This $498,945 federal Project Grant award from the U.S. Department of Agriculture's Agricultural Marketing Service, under the Acer Access and Development Program (CFDA 10.174), aims to develop protocols for mapping maple sap quantity and quality from leaf spectra. The project will follow the carbon dynamics of 50 maple trees at Michigan State University's Forestry Innovation Center to determine the factors contributing to sap production. Leaf spectroscopy will be used to predict leaf chemistry and enable non-destructive sampling. The team will then train machine learning models to predict sap quantity and quality from foliar spectra and apply the predictive models to spectral images collected by an unmanned aerial system to map production potential across the sugar bush. The project includes sub-awards to Michigan State University and Minnesota State University Mankato to support the early prediction of maple syrup quality using carbon dynamics spectroscopy. The project is expected to run from September 30, 2024, to September 29, 2027.
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