MODELING OF TIME-VARIANT THRESHABILITY DUE TO INTERACTIONS BETWEEN A CROP IN A FIELD AND ATMOSPHERIC AND SOIL CONDITIONS FOR PREDICTION OF DAILY OPPORTUNITY WINDOWS FOR HARVEST OPERATIONS USING FIELD-LEVEL DIAGNOSIS AND PREDICTION OF WEATHER CONDITIONS AND OBSERVATIONS AND RECENT INPUT OF HARVEST CONDITION STATES

摘要

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.

主权项

1. A method, comprising:
ingesting, as input data, weather information, crop-specific information and harvest data for a crop to be harvested, the weather information including recent and current field-level weather data and extended-range weather forecast data, the crop-specific information including at least one of crop type data and crop state data representing at least a standing or windrowed status of the crop, and the harvest data including data representing a threshability of the crop measured by agricultural equipment associated with harvesting operations of the crop; modeling the input data in a plurality of data processing modules within a computing environment in which the plurality of data processing modules are executed in conjunction with at least one processor, the data processing modules configured to project time-varying threshability of the crop to be harvested in one or more forthcoming temporal harvest windows, by
1) predicting expected weather conditions relative to crop wetness over at least one time period relative to the one or more forthcoming temporal harvest windows,2) applying the expected weather conditions, the crop-specific information, and the harvest data to an agricultural model that applies one or more physical and empirical characteristics of the crop to be harvested to forecast changes in one or more threshability characteristics of the crop over the one or more forthcoming temporal harvest windows, and generating, as output data, a harvest condition profile representing the forecast of the changes in one or more threshability characteristics of the crop on both a current day and future days within the at least one time period relative to the one or more forthcoming temporal harvest windows, and generating one or more advisories based on the harvest condition profile to at least one of a user performing harvest operations, a user managing harvest operations, and agricultural equipment performing harvest operations.