Computer-implemented recommendation of side-by-side planting in agricultural fields

    公开(公告)号:US11564345B1

    公开(公告)日:2023-01-31

    申请号:US16450586

    申请日:2019-06-24

    Applicant: CLIMATE LLC

    Abstract: Techniques for recommending side-by-side plantings of pairs of hybrids or seeds include a server computer receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first data for agricultural fields where the hybrid seeds were planted. The server receives second data for available hybrids and seeds and automatically calculates a dataset of success probability scores that describe the probability of a successful yield on the target fields. Data is organized as pairs to facilitate comparison of actual plantings to optimized plantings that have a probability of success (POS), in terms of yield lift or increased yield season-over-season, for different yield values. Confidence values are generated and stored in association with the POS values and can be used as a basis of visual output to support planting and/or field management decisions as part of an automated intelligent agricultural decision support system.

    Computer-implemented recommendation of side-by-side planting in agricultural fields

    公开(公告)号:US11864488B1

    公开(公告)日:2024-01-09

    申请号:US18103151

    申请日:2023-01-30

    Applicant: CLIMATE LLC

    CPC classification number: A01C7/102 A01C21/005 G06F16/248 G06F16/29 G06N7/01

    Abstract: Techniques for recommending side-by-side plantings of pairs of seeds include a server computer receiving agricultural data records that represent crop seed data describing seed and yield properties of seeds and first data for agricultural fields where the seeds were planted. The server receives second data for available seeds and automatically calculates a dataset of success probability scores that describe the probability of a successful yield on the target fields. Data is organized as pairs to facilitate comparison of actual plantings to optimized plantings that have a probability of success (POS), in terms of yield lift or increased yield season-over-season, for different yield values. Confidence values are generated and stored in association with the POS values and can be used as a basis of visual output to support planting and/or field management decisions as part of an automated intelligent agricultural decision support system.

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