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Over 3200 discrete soybean samples were obtained from production locations around the United States during the years 2012-2016. Ground samples were scanned on near infrared spectrometers (NIRS) and analyzed by HPLC for total isoflavone and total saponin composition, as well as total carbohydrate composition. Multiple Linear Regression (MLR) analysis of preprocessed spectral data was used to develop optimized models to predict isoflavone content. The selection of a suitable calibration model was based on a high regression coefficient (R2),
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