{"product_id":"advances-in-plant-phenotyping-for-more-sustainable-crop-production-9781786768568","title":"Advances in Plant Phenotyping for More","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e“Compared to other books that primarily focus on plant phenotyping applications, 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.”\u003c\/b\u003e\u003ci\u003e (Dr Jianfeng Zhou, University of Missouri, Columbia)\u003c\/i\u003e\u003cbr\u003e\u003cbr\u003e\u003cstrong\u003ePlant 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.\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003e Advances in plant phenotyping for more sustainable crop production\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eEdited by a world-renowned researcher in plant science, \u003cem\u003eAdvances in plant phenotyping for more sustainable crop production\u003c\/em\u003e 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 image-based plant phenotyping. The book will also be a key resource for plant breeders, government and private agencies involved in advocating for a more sustainable agriculture, agricultural engineers, as well as suppliers of agricultural technology.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e“Compared to other books that primarily focus on plant phenotyping applications, 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. Chapter authors consist of experts in the area with good records in research publications and outstanding achievements. The book provides in-depth discussion and insights on plant phenotyping technologies and their applications while also giving a broad overview of the challenges and perspectives in research and applications. 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.”\u003c\/b\u003e \u003ci\u003e(Dr Jianfeng Zhou, University of Missouri, Columbia)\u003c\/i\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003ePart 1 The development of phenotyping as a research field\u003c\/strong\u003e\u003cbr\u003e 1.Origins and drivers of crop phenotyping: \u003cem\u003eRoland Pieruschka and Ulrich Schurr, Institute for Bio- and Geosciences (IBG), IBG-2: Plant Sciences, Forschungszentrum Jülich, Germany\u003c\/em\u003e; \u003cbr\u003e 2.The evolution of trait selection in breeding: from seeing to remote sensing: \u003cem\u003eMatthew Reynolds, Francisco Pinto, Liana Acevedo, Francisco J. Pinera-Chavez, and Carolina Rivera-Amado, International Maize and Wheat Improvement Center (CIMMYT), Mexico\u003c\/em\u003e;\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003ePart 2 Sensor types\u003c\/strong\u003e\u003cbr\u003e 3.Advances in optical analysis for crop phenotyping: \u003cem\u003eJian Jin and Tanzeel U. Rehman, Purdue University, USA; and Qin Zhang, Washington State University, USA\u003c\/em\u003e; \u003cbr\u003e 4.Advances in the use of thermography in crop phenotyping: \u003cem\u003eDavid M. Deery, CSIRO Agriculture and Food, Australia\u003c\/em\u003e; \u003cbr\u003e 5.Advances in the use of X-ray computed tomography in crop phenotyping: \u003cem\u003eStefan Gerth, Norman Uhlmann and Michael Salamon, Fraunhofer EZRT, Germany\u003c\/em\u003e;\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003ePart 3 Carrier\/delivery systems\u003c\/strong\u003e \u003cbr\u003e 6.Field robots for plant phenotyping: \u003cem\u003eRick van de Zedde, Wageningen University and Research, The Netherlands; and Lili Yao, Visiting Researcher – Wageningen University and Research, The Netherlands\u003c\/em\u003e; \u003cbr\u003e 7.Advances in the use of aerial systems\/UAVs for crop phenotyping as examples for lean, low-cost, high-throughput field crop phenotyping systems: \u003cem\u003eHelge Aasen, Institute of Agricultural Sciences, ETH Zurich and Remote Sensing Team, Division of Agroecology and Environment, Agroscope, Switzerland; and Lukas Roth, Institute of Agricultural Sciences, ETH Zurich, Switzerland\u003c\/em\u003e;\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003ePart 4 Data analysis\u003c\/strong\u003e\u003cbr\u003e 8.Meeting computer vision and machine learning challenges in crop phenotyping: \u003cem\u003eHanno Scharr, Institute of Bio- and Geosciences: Plant Sciences (IBG-2) and Institute for Advanced Simulation: Data Analytics and Machine Learning (IAS-8), Forschungszentrum Jülich, Germany; and Sotirios A. Tsaftaris, The University of Edinburgh and Alan Turing Institute, UK\u003c\/em\u003e; \u003cbr\u003e 9.Digital phenotyping and genotype-to-phenotype (G2P) models to predict complex traits in cereal crops: \u003cem\u003eNicolas Virlet, Rothamsted Research, UK; Danilo H. Lyra, Biometrics and Breeding Research, BASF, Belgium; and Malcolm J. Hawkesford, Rothamsted Research, UK\u003c\/em\u003e; \u003cbr\u003e 10.The role of crop growth models in crop improvement: integrating phenomics, envirotyping and genomic prediction: \u003cem\u003eJana Kholová, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), India; Amir Hajjarpoor, UMR DIADE, Université de Montpellier, Institut de Recherche pour le Développement (IRD), France; Vincent Garin, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Mali; William Nelson, Gottingen University, Germany; Madina Diacoumba, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Mali; Carlos D. Messina, Pioneer Hi-Bred International, USA; Graeme L. Hammer, Queensland Alliance for Agriculture and Food Innovation - The University of Queensland, Australia; Yunbi Xu, Chinese Academy of Agricultural Sciences, China and International Maize and Wheat Improvement Center (CIMMYT), Mexico; Milan O. Urban, International Center for Tropical Agriculture (CIAT), Colombia; and Jan Jarolímek, Czech University of Life Sciences (CZU), Czech Republic\u003c\/em\u003e;\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003ePart 5 Case studies\u003c\/strong\u003e\u003cbr\u003e 11.Using phenotyping techniques to analyse crop functionality and photosynthesis: \u003cem\u003eEva Rosenqvist, University of Copenhagen, Denmark\u003c\/em\u003e; \u003cbr\u003e 12.Using phenotyping techniques to predict and model grain yield: translating phenotyping into genetic gain: \u003cem\u003eThomas Vatter and José L. Araus, University of Barcelona and AGROTECNIO (Center for Research in Agrotechnology), Spain\u003c\/em\u003e; \u003cbr\u003e 13.Automated assessment of plant diseases and traits by sensors: how can digital technologies support smart farming and plant breeding?: \u003cem\u003eAnne-Katrin Mahlein, Institute of Sugar Beet Research, Germany; Jan Behmann, Bayer Crop Science, Germany; David Bohnenkamp, BASF Digital Farming GmbH, Germany; René H. J. Heim, UAV Research Centre (URC), Ghent University, Belgium; and Sebastian Streit and Stefan Paulus, Institute of Sugar Beet Research, Germany\u003c\/em\u003e;\u003c\/p\u003e","brand":"Burleigh Dodds Science Publishing Limited","offers":[{"title":"Default Title","offer_id":51042488615255,"sku":"9781786768568","price":150.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781786768568.jpg?v=1750954353","url":"https:\/\/bookcurl.com\/products\/advances-in-plant-phenotyping-for-more-sustainable-crop-production-9781786768568","provider":"Book Curl","version":"1.0","type":"link"}