Leveraging Machine Learning for Agricultural Use Cases
Date
2025-05
Authors
Zaremehrjerdi, Hossein
Major Professor
Ganapathysubramanian, Baskar
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Committee Member
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Abstract
Artificial intelligence (AI) has transformed soybean research, revolutionizing crop improvement and production strategies. This review highlights key areas where AI has been instrumental. In phenomics, AI has facilitated the collection and analysis of high-dimensional data to characterize soybean traits from below-ground to above-ground, enabling phenotype prediction and the identification of complex trait patterns. In genomics, AI has enhanced the accuracy of genomic selection and pinpointed genomic regions associated with critical traits, including resistance to biotic and abiotic stresses. Additionally, AI has been widely applied to detect and manage plant stresses using data from RGB, multispectral, and thermal imagery collected via ground-based and aerial platforms. These advancements underscore the transformative role of AI in accelerating soybean research and innovation
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creative component
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Attribution-NonCommercial-NoDerivs 3.0 United States
Copyright
2025