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公开(公告)号：US10529036B2
公开(公告)日：2020-01-07
申请号：US15004820
申请日：2016-01-22
Applicant: The Climate Corporation
Abstract: A method for determining national crop yields during the growing season may be accomplished using a system that receives agricultural data records that are used to forecast a national crop yield for a particular year. Weather index values are calculated and aggregated from the agricultural data records. Crop yield estimating instructions select representative features from aggregated weather index data and create a covariate matrix for each specific geographic area. Linear regression instructions calculate the crop yield for the specific geographic area for the specific year using the corresponding covariate matrix for that specific year. The crop estimating instructions determine a national crop yield for the specific year using the sum of the crop yields for the specific geographic areas for the specific year nationally adjusted using national yield adjustment instructions. In an embodiment, the crop yield may refer to a specific crop yield such as corn yield.
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公开(公告)号：US10154624B2
公开(公告)日：2018-12-18
申请号：US15231505
申请日：2016-08-08
Applicant: The Climate Corporation
Abstract: In an approach, hyperspectral and/or multispectral remote sensing images are automatically analyzed by a nitrogen analysis subsystem to estimate the value of nitrogen variables of crops or other plant life located within the images. For example, the nitrogen analysis subsystem may contain a data collector module, a function generator module, and a nitrogen estimator module. The data collector module prepares training data which is used by the function generator module to train a mapping function. The mapping function is then used by the nitrogen estimator module to estimate the values of nitrogen variables for a new remote sensing image that is not included in the training set. The values may then be reported and/or used to determine an optimal amount of fertilizer to add to a field of crops to promote plant growth.
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13.发明授权公开(公告)号：US11551313B2
公开(公告)日：2023-01-10
申请号：US16853601
申请日：2020-04-20
Applicant: THE CLIMATE CORPORATION
Inventor： Lijuan Xu , Ying Xu , Ankur Gupta
Abstract: A computer implemented method for generating digital models of relative crop yield based on nitrate values in the soil is provided. In an embodiment, nitrate measurements from soil during a particular portion of a crop's development and corresponding crop yields are received by an agricultural intelligence computing system. Based, at least in part, on the nitrate measurements and corresponding crop yields, the system determines maximum yields for each location of a plurality of locations. The system then converts each crop yield value into a relative crop yield by dividing the crop yield value by the maximum crop yield for the location. Using the relative crop yields and the corresponding nitrate values in the soil, the system generates a digital model of relative crop yield as a function of nitrate in the soil during the particular portion of the crop's development. When the system receives nitrate measurements from soil in a particular field during the particular portion of a crop's development, the system computes a relative yield value for the particular field using the model of relative crop yield.
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公开(公告)号：US10586158B2
公开(公告)日：2020-03-10
申请号：US14925797
申请日：2015-10-28
Applicant: The Climate Corporation
Inventor： Jiunn-Ren Chen , Ying Xu
Abstract: A computer system and computer-implemented techniques for determining crop harvest times during a growing season based upon hybrid seed properties, weather conditions, and geo-location of planted fields is provided. In an embodiment, determining crop harvest times for corn fields may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including seed type and relative maturity, and weather data for the specific geo-location of the agricultural field.
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15.发明授权公开(公告)号：US10251347B2
公开(公告)日：2019-04-09
申请号：US14990463
申请日：2016-01-07
Applicant: THE CLIMATE CORPORATION
Inventor： Ying Xu , Erik Andrejko
Abstract: A method for generating digital models of potential crop yield based on planting date, relative maturity, and actual production history is provided. In an embodiment, data representing historical planting dates, relative maturity values, and crop yield is received by an agricultural intelligence computer system. Based on the historical data, the system generates spatial and temporal maps of planting dates, relative maturity, and actual production history. Using the maps, the system creates a model of potential yield that is dependent on planting date and relative maturity. The system may then receive actual production history data for a particular field. Using the received actual production history data, a particular planting date, and a particular relative maturity value, the agricultural intelligence computer system computes a potential yield for a particular field.
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Patent Agency Ranking
公开(公告)号：US20180101728A1
公开(公告)日：2018-04-12
申请号：US15831269
申请日：2017-12-04
Applicant: The Climate Corporation
CPC classification number: G06K9/00657 , G06K9/42 , G06K9/6215
Abstract: Systems and methods for scalable comparisons between two pixel maps are provided. In an embodiment, an agricultural intelligence computer system generates pixel maps from non-image data by transforming a plurality of values and location values into pixel values and pixel locations. The non-image data may include data relating to a particular agricultural field, such as nutrient content in the soil, pH values, soil moisture, elevation, temperature, and/or measured crop yields. The agricultural intelligence computer system converts each pixel map into a vector of values. The agricultural intelligence computer system also generates a matrix of metric coefficients where each value in the matrix of metric coefficients is computed using a spatial distance between to pixel locations in one of the pixel maps. Using the vectors of values and the matrix of metric coefficients, the agricultural intelligence computer system generates a difference metric identifying a difference between the two pixel maps. In an embodiment, the difference metric is normalized so that the difference metric is scalable to pixel maps of different sizes. The difference metric may then be used to select particular images that best match a measured yield, identify relationships between field values and measured crop yields, identify and/or select management zones, investigate management practices, and/or strengthen agronomic models of predicted yield.
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17.发明申请公开(公告)号：US20170169523A1
公开(公告)日：2017-06-15
申请号：US14968728
申请日：2015-12-14
Applicant: THE CLIMATE CORPORATION
Inventor： Lijuan Xu , Ying Xu , Ankur Gupta
CPC classification number: G06Q50/02 , A01B79/005 , A01C21/00 , G06Q10/06315 , G06Q10/067
Abstract: A computer implemented method for generating digital models of relative crop yield based on nitrate values in the soil is provided. In an embodiment, nitrate measurements from soil during a particular portion of a crop's development and corresponding crop yields are received by an agricultural intelligence computing system. Based, at least in part, on the nitrate measurements and corresponding crop yields, the system determines maximum yields for each location of a plurality of locations. The system then converts each crop yield value into a relative crop yield by dividing the crop yield value by the maximum crop yield for the location. Using the relative crop yields and the corresponding nitrate values in the soil, the system generates a digital model of relative crop yield as a function of nitrate in the soil during the particular portion of the crop's development. When the system receives nitrate measurements from soil in a particular field during the particular portion of a crop's development, the system computes a relative yield value for the particular field using the model of relative crop yield.
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公开(公告)号：US20170124463A1
公开(公告)日：2017-05-04
申请号：US14925797
申请日：2015-10-28
Applicant: The Climate Corporation
Inventor： Jiunn-Ren Chen , Ying Xu
Abstract: A computer system and computer-implemented techniques for determining crop harvest times during a growing season based upon hybrid seed properties, weather conditions, and geo-location of planted fields is provided. In an embodiment, determining crop harvest times for corn fields may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including seed type and relative maturity, and weather data for the specific geo-location of the agricultural field. Weather data includes temperature, humidity, and dew point for a specified period of days. Using digitally programmed equilibrium moisture content logic within the computer system to create and store, in computer memory, an equilibrium moisture content time series for the specific geo-location that is based upon weather data. The equilibrium moisture content is used to determine the rate of grain dry down because it gives a basis for how strongly water vapor will dissipate from a kernel to open air. Using digitally programmed grain moisture logic of the computer system to calculate and store in computer memory R6 moisture content for a specific hybrid seed based on a plurality of hybrid seed data. Using digitally programmed grain dry down logic of the computer system to create and store in computer memory a grain dry down time series model for the specific hybrid seed at the specific geo-location that represents the estimated moisture content of the kernel over specified time data points. The grain dry down time series is based upon the equilibrium moisture content time series, the estimated R6 date, the estimated R6 moisture content value, and specific hybrid seed properties. Using digitally programmed harvest recommendation logic of the computer system to determine and display a harvest time recommendation for harvesting crop grown from a specific hybrid seed plant based on the grain dry down time series and the desired moisture level of the grower.
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公开(公告)号：US20210097632A1
公开(公告)日：2021-04-01
申请号：US17011483
申请日：2020-09-03
Applicant: The Climate Corporation
IPC: G06Q50/02
Abstract: A method for determining national crop yields during a growing season is accomplished using a server computer system that receives observed agricultural data records for a specific geo-location at a specific time. The server calculates weather index values from the agricultural data records that represent crop stress on plants. Geo-specific weather indices are generated from the weather index values, which then are aggregated to generate aggregated weather index data series. Representative features are selected from each aggregated weather index data series to create a covariate matrix for each geographic area. Crop yield for the geographic area is calculated using a linear regression model based on the covariate matrix for the specific geographic area. The server determines a national crop yield for the specific year as a sum of the crop yields for the specific geographic areas nationally adjusted using national yield adjustment instructions.
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20.发明申请公开(公告)号：US20190230873A1
公开(公告)日：2019-08-01
申请号：US16375589
申请日：2019-04-04
Applicant: The Climate Corporation
Inventor： Ying Xu , Erik Andrejko
Abstract: A method for generating digital models of potential crop yield based on planting date, relative maturity, and actual production history is provided. In an embodiment, data representing historical planting dates, relative maturity values, and crop yield is received by an agricultural intelligence computer system. Based on the historical data, the system generates spatial and temporal maps of planting dates, relative maturity, and actual production history. Using the maps, the system creates a model of potential yield that is dependent on planting date and relative maturity. The system may then receive actual production history data for a particular field. Using the received actual production history data, a particular planting date, and a particular relative maturity value, the agricultural intelligence computer system computes a potential yield for a particular field.
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