Crop Improvement with Artificial Intelligence
Methods and Applications
Seiten
2026
John Wiley & Sons Inc (Verlag)
9781394330454 (ISBN)
John Wiley & Sons Inc (Verlag)
9781394330454 (ISBN)
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Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding
Advancing Crop Improvement with Artificial intelligence provides a comprehensive overview of the integration of AI into crop development and farm management, highlighting the latest advancements and applications in the field. The book offers an exhaustive review of recent progress and implementations of AI in agriculture, covering a wide range of topics crucial for understanding the innovative potential of AI in crop enhancement.
Beginning with an exploration of the documented factors and potential for innovation in agriculture, the book introduces readers to the fundamental concepts of AI and its transformative impact on advanced farming methods. It delves into the various applications of AI in plant biology and breeding, from data collection and pre-processing to predictive analytics for crop yield and disease resistance.
The book also addresses ethical considerations and challenges in AI-enabled crop improvement and delivers insights into the prospects of employing AI for crop enhancement, underscoring the significance of genetic diversity, resource optimization, and ethical considerations.
Advancing Crop Improvement with Artificial intelligence discusses sample topics including:
Utilization of LLMs to improve analysis of agricultural data by interpreting intricate datasets and providing insights to enhance decision-making
Generative AI's role in developing innovative solutions and predictive models for better crop management, pest control, and resource distribution
Current challenges such as data constraints, economic feasibility, and untested technologies
Integration of multi-omics data with the latest applications and technologies, including functional genomics, phenotyping, high-throughput imaging, and genomic prediction in plants, to analyze complex traits and advance plant transcriptomics
Advancing Crop Improvement with Artificial intelligence is an essential resource for scholars, researchers, academics, agronomists, policymakers, and all other readers interested in capitalizing AI to address the hurdles of worldwide food security and encourage sustainable agricultural implementation.
Advancing Crop Improvement with Artificial intelligence provides a comprehensive overview of the integration of AI into crop development and farm management, highlighting the latest advancements and applications in the field. The book offers an exhaustive review of recent progress and implementations of AI in agriculture, covering a wide range of topics crucial for understanding the innovative potential of AI in crop enhancement.
Beginning with an exploration of the documented factors and potential for innovation in agriculture, the book introduces readers to the fundamental concepts of AI and its transformative impact on advanced farming methods. It delves into the various applications of AI in plant biology and breeding, from data collection and pre-processing to predictive analytics for crop yield and disease resistance.
The book also addresses ethical considerations and challenges in AI-enabled crop improvement and delivers insights into the prospects of employing AI for crop enhancement, underscoring the significance of genetic diversity, resource optimization, and ethical considerations.
Advancing Crop Improvement with Artificial intelligence discusses sample topics including:
Utilization of LLMs to improve analysis of agricultural data by interpreting intricate datasets and providing insights to enhance decision-making
Generative AI's role in developing innovative solutions and predictive models for better crop management, pest control, and resource distribution
Current challenges such as data constraints, economic feasibility, and untested technologies
Integration of multi-omics data with the latest applications and technologies, including functional genomics, phenotyping, high-throughput imaging, and genomic prediction in plants, to analyze complex traits and advance plant transcriptomics
Advancing Crop Improvement with Artificial intelligence is an essential resource for scholars, researchers, academics, agronomists, policymakers, and all other readers interested in capitalizing AI to address the hurdles of worldwide food security and encourage sustainable agricultural implementation.
Sadhana Singh, Assistant Professor (Biochemistry), School of Sciences, U.P. Rajarshi Tandon Open University, Prayagraj, India. Sadhana's research interests include-plant stress tolerance (model and non-model), molecular regulations controlling plant abiotic stresses, and the role of NAC genes towards abiotic stress tolerance. Santosh Kumar Upadhyay, Assistant Professor, Department of Botany, Panjab University, Chandigarh, India. He has been working in the field of plant biotechnology for more than 16 years.
| Erscheint lt. Verlag | 16.4.2026 |
|---|---|
| Verlagsort | New York |
| Sprache | englisch |
| Themenwelt | Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei |
| ISBN-13 | 9781394330454 / 9781394330454 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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