Crop Improvement with Artificial Intelligence

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Bol Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding 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. Crop Improvement with Artificial Intelligence discusses 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 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. Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding 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. Crop Improvement with Artificial Intelligence discusses 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 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.

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Bol

Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding 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. Crop Improvement with Artificial Intelligence discusses 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 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. Guide to the application of AI for crop improvement, including deployment in plant biology and crop breeding 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. Crop Improvement with Artificial Intelligence discusses 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 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.

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Pagina's: 496, Editie: Eerste editie, Hardcover, Wiley


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Merk Wiley
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  • 9781394330454
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