Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning

24 Jun 2020Johnathon ShookTryambak GangopadhyayLinjiang WuBaskar GanapathysubramanianSoumik SarkarAsheesh K. Singh

Accurate prediction of crop yield supported by scientific and domain-relevant insights, can help improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop production including erratic rainfall and temperature variations. We used historical performance records from Uniform Soybean Tests (UST) in North America spanning 13 years of data to build a Long Short Term Memory - Recurrent Neural Network based model to dissect and predict genotype response in multiple-environments by leveraging pedigree relatedness measures along with weekly weather parameters... (read more)

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