Advances in Plant Phenotyping for More Sustainable Crop Production

This book provides an in-depth analysis of plant traits and the critical needs for high throughput phenotyping, making it a valuable resource for beginners and experts in the field. It is particularly helpful for readers with no breeding background to explore the origins, concepts, and insights of plant phenotyping systematically.

Format: Hardback
Length: 404 pages
Publication date: 28 June 2022
Publisher: Burleigh Dodds Science Publishing Limited

This book provides an in-depth analysis of plant traits and the critical needs for high throughput phenotyping. In addition, the book is the result of collaborative contributions of broad participation from well-recognized international institutions in plant phenotyping. In summary, this book is a great reference for beginner and expert readers to learn and expand their knowledge about plant phenotyping technologies. It is particularly helpful to readers with no breeding background to explore in-depth information about the origins, concepts, and insights of plant phenotyping in a systematic way.

Plant phenotyping is rapidly developing technology that involves the quantitative analysis of structural and functional plant traits. It is widely recognised that phenotyping needs to match similar advances in genetics if it is to not create a bottleneck in plant breeding.

Advances in plant phenotyping for more sustainable crop production reviews the wealth of research on advances in plant phenotyping to meet this challenge, including new technologies such as optical and thermographic sensors, as well as alternative carrier systems such as field robots and unmanned aerial vehicles (UAVs). The book details the use of plant phenotyping to analyse traits such as crop root functionality, yield performance and disease resistance.

Edited by a world-renowned researcher in plant science, Advances in plant phenotyping for more sustainable crop production will be a standard reference for university and other researchers in plant science, as well as those in computing and engineering science with a research focus on computer vision, data mining, and machine learning.

Weight: 710g
Dimension: 229 x 152 x 24 (mm)
ISBN-13: 9781786768568