Data analytics and chemometrics, including machine learning, have been used in various areas of agricultural research including the biomass quality assessment, adulteration detection, and remote sensing.  This presentation will provide an overview of how data analytics is utilize for data interpretation and to develop methods in those and additional agricultural research areas.  Examples of data analytics will include PLS and ANN calibration/prediction, PARAFAC, and 2D correlation spectroscopy.  Particular emphasis will be given to illustrate how aromatic and redox-active end-products and building products are used to develop (1) on-farm chemical tools to decipher the genotypic and environmental controls on the quality of sugar crops, (2) industrial methods for biorefineries, and (3) to elucidate the environmental fate cycles of biofertilizer and other biobased products.

Rapid data analytics in agro-environmental research: Fertilizer development, fate monitoring, to breeding

ACS Spring Meeting 2021

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