 Module Discovery
2.3 Link Phenotyping Data to Gene Modules
2.4 Gene Function Annotation
2.5 Visualization of Modules and Phenotyping Data
3 Materials
3.1 Databases of Gene Co-expression Networks in Plants
4 Notes
References
21: Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data
1 Introduction
2 Field-Based High-Throughput Phenotyping Using UAV
2.1 Application of HTP in Breeding Populations
2.2 Genetic Gain in HTP-Based Selection
2.3 Use of HTP for GWAS and GS
3 Integration of HTP Data into GS
3.1 Single-Trait Analysis
3.2 Multi-Trait Analysis
3.3 Genotype by Environment Interaction
4 Utilizing Image-Derived Longitudinal Traits for Genetic Studies in Plants
4.1 Single Time Point Genetic Inference
4.2 Functional Mapping
4.2.1 Single-Step Functional Mapping
4.2.2 Two-Step Functional Mapping
4.3 Insights from Animal Breeding for Genomic Prediction Using Longitudinal Traits
4.4 Multivariate Approaches for Longitudinal Genomic Prediction
4.5 Covariance Functions and Random Regression Models for Longitudinal Genetic Prediction
5 Conclusions
References
Index