From Markers to Machine Learning in Predictive Plant Breeding
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From Markers to Machine Learning in Predictive Plant Breeding
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In this episode of the Computomics podcast, Dr. Rex Bernardo discusses the evolution of predictive plant breeding, from early molecular markers to today’s machine learning and AI approaches. He explains how these tools can support not only trait prediction, but also more complex breeding decisions, such as whether a line is likely to be selected or become a successful variety. The conversation also highlights community-focused work on leafy African vegetables in Minnesota and reflects on how plant breeding education must evolve to prepare future breeders for a more interdisciplinary, data-driven field.
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