Satellite-based agricultural modeling

A non-transitory computer-readable storage medium storing executable instructions that, when executed, cause an online agricultural system to perform steps comprising:

• generating a first training set of data comprising historic crop information and current crop information representative of a first crop product;
• training a first machine-learned model configured to predict a future characteristic of the first crop product using the training set of data;
• generating a second training set of data comprising remote sensor data corresponding to the crop product type of the first crop product and associated historic quality specification data corresponding to the crop product type of the first crop product;
• training a second machine-learned model configured to predict a quality specification for the first crop product based on remote sensor data corresponding to the first crop product using the second training set of data;
• for each of a plurality of crop producers:
• receiving a first request to list a first crop product within the online agricultural system, the first request identifying a first location of the first crop product and a crop product type of the first crop product;
• applying the first machine-learned model to the first location of the first crop product and the crop product type to predict a first future characteristic of the first crop product;
• modifying a first user interface presented to the crop producer to include the predicted first future characteristic, the user interface requesting one or both of a first crop product price and a first quantity of the first crop product;
• and
• determining a first quality specification for the first crop product listed within the first request by applying the second machine-learned model to remote sensor data corresponding to the first crop product;
• and
• for each of a plurality of prospective acquiring entities:
• receiving a second request to acquire a second crop product, the second request identifying a second quality requirement of the second crop product and at least the crop product type of the second crop product, a second quantity of the second crop product, a second crop product price, and a second location to which the second crop product is to be delivered;
• monitoring, by a server in real-time, the first quality specification of each first request received from a crop producer to identify a set of first requests with first quality specifications that satisfy the second quality requirement of the second crop product identified by the second request;
• and
• modifying a second user interface presented to the prospective acquiring entity to include for one or more first requests in the identified set of first requests:
• the corresponding predicted first future characteristic, the corresponding first crop product price, the corresponding first quantity of the first crop product, the corresponding first location of the first crop product, and the corresponding first quality specification of the first crop product.

An online agricultural system comprising:

• a non-transitory computer-readable storage medium storing executable instructions that, when executed, cause the online agricultural system to perform steps comprising:
• generating a first training set of data comprising historic crop information and current crop information representative of a first crop product;
• training a first machine-learned model configured to predict a future characteristic of the first crop product using the training set of data;
• generating a second training set of data comprising remote sensor data corresponding to the crop product type of the first crop product and associated historic quality specification data corresponding to the crop product type of the first crop product;
• training a second machine-learned model configured to predict a quality specification for the first crop product based on remote sensor data corresponding to the first crop product using the second training set of data;
• for each of a plurality of crop producers:
• receiving a first request to list a first crop product within the online agricultural system, the first request identifying a first location of the first crop product and a crop product type of the first crop product;
• applying the first machine-learned model to the first location of the first crop product and the crop product type to predict a first future characteristic of the first crop product;
• modifying a first user interface presented to the crop producer to include the predicted first future characteristic, the user interface requesting one or both of a first crop product price and a first quantity of the first crop product;
• and
• determining a first quality specification for the first crop product listed within the first request by applying the second machine-learned model to remote sensor data corresponding to the first crop product;
• and
• for each of a plurality of prospective acquiring entities;
• receiving a second request to acquire a second crop product, the second request identifying a second quality requirement of the second crop product and at least the crop product type of the second crop product, a second quantity of the second crop product, a second crop product price, and a second location to which the second crop product is to be delivered;
• monitoring, by a server in real-time, the first quality specification of each first request received from a crop producer to identify a set of first requests with first quality specifications that satisfy the second quality requirement of the second crop product identified by the second request;
• and
• modifying a second user interface presented to the prospective acquiring entity to include for one or more first requests in the identified set of first requests:
• the corresponding predicted first future characteristic, the corresponding first crop product price, the corresponding first quantity of the first crop product, the corresponding first location of the first crop product, and the corresponding first quality specification of the first crop product.

A method comprising:

• generating a first training set of data comprising historic crop information and current crop information representative of a first crop product;
• training a first machine-learned model configured to predict a future characteristic of the first crop product using the training set of data;
• for each of a plurality of crop producers:
• receiving a first request to list a first crop product within an online agricultural system, the first request identifying a first location of the first crop product and a crop product type of the first crop product;
• applying the first machine-learned model to the first location of the first crop product and the crop product type to predict a first future characteristic of the first crop product;
• and
• modifying a first user interface presented to the crop producer to include the predicted first future characteristic, the user interface requesting one or both of a first crop product price and a first quantity of the first crop product;
• and
• for each of a plurality of prospective acquiring entities;
• receiving a second request to acquire a second crop product, the second request identifying a second quality requirement of the second crop product and at least the crop product type of the second crop product, a second quantity of the second crop product, a second crop product price, and a second location to which the second crop product is to be delivered;
• monitoring, by a server in real-time, a first quality specification of each first request received from a crop producer to identify a set of first requests with first quality specifications that satisfy the second quality requirement of the second crop product identified by the second request;
• and
• modifying a second user interface presented to the prospective acquiring entity to include for one or more first requests in the identified set of first requests:
• the corresponding predicted first future characteristic, the corresponding first crop product price, the corresponding first quantity of the first crop product, the corresponding first location of the first crop product, and the corresponding first quality specification of the first crop product.