Article
Computer vision and machine learning for robust phenotyping in genome-wide studies.
Scientific reports - 8 Mar 2017
Zhang Jiaoping, Naik Hsiang Sing, Assefa Teshale, Sarkar Soumik, Reddy R V Chowda, Singh Arti, Ganapathysubramanian Baskar, Singh Asheesh K
Abstract excerpt
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic studies of abiotic stress iron deficiency chlorosis (IDC) of soybean is reported. IDC classification and severity for an association panel of 461 diverse...
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