Machine Learning For Better Bolls

UNIVERSITY OF GEORGIA ATHENS, GEORGIA Snider’s research lays the groundwork for improving cotton genetics, dovetailing closely with that of UGA cotton breeder Peng Chee, whose mission is to develop high-performing cotton with genetics tailored to the Southeast. While Snider investigates how specific traits influence plant performance under stress, breeders like Chee must sift through thousands of […]

The post Machine Learning For Better Bolls first appeared on Cotton Farming.

The post Machine Learning For Better Bolls appeared first on Cotton Farming.

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Approved by USDA’s World Agricultural Outlook Board Economic Research Service