OPTIMAL PLACEMENT AND PORTFOLIO OPPORTUNITY TARGETING

    公开(公告)号:US20200005401A1

    公开(公告)日:2020-01-02

    申请号:US16457709

    申请日:2019-06-28

    Abstract: Techniques are provided for receiving a first set of historical agricultural data for one or more fields of a grower and a second set of historical agricultural data comprising a dataset of hybrid seed properties; cross-referencing the first set and the second set of historical agricultural data to generate a yield range improvement recommendation for each of the one or more fields, wherein the yield improvement recommendation comprises a recommended change in seed population or a recommended change in seed density; generating predictive yield data for the one or more fields by applying the yield improvement recommendation to the first set of historical agricultural data; generating comparison yield data using the grower yield data and the predictive yield data for the one or more fields; and causing displaying the comparison yield data for the grower.

    Risk-adjusted hybrid seed selection and crop yield optimization by field

    公开(公告)号:US10993365B2

    公开(公告)日:2021-05-04

    申请号:US16128380

    申请日:2018-09-11

    Abstract: Techniques are provided for receiving a first set of historical agricultural data and a second set of historical agricultural data; generating a plurality of projected target yield ranges using the first set and the second set of historical agricultural data by generating a historic yield distribution; generating one or more yield ranking scores for one or more fields of a grower using the first set of historical agricultural data, and assigning a projected target yield range of the plurality of projected target yield ranges to each of the one or more fields based on the one or more yield ranking scores to generate assigned projected target yield ranges; receiving a third set of historical agricultural data comprising seed optimization data, and generating a recommended change in seed population or a recommended change in seed density; causing displaying the yield improvement recommendation for each of the one or more fields.

    LEVERAGING FEATURE ENGINEERING TO BOOST PLACEMENT PREDICTABILITY FOR SEED PRODUCT SELECTION AND RECOMMENDATION BY FIELD

    公开(公告)号:US20200327603A1

    公开(公告)日:2020-10-15

    申请号:US16845052

    申请日:2020-04-09

    Abstract: An example computer-implemented method includes receiving a plurality of agricultural data records including yield properties of products grown in fields and raw field features of the fields. The method also includes transforming the raw field features into distinct feature classes that characterize key features affecting yield of the one or more products, and generating, using data from the plurality of agricultural data records and the distinct feature classes, genomic-by-environmental relationships between one or more products, yield properties of the one or more products, and field features associated with the one or more products. Further, the method includes generating, based at least in part on the genomic-by-environmental relationships, predicted yield performance for a set of products associated with one or more target environments, generating product recommendations for the one or more target environments based on the predicted yield performance for the set of products, and providing one or more instructions configured to cause display of the product recommendations.

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