Emerging Omics Technologies for Sustainable Agriculture provides a comprehensive overview of the transformative potential of advanced tools such as AI, genomics and proteomics to ensure future agricultural production.
The integration of genomics, transcriptomics, proteomics, and metabolomics has advanced the understanding of plant and microbial systems and the application of this knowledge has enabled precision farming, optimizing crop yield and minimizing environmental impact. There are unprecedented opportunities to enhance crop yields, improve pest and disease management, to optimize resource utilization and to mitigate environmental impacts. Through the use of advanced data analytics, machine learning, and predictive modeling, researchers can decipher complex biological processes and develop innovative solutions for agricultural challenges.
Emerging Omics Technologies for Sustainable Agriculture explores the advancements in AI-driven omics technologies, such as genome editing, transcriptomics, and phenomics, and their applications in crop improvement, soil health monitoring, and precision agriculture.
1. Chapter 1. Introduction to emerging omics technologies and sustainable agricultural practices - p. 1 2. Chapter 2. Introduction to technological advancements in smart agriculture - p. 15 3. Chapter 3. Comparative genomics: insights into enhancing disease resistance in crops - p. 41 4. Chapter 4. Advancements in DNA storage: innovations, challenges, and the road ahead - p. 79 5. Chapter 5. Precision crop breeding: integrating pan-genomics, CRISPR, and machine learning - p. 105 6. Chapter 6. Microbiome dynamics in agricultural systems: from root–microbe interactions to sustainable practices - p. 129 7. Chapter 7. Microbial threats in agricultural crops and their management through artificial intelligence approaches - p. 151 8. Chapter 8. Agriculture meets artificial intelligence: revolutionizing farming practices through technology - p. 177 9. Chapter 9. Machine learning models for crop yield prediction - p. 201 10. Chapter 10. Metagenomics and the soil microbiome: shaping the future of sustainable agriculture - p. 227 11. Chapter 11. Introduction to technological advancements in smart farming practices - p. 257 12. Chapter 12. Climatic resilient agriculture: harnessing cutting-edge technologies for innovation - p. 281 13. Chapter 13. Introduction, challenges, and application of artificial intelligence and Internet of Things for sustainable agriculture - p. 315 14. Chapter 14. Role of cryopreservation in plant virus eradication in horticulture - p. 339 15. Chapter 15. Emerging omics technologies to combat herbicide-resistant weeds - p. 369 16. Chapter 16. Application of machine learning in predicting biochar performance for soil–metal interactions - p. 387 17. Chapter 17. Machine learning innovations for accurate crop yield forecasting - p. 401 18. Chapter 18. Integrative proteomics, microbiome-based and molecular approaches with implications in plant health management - p. 425 19. Chapter 19. Impact of climate change on plant–microbe interactions in agroecosystems - p. 449 20. Index - p. 477
Emerging Omics Technologies for Sustainable Agriculture provides a comprehensive overview of the transformative potential of advanced tools such as AI, genomics and proteomics to ensure future agricultural production.
The integration of genomics, transcriptomics, proteomics, and metabolomics has advanced the understanding of plant and microbial systems and the application of this knowledge has enabled precision farming, optimizing crop yield and minimizing environmental impact. There are unprecedented opportunities to enhance crop yields, improve pest and disease management, to optimize resource utilization and to mitigate environmental impacts. Through the use of advanced data analytics, machine learning, and predictive modeling, researchers can decipher complex biological processes and develop innovative solutions for agricultural challenges.
Emerging Omics Technologies for Sustainable Agriculture explores the advancements in AI-driven omics technologies, such as genome editing, transcriptomics, and phenomics, and their applications in crop improvement, soil health monitoring, and precision agriculture.
1. Chapter 1. Introduction to emerging omics technologies and sustainable agricultural practices - p. 1 2. Chapter 2. Introduction to technological advancements in smart agriculture - p. 15 3. Chapter 3. Comparative genomics: insights into enhancing disease resistance in crops - p. 41 4. Chapter 4. Advancements in DNA storage: innovations, challenges, and the road ahead - p. 79 5. Chapter 5. Precision crop breeding: integrating pan-genomics, CRISPR, and machine learning - p. 105 6. Chapter 6. Microbiome dynamics in agricultural systems: from root–microbe interactions to sustainable practices - p. 129 7. Chapter 7. Microbial threats in agricultural crops and their management through artificial intelligence approaches - p. 151 8. Chapter 8. Agriculture meets artificial intelligence: revolutionizing farming practices through technology - p. 177 9. Chapter 9. Machine learning models for crop yield prediction - p. 201 10. Chapter 10. Metagenomics and the soil microbiome: shaping the future of sustainable agriculture - p. 227 11. Chapter 11. Introduction to technological advancements in smart farming practices - p. 257 12. Chapter 12. Climatic resilient agriculture: harnessing cutting-edge technologies for innovation - p. 281 13. Chapter 13. Introduction, challenges, and application of artificial intelligence and Internet of Things for sustainable agriculture - p. 315 14. Chapter 14. Role of cryopreservation in plant virus eradication in horticulture - p. 339 15. Chapter 15. Emerging omics technologies to combat herbicide-resistant weeds - p. 369 16. Chapter 16. Application of machine learning in predicting biochar performance for soil–metal interactions - p. 387 17. Chapter 17. Machine learning innovations for accurate crop yield forecasting - p. 401 18. Chapter 18. Integrative proteomics, microbiome-based and molecular approaches with implications in plant health management - p. 425 19. Chapter 19. Impact of climate change on plant–microbe interactions in agroecosystems - p. 449 20. Index - p. 477
