Intelligent Image Analysis for Plant Phenotyping

✍ Scribed by Ashok Samal (editor), Sruti Das Choudhury (editor)

• Publisher: CRC Press
• Year: 2020
• Tongue: English
• Leaves: 347
• Edition: 1
• Category: Library

✦ Synopsis

Domesticated crops are the result of artificial selection for particular phenotypes or, in some cases, natural selection for an adaptive trait. Plant traits can be identified through image-based plant phenotyping, a process that was, until recently, strenous and time-consuming. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques, using computer vision and imaging technologies. These methodologies provide an automated, non-invasive, and scalable mechanism by which to define and collect plant phenotypes. Beautifully illustrated, with numerous color images, the book focuses on phenotypes measured from individual plants under controlled experimental conditions, which are widely available in high-throughput systems. A practical resource for students, researchers, and practitioners, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences.

✦ Table of Contents

Dedication
Contents
Preface
Acknowledgments
Editors
Contributors
Part I: Basics
1 Image-Based Plant Phenotyping: Opportunities and Challenges • Ashok Samal, Sruti Das Choudhury, and Tala Awada
2 Multisensor Phenotyping for Crop Physiology • Stefan Paulus, Gustavo Bonaventure, and Marcus Jansen
3 Image Processing Techniques for Plant Phenotyping • Bashyam Srinidhi and Sanjiv Bhatia
Part II: Techniques
4 Segmentation Techniques and Challenges in Plant Phenotyping • Sruti Das Choudhury
5 Structural High-Throughput Plant Phenotyping Based on Image Sequence Analysis • Sruti Das Choudhury and Ashok Samal
6 Geometry Reconstruction of Plants • Ayan Chaudhury and Christophe Godin
7 Image-Based Structural Phenotyping of Stems and Branches • Fumio Okura, Takahiro Isokane, Ayaka Ide, Yasuyuki Matsushita, and Yasushi Yagi
8 Time Series- and Eigenvalue-Based Analysis of Plant Phenotypes • Sruti Das Choudhury, Saptarsi Goswami, and Amlan Chakrabarti
9 Data-Driven Techniques for Plant Phenotyping Using Hyperspectral Imagery • Suraj Gampa and Rubi Quiñones
10 Machine Learning and Statistical Approaches for Plant Phenotyping • Zheng Xu and Cong Wu
11 A Brief Introduction to Machine Learning and Deep Learning for Computer Vision • Eleanor Quint and Stephen Scott
Part III: Practice
12 Chlorophyll a Fluorescence Analyses to Investigate the Impacts of Genotype, Species, and Stress on Photosynthetic Efficiency and Plant Productivity • Carmela Rosaria Guadagno and Brent E. Ewers
13 Predicting Yield by Modeling Interactions between Canopy Coverage Image Data, Genotypic and Environmental Information for Soybeans • Diego Jarquin, Reka Howard, Alencar Xavier, andSruti Das Choudhury
14 Field Phenotyping for Salt Tolerance and Imaging Techniques for Crop Stress Biology • Shayani Das Laha, Amlan Jyoti Naskar, Tanmay Sarkar, Suman Guha, Hossain Ali Mondal, and Malay Das
15 The Adoption of Automated Phenotyping by Plant Breeders • Lana Awada, Peter W. B. Phillips, and Stuart J. Smyth
Index