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14 条记录 (耗时 0.015 秒)

    Ultraviolet light and machine learning-based assessment of food item quality
    1.
    发明授权
    Ultraviolet light and machine learning-based assessment of food item quality 有权

    公开(公告)号：US11847681B2

    公开(公告)日：2023-12-19

    申请号：US18131532

    申请日：2023-04-06

    申请人： Apeel Technology, Inc.

    发明人： Benjamin Gordon ,  Ohad Michel ,  Matthew Kahlscheuer ,  Benjamin Flores ,  Charles Frazier ,  Louis Perez

    IPC分类号： G06Q30/00 ,  G06Q30/0601 ,  G06N20/00

    CPC分类号： G06Q30/0627 ,  G06N20/00

    摘要： The disclosed technology provides for determining infection in food items using image data of the food items under ultra-violet (UV) light. A method includes performing object detection on the image data to identify a bounding box around each of the food items in the image data, determining, for each food item, an infection presence metric by applying a model to the bounding box, the model being trained using image training data of other food items under UV light, the image training data being annotated based on previous identifications of a first portion of the other food items having infection features and a second portion having healthy quality features, and determining, based on a determination that the infection presence metric for each of the food items indicates presence of an infection, an infection coverage metric for the food item.

    SYSTEMS AND METHODS FOR PRE-HARVEST DETECTION OF LATENT INFECTION IN PLANTS
    3.
    发明申请
    SYSTEMS AND METHODS FOR PRE-HARVEST DETECTION OF LATENT INFECTION IN PLANTS 有权

    公开(公告)号：US20220132748A1

    公开(公告)日：2022-05-05

    申请号：US17519813

    申请日：2021-11-05

    申请人： Apeel Technology, Inc.

    发明人： Cody Vild ,  Savannah Braden ,  Matthew Kahlscheuer ,  Louis Perez

    IPC分类号： A01G7/06 ,  A01G25/16 ,  A01M7/00 ,  G06N20/00

    摘要： Disclosed herein are systems and methods for identifying pre-harvest latent infection in plants. In one aspect, a method can include operations of obtaining data describing a level of expression of one or more infection biomarkers present in a plant, encoding the obtained data into a data structure for input to a machine learning model, providing, by the one or more computers, encoded data structure as in input to the machine learning model that has been trained to generate output data indicating a likelihood that the plant has a latent infection based on processing the encoded data structure, obtaining the generated output data indicating a likelihood that the plant has a latent infection, determining based on the generated output data, that the plant has a latent infection, and performing one or more operations to mitigate the latent infection in the plant.

    PREDICTION OF INFECTION IN PLANT PRODUCTS
    4.
    发明申请
    PREDICTION OF INFECTION IN PLANT PRODUCTS 有权

    公开(公告)号：US20210151127A1

    公开(公告)日：2021-05-20

    申请号：US17090834

    申请日：2020-11-05

    申请人： Apeel Technology, Inc.

    发明人： Cody Vild ,  Savannah Braden ,  Matthew Kahlscheuer ,  Louis Perez

    IPC分类号： G16B40/00 ,  C12Q1/6895 ,  G06N20/00 ,  G06N5/04

    摘要： A method for predicting a likelihood of infection in a set of similarly sourced plant products is disclosed. A subset of plant products is selected from the set of plant products. For each plant product in the subset, a level of expression of one or more infection biomarkers, and optionally a level of expression of one more housekeeping biomarkers, are determined. A set of biomarker expression statistics for the subset of plant products is determined based on the determined levels of expression of the one or more infection biomarkers and optionally the levels of expression of the one or more housekeeping biomarkers for each plant product in the subset. A likelihood of infection in the set of plant products is then predicted based at least in part on the determined set of biomarker expression statistics for the subset of plant products.

    GAS PHASE TREATMENT OF PRODUCE
    6.
    发明公开
    GAS PHASE TREATMENT OF PRODUCE 审中-公开

    公开(公告)号：US20230292776A1

    公开(公告)日：2023-09-21

    申请号：US18124540

    申请日：2023-03-21

    申请人： Apeel Technology, Inc.

    发明人： Benjamin Gordon ,  Matthew Kahlscheuer ,  Charles Frazier ,  Jessica Sexton ,  Anthony Crisci

    IPC分类号： A23B7/144

    CPC分类号： A23B7/144

    摘要： A produce treatment method to mitigate latent infections, such as fungal infections, and to delay ripening in produce is described. The produce treatment method includes providing an antimicrobial agent to an enclosure comprising a plurality of produce items, and contacting the plurality of produce items with the antimicrobial agent, wherein the antimicrobial agent is in gaseous form and is selected to deactivate latent microbes in the plurality of produce items.

    Prediction of latent infection in plant products
    7.
    发明授权
    Prediction of latent infection in plant products 有权

    公开(公告)号：US11170872B2

    公开(公告)日：2021-11-09

    申请号：US17090834

    申请日：2020-11-05

    申请人： Apeel Technology, Inc.

    发明人： Cody Vild ,  Savannah Braden ,  Matthew Kahlscheuer ,  Louis Perez

    IPC分类号： G16B40/00 ,  G06N20/00 ,  C12Q1/6895 ,  G06N5/04 ,  G06Q10/08 ,  A01G22/00 ,  A01N1/00 ,  A01N3/00

    摘要： A method for predicting a likelihood of infection in a set of similarly sourced plant products is disclosed. A subset of plant products is selected from the set of plant products. For each plant product in the subset, a level of expression of one or more infection biomarkers, and optionally a level of expression of one more housekeeping biomarkers, are determined. A set of biomarker expression statistics for the subset of plant products is determined based on the determined levels of expression of the one or more infection biomarkers and optionally the levels of expression of the one or more housekeeping biomarkers for each plant product in the subset. A likelihood of infection in the set of plant products is then predicted based at least in part on the determined set of biomarker expression statistics for the subset of plant products.

    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY
    8.
    发明公开
    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY 审中-公开

    公开(公告)号：US20240062265A1

    公开(公告)日：2024-02-22

    申请号：US18499544

    申请日：2023-11-01

    申请人： Apeel Technology, Inc.

    发明人： Benjamin Gordon ,  Ohad Michel ,  Matthew Kahlscheuer ,  Benjamin Flores ,  Charles Frazier ,  Louis Perez

    IPC分类号： G06Q30/0601 ,  G06N20/00

    CPC分类号： G06Q30/0627 ,  G06N20/00

    摘要： The disclosed technology provides for determining infection in food items using image data of the food items under ultra-violet (UV) light. A method includes performing object detection on the image data to identify a bounding box around each of the food items in the image data, determining, for each food item, an infection presence metric by applying a model to the bounding box, the model being trained using image training data of other food items under UV light, the image training data being annotated based on previous identifications of a first portion of the other food items having infection features and a second portion having healthy quality features, and determining, based on a determination that the infection presence metric for each of the food items indicates presence of an infection, an infection coverage metric for the food item.