Plant Genomic Prediction AI – Enhanced Models for Plant Genomics and Crop Improvement | 8.93 MB
Title: Plant Genomic Prediction
Author: Jen-Tsung Chen;
Category: Nonfiction, Science & Nature, Science, Biological Sciences, Biotechnology, Technology, Agriculture & Animal Husbandry
Language: English | 368 Pages | ISBN: 1836991304
Description:
Predicting plant gene functions using AI-enhanced genomic prediction models is becoming a key component in crop breeding. This technology will significantly advance the development of new crops resistant to a wide range of stresses. This book describes the application of AI-enhanced genomic prediction models and their integration with high-throughput technology, such as smart phenotyping, multiple omics data from metabolomics, proteomics, and transcriptomics, to accelerate crop improvement. Written by a team of experts in this field, this book describes new methods for the production of climate change-ready, disease-resistant, stress-resilient crops by advancing the next generation of plant breeding tools. It is an ideal reference for readers working in all aspects of plant sciences and agricultural biotechnology, particularly plant stress physiology and crop breeding. The book: Describes AI-empowered models for accelerating plant genomic selection Comprehensively reviews omics-assisted genomic prediction for crop breeding Includes ways to develop climate change-ready and disease-resistant future crops
Predicting plant gene functions using AI-enhanced genomic prediction models is becoming a key component in crop breeding. This technology will significantly advance the development of new crops resistant to a wide range of stresses. This book describes the application of AI-enhanced genomic prediction models and their integration with high-throughput technology, such as smart phenotyping, multiple omics data from metabolomics, proteomics, and transcriptomics, to accelerate crop improvement. Written by a team of experts in this field, this book describes new methods for the production of climate change-ready, disease-resistant, stress-resilient crops by advancing the next generation of plant breeding tools. It is an ideal reference for readers working in all aspects of plant sciences and agricultural biotechnology, particularly plant stress physiology and crop breeding. The book: Describes AI-empowered models for accelerating plant genomic selection Comprehensively reviews omics-assisted genomic prediction for crop breeding Includes ways to develop climate change-ready and disease-resistant future crops
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