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 threshol...