USING MACHINE LEARNING-BASED SEED HARVEST MOISTURE PREDICTIONS TO IMPROVE A COMPUTER-ASSISTED AGRICULTURAL FARM OPERATION

• Main Authors: SSEGANE, Herbert, YANG, Xiao, XIE, Yao, SOOD, Shilpa, BULL, Jason Kendrick, EHLMANN, Tonya S, REICH, Timothy, MACISAAC, Susan Andrea, SCHNICKER, Bruce J, TRAPP, Allan, SORGE, Matthew, JACOBS, Morrison, SHAH, Nikisha
• Format: Patent
• Language: English; French; German
• Published: 14.09.2022
• Subjects: AGRICULTURE; ANIMAL HUSBANDRY; CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; FERTILISING; FISHING; FORESTRY; HARVESTING; HUMAN NECESSITIES; HUNTING; MOWING; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES ORIMPLEMENTS, IN GENERAL; PHYSICS; PLANTING; SOIL WORKING IN AGRICULTURE OR FORESTRY; SOWING; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TRAPPING

Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.