METHOD AND APPARATUS FOR RECORDING, PROCESSING, VISUALISATION AND APPLICATION OF AGRONOMICAL DATA

    公开(公告)号:US20200042909A1

    公开(公告)日:2020-02-06

    申请号:US16479805

    申请日:2018-01-24

    Applicant: GAMAYA SA

    Abstract: The present disclosure relates to methods and devices for a systemic approach to plant-based ecosystem management, including for juxtaposing, processing, organising, and visualizing data relevant to plant-based ecosystems, such as agricultural ecosystems, and delineating external interventions into such systems, such as human interventions, including those with automated machines. Recognizing the time-based—for example, seasonal—nature of plant-based ecosystems, this invention) juxtaposes relevant—but often previously dispersed—data types, 2) organizes them in tensors of customizable dimensions so as to facilitate modeling and in particular deep neural network and other deep machine learning and artificial intelligence approaches that take into account time-based, or other variable-based, changes to identify areas of interest within given land parcels, and 3) visualizes the data so as to highlight time-based, or other variable-based, relationships and trends. Such steps facilitate the development of individual plant or sub-land-parcel prescriptions for human intervention aimed at optimizing ecosystem output traits in the current season while considering their impact on subsequent seasons, thereby enabling the systematic management of plant-based ecosystems.

    PLANT-SYSTEM WITH INTERFACE TO MYCORRHIZAL FUNGAL COMMUNITY

    公开(公告)号:US20200275618A1

    公开(公告)日:2020-09-03

    申请号:US16649844

    申请日:2018-09-21

    Applicant: GAMAYA SA

    Abstract: A plant system (100), comprising a plurality of plants (102) in a substrate (101); a mycorrhizal fungal community (104) in the substrate arranged to form a biological interface with roots of the plants enabling an exchange of chemical substances between the fungus and the plurality of plants; and at least a sensor (207), which interfaces with said mycorrhizal fungal community and is configured to collect sensory information about a physiological condition and phenotypic state of said plurality of plants.

    Wide-angle computational imaging spectroscopy method and apparatus

    公开(公告)号:US11092489B2

    公开(公告)日:2021-08-17

    申请号:US16483048

    申请日:2018-01-31

    Applicant: GAMAYA SA

    Abstract: A system for computational imaging spectroscopy to provide compact and lightweight design, as well as large field of view of an object to be captured. The system includes imaging components, and computational device. The imaging components includes lens assembly, a fixed or variable-diameter aperture, spectral filter array and imaging sensor. The lens assembly provides wide angle of view, image-side telecentricity, and further may correct for longitudinal chromatic aberrations. The lens assembly may not provide correction of lateral chromatic aberrations. Furthermore, the lens assembly provides image-space telecentricity so as to chief rays are incident perpendicular to image sensor. The lens assembly may produce different chromatic aberrations pattern for each wavelength within the spectral range of interest. The pass-band nanofilter array is configured to filter a plurality of specific bands of light reflected from the imaged object and further produces a plurality of spatio-spectral samples of the imaged object projected onto the photosensitive pixels of imaging sensor. The computational device reconstructs complete spectral cube within the spectral range of interest, and further enables the computation of object reflectance at each pixel of the captured image from the plurality of spatio-spectral samples registered by the imaging sensor.

    WIDE-ANGLE COMPUTATIONAL IMAGING SPECTROSCOPY METHOD AND APPARATUS

    公开(公告)号:US20200348175A1

    公开(公告)日:2020-11-05

    申请号:US16483048

    申请日:2018-01-31

    Applicant: GAMAYA SA

    Abstract: A system for computational imaging spectroscopy to provide compact and lightweight design, as well as large field of view of an object to be captured. The system includes imaging components, and computational device. The imaging components includes lens assembly, a fixed or variable-diameter aperture, spectral filter array and imaging sensor. The lens assembly provides wide angle of view, image-side telecentricity, and further may correct for longitudinal chromatic aberrations. The lens assembly may not provide correction of lateral chromatic aberrations. Furthermore, the lens assembly provides image-space telecentricity so as to chief rays are incident perpendicular to image sensor. The lens assembly may produce different chromatic aberrations pattern for each wavelength within the spectral range of interest. The pass-band nanofilter array is configured to filter a plurality of specific bands of light reflected from the imaged object and further produces a plurality of spatio-spectral samples of the imaged object projected onto the photosensitive pixels of imaging sensor. The computational device reconstructs complete spectral cube within the spectral range of interest, and further enables the computation of object reflectance at each pixel of the captured image from the plurality of spatio-spectral samples registered by the imaging sensor.

    SYSTEMS AND METHODS TO PREDICT HARVEST CYCLES USING NEURAL NETWORKS

    公开(公告)号:US20250063977A1

    公开(公告)日:2025-02-27

    申请号:US18742538

    申请日:2024-06-13

    Applicant: Gamaya SA

    Abstract: A method according to an embodiment includes receiving, at one or more processors, satellite image data, temperature measurement data, precipitation measurement data, and one or more agronomic parameters, associated with an agricultural land segment. The method also includes predicting, using the one or more processors and a first neural network, a biomass value associated with the agricultural land segment. The method also includes predicting, using the one or more processors and a second neural network, a sugar content value associated with the agricultural land segment. The method also includes predicting, using the one or more processors, a total sugar value associated with the agricultural land segment. Optionally, the method also includes optimizing harvest dates for a plurality of agricultural land segments that includes the agricultural land segment, based on one or more constraints.

    Systems and methods to predict harvest cycles using neural networks

    公开(公告)号:US12010939B1

    公开(公告)日:2024-06-18

    申请号:US18454397

    申请日:2023-08-23

    Applicant: Gamaya SA

    Abstract: A method according to an embodiment includes receiving, at one or more processors, satellite image data, temperature measurement data, precipitation measurement data, and one or more agronomic parameters, associated with an agricultural land segment. The method also includes predicting, using the one or more processors and a first neural network, a biomass value associated with the agricultural land segment. The method also includes predicting, using the one or more processors and a second neural network, a sugar content value associated with the agricultural land segment. The method also includes predicting, using the one or more processors, a total sugar value associated with the agricultural land segment. Optionally, the method also includes optimizing harvest dates for a plurality of agricultural land segments that includes the agricultural land segment, based on one or more constraints.

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