adamavip/nirs-protein-prediction
We present here a 1D convolutional neural network model to predict grain protein content using spectroscopic data of multiple cereals
This project helps cereal breeders quickly determine protein content in multiple grain cereals. By using near-infrared spectroscopy (NIRS) data from grain samples, it predicts protein content without time-consuming wet lab analysis. The output is a rapid, reliable estimate of protein levels, assisting in plant breeding decisions.
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Use this if you are a cereal breeder or agricultural researcher who needs a fast and accurate way to estimate protein content in large batches of grain samples using NIRS data.
Not ideal if you lack access to NIRS scanning equipment or require detailed chemical compositional analysis beyond protein content.
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Apr 07, 2022
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