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MODELING OF CROP GROWTH FOR DESIRED MOISTURE CONTENT OF BOVINE FEEDSTUFF AND DETERMINATION OF HARVEST WINDOWS FOR HIGH-MOISTURE CORN USING FIELD-LEVEL DIAGNOSIS AND FORECASTING OF WEATHER CONDITIONS AND OBSERVATIONS AND USER INPUT OF HARVEST CONDITION STATES
MODELING OF CROP GROWTH FOR DESIRED MOISTURE CONTENT OF BOVINE FEEDSTUFF AND DETERMINATION OF HARVEST WINDOWS FOR HIGH-MOISTURE CORN USING FIELD-LEVEL DIAGNOSIS AND FORECASTING OF WEATHER CONDITIONS AND OBSERVATIONS AND USER INPUT OF HARVEST CONDITION STATES
A modeling framework for evaluating the impact of weather conditions on farming and harvest operations applies real-time, field-level weather data and forecasts of meteorological and climatological conditions together with user-provided and/or observed feedback of a present state of a harvest-related condition to agronomic models and to generate a plurality of harvest advisory outputs for precision agriculture. A harvest advisory model simulates and predicts the impacts of this weather information and user-provided and/or observed feedback in one or more physical, empirical, or artificial intelligence models of precision agriculture to analyze crops, plants, soils, and resulting agricultural commodities, and provides harvest advisory outputs to a diagnostic support tool for users to enhance farming and harvest decision-making, whether by providing pre-, post-, or in situ-harvest operations and crop analyses.
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