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公开(公告)号：US11796970B2
公开(公告)日：2023-10-24
申请号：US17952965
申请日：2022-09-26
Applicant: Climate LLC
Inventor： Gardar Johannesson , Maria Terres , Moslem Ladoni , Carlos Carrion , Nicholas Cizek , Brian Lutz , Ricardo Lemos , James Delaney
CPC classification number: G05B13/048 , A01B79/005 , A01B79/02 , G06F17/18
Abstract: Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field, the first portion of the agronomic field having received a first treatment, and second yield data, for a second portion of the agronomic field, the second portion of the agronomic field having received a second treatment that is different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, the yield value indicating an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment. In an embodiment, in response to selecting the second treatment, the system generates a prescription map, the prescription map including the second treatment. The system may also generate one or more scripts which, when executed by an application controller, cause the application controller to control an operating parameter of an agricultural implement to apply the second treatment.
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Patent Agency Ranking
公开(公告)号：US11796971B2
公开(公告)日：2023-10-24
申请号：US17977860
申请日：2022-10-31
Applicant: Climate LLC
Inventor： Carlos Carrion , Nicholas Cizek , James Delaney , Gardar Johannesson , Moslem Ladoni , Ricardo Lemos , Brian Lutz , Maria Terres
CPC classification number: G05B13/048 , A01B79/005 , A01B79/02 , G06F17/18
Abstract: Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field having received a first treatment, and second yield data for a second portion of the agronomic field having received a second treatment different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, where the yield value indicates an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment and generates a prescription map including the second treatment.
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公开(公告)号：US20230050552A1
公开(公告)日：2023-02-16
申请号：US17977860
申请日：2022-10-31
Applicant: CLIMATE LLC
Inventor： Carlos Carrion , Nicholas Cizek , James Delaney , Gardar Johannesson , Moslem Ladoni , Ricardo Lemos , Brian Lutz , Maria Terres
Abstract: Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field having received a first treatment, and second yield data for a second portion of the agronomic field having received a second treatment different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, where the yield value indicates an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment and generates a prescription map including the second treatment.
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公开(公告)号：US12052943B1
公开(公告)日：2024-08-06
申请号：US17181956
申请日：2021-02-22
Applicant: CLIMATE LLC
Inventor： Hunter Merrill , Gardar Johannesson
CPC classification number: A01C21/005 , G05D1/0016 , G05D1/0212 , G06N7/01 , G06N20/00
Abstract: Systems and methods for improving the training of machine learning models to generate probability distributions of yield values are presented. In an embodiment, a system stores a machine learning system trained to compute parameters for a probability distribution of yield values based on seeding density, seed type, and information specific to a field. The system receives inputs for a particular field and computes parameters for a probability distribution of yield. The system generates a probability distribution of yield using the parameters and uses the probability distribution to generate a yield guarantee value. The system supplies the yield guarantee value to a field manager computing device with a seed type and/or seed density recommendation. When the system receives input accepting the recommendation, the system generates one or more scripts which, when executed by an application controller, causes the application controller to control an agricultural implement to cause the agricultural implement to plant a seed on the field according to the recommendation.
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公开(公告)号：US11574465B2
公开(公告)日：2023-02-07
申请号：US16725869
申请日：2019-12-23
Applicant: CLIMATE LLC
Inventor： Yaqi Chen , Gardar Johannesson , Wei Guan
Abstract: In an embodiment, digital images of agricultural fields are received at an agricultural intelligence processing system. Each digital image includes a set of pixels having pixel values, and each pixel value of a pixel includes a plurality of spectral band intensity values. Each spectral band intensity value describes a spectral band intensity of one band among several bands of electromagnetic radiation. For each of the agricultural fields, spectral band intensity values of each band are preprocessed at a field level using the digital images for that agricultural field resulting in preprocessed intensity values. The preprocessed intensity values are provided as input to a machine learning model. The model generates a predicted yield value for each field. The predicted yield value is used to update field yield maps of agricultural fields for forecasting and can be displayed via a graphical user interface (GUI) of a client computing device.
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公开(公告)号：US11487254B2
公开(公告)日：2022-11-01
申请号：US16723892
申请日：2019-12-20
Applicant: Climate LLC
Inventor： Gardar Johannesson , Maria Terres , Moslem Ladoni , Carlos Carrion , Nicholas Cizek , Brian Lutz , Ricardo Lemos , James Delaney
Abstract: Systems and methods for utilizing a spatial statistical model to maximize efficacy in performing trials on agronomic fields are disclosed herein. In an embodiment, a system receives first yield data for a first portion of an agronomic field, the first portion of the agronomic field having received a first treatment, and second yield data, for a second portion of the agronomic field, the second portion of the agronomic field having received a second treatment that is different than the first treatment. The system uses a spatial statistical model and the first yield data to compute a yield value for the second portion of the agronomic field, the yield value indicating an agronomic yield for the second portion of the agronomic field if the second portion of the agronomic field had received the first treatment instead of the second treatment. Based on the computed yield value and the second yield data, the system selects the second treatment. In an embodiment, in response to selecting the second treatment, the system generates a prescription map, the prescription map including the second treatment. The system may also generate one or more scripts which, when executed by an application controller, cause the application controller to control an operating parameter of an agricultural implement to apply the second treatment.
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