Plant breeding and cultivar development
著者
書誌事項
Plant breeding and cultivar development
Academic Press, an imprint of Elsevier, c2021
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注記
Includes bibliographical references (p. 595-614) and index
内容説明・目次
内容説明
Plant Breeding and Cultivar Development features an optimal balance between classical and modern tools and techniques related to plant breeding. Written for a global audience and based on the extensive international experience of the authors, the book features pertinent examples from major and minor world crops. Advanced data analytics (machine learning), phenomics and artificial intelligence are explored in the book's 28 chapters that cover classical and modern plant breeding. By presenting these advancements in specific detail, private and public sector breeding programs will learn about new, effective and efficient implementation.
The insights are clear enough that non-plant breeding majoring students will find it useful to learn about the subject, while advanced level students and researchers and practitioners will find practical examples that help them implement their work.
目次
1. Plant Breeding - Past, Present, and Future Perspectives
2. Mode of Reproduction in Crop Plants
3. Genetics in Relation to Plant Breeding
4. Primer on Population and Quantitative Genetics
5. Plant Genetic Resources
6. Wilde Hybridization
7. Haploids and Polyploidy
8. Hybridization and Selection in Self-Pollinated Crops
9. Mass and Pure Line Selection
10. Bulk Method
11. Pedigree Method
12. Single Seed Descent Method
13. Backcross Method
14. Mutation Breeding
15. Inbreeding Depression and Heterosis
16. Population Improvement
17. Recurrent Selection in Self-pollinated Crops
18. Synthetic and Composite Varieties
19. Hybrid Varieties
20. Breeding Methods Used in Asexual Crops
21. Breeding for Resistance to Abiotic Stresses
22. Breeding for Resistance to Biotic Stresses
23. Intellectual Property Rights and Protection
24. Participatory Plant Breeding
25. Breeding of Crop Ideotypes
26. Field Plot Designs in Plant Breeding
27. Molecular Tools in Crop Improvement and Cultivar Development
28. Phenomics and Machine Learning in Crop Improvement
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