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公开(公告)号：US20220196877A1
公开(公告)日：2022-06-23
申请号：US17693158
申请日：2022-03-11
Applicant: CLIMATE LLC
IPC: G01V99/00 , G01N21/359 , G01N33/00 , G06Q10/04 , G06F30/27 , A01B76/00 , G01N21/31 , G01W1/10 , G01N33/24
Abstract: A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific crop yield for a specific year using linear regression to calculate the specific crop yield from the covariate matrix. The system determines a forecasted crop yield for the specific year using a sum of the specific crop yields for the specific year, as adjusted.
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公开(公告)号：US11762125B2
公开(公告)日：2023-09-19
申请号：US17693158
申请日：2022-03-11
Applicant: CLIMATE LLC
IPC: G01V99/00 , G01N21/359 , G01N33/00 , G06Q10/04 , G06F30/27 , A01B76/00 , G01N21/31 , G01W1/10 , G01N33/24 , G01N21/17 , A01B79/00 , G06F111/06
CPC classification number: G01V99/005 , A01B76/00 , G01N21/31 , G01N21/359 , G01N33/0098 , G01N33/24 , G01W1/10 , G06F30/27 , G06Q10/04 , A01B79/005 , G01N2021/1793 , G01N2021/3155 , G01N2201/0616 , G01N2201/129 , G06F2111/06
Abstract: A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific crop yield for a specific year using linear regression to calculate the specific crop yield from the covariate matrix. The system determines a forecasted crop yield for the specific year using a sum of the specific crop yields for the specific year, as adjusted.
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公开(公告)号：US11882786B2
公开(公告)日：2024-01-30
申请号：US17948128
申请日：2022-09-19
Applicant: CLIMATE LLC
Inventor： Sanjay Lamsal , Lijuan Xu
CPC classification number: A01C7/102 , A01B79/005 , A01C21/00 , G06N5/04 , G06N7/01
Abstract: A computer system and computer-implemented techniques for determining and presenting improved seeding rate recommendations for planting seeds in a field are provided. In an embodiment, a computer-implemented method includes receiving digital data representing planting parameters including seed type information and planting row width, and retrieving a set of seeding models based upon the planting parameters, where each of the seeding models includes a regression model defining a relationship between plant yield and seeding rate on a specific field. The method also includes generating an empirical mixture model as a composite distribution of the set of seeding models, generating a seeding rate distribution for the planting parameters based upon the empirical mixture model, and calculating a seeding rate recommendation based on the seed rate distribution. The method then also includes planting plant seeds in the specific field consistent with the seeding rate recommendation.
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公开(公告)号：US11445660B2
公开(公告)日：2022-09-20
申请号：US17083288
申请日：2020-10-28
Applicant: CLIMATE LLC
Inventor： Lijuan Xu , Sanjay Lamsal
Abstract: A computer system and computer-implemented techniques for determining and presenting improved seeding rate recommendations for sowing hybrid seeds in a field is provided. In an embodiment, determining and presenting seeding rate recommendations for a field may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including hybrid seed type, and sowing row width. Using digitally programmed seeding query logic, within the server computer system, receiving digital data representing planting parameters including hybrid seed type information and sowing row width. The seeding query logic then retrieves a set of one or more seeding models from an electronic digital seeding data repository based upon the planting parameters. Each of the seeding model retrieved contain a regression model for the hybrid seed type modeling a relationship between plant yield and seeding rate on a specific field. Using mixture model logic, within the server computer system, generating an empirical mixture model in digital computer memory that represents a composite distribution of the set of one or more seeding models. The mixture model logic then generates an optimal seeding rate distribution dataset in digital computer memory based upon the empirical mixture model, where the optimal seeding rate distribution dataset represents the optimal seeding rate across all measure fields. Using optimal seeding rate recommendation logic, within the server computer system, calculating and presenting on a digital display device an optimal seeding rate recommendation that is based upon the optimal seeding rate distribution dataset.
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