Abstract: Systems and methods are provided for managing agricultural activities in a field region. In one example, a computer-implemented method includes identifying temperature grids for the field region, and identifying weather stations for the temperature grids. Each weather station is located at a weather station location in the temperature grids. The computer-implemented method also includes computing weight values based on the weather station locations of the weather stations, such that the weather stations that are more proximate to their respective grids have higher weights than weather stations that are less proximate to their respective grids, and receiving temperature readings from the weather stations. The computer-implemented method then includes computing a plurality of weighted temperatures based on the weight values, computing field condition data for the field region based on the weighted temperatures, and determining at least one field activity for the field region based on the field condition data.

Abstract: A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

Abstract: Systems and methods are provided for managing hybrid seeds for planting. One example computer-implemented method includes receiving a first dataset of hybrid seeds for planting on a target field, where the first dataset includes probability of success values and historical agricultural data for the hybrid seeds, and selecting a subset of hybrid seeds of the first dataset based on the probability of success values. The method also includes generating representative yield values for the subset of hybrid seeds based on the historical agricultural data, generating risk values for the subset of hybrid seeds based on the historical agricultural data, and generating a second dataset of hybrid seeds for planting based on the risk values, the representative yield values, and properties for the target field. The method further includes causing displaying the representative yield values and the risk values related to the second dataset of hybrid seeds for planting.

Abstract: Techniques are provided for generating target success group of hybrid seeds for target fields include a server receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first field geo-location data for agricultural fields where the hybrid seeds were planted. The server receives second geo-locations data for target fields where hybrid seeds are to be planted. The server generates a dataset of hybrid seed properties that include yield values and environmental classifications for hybrid seeds and then a dataset of success probability scores that describe the probability of a successful yield on the target fields based on the dataset of hybrid seed properties and the second geo-location data. The server generates target success yield group of hybrid seeds and probability of success values based on success probability scores and a yield threshold. The server causes display of the target success yield group.

Abstract: A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

Abstract: A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

Abstract: A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

Abstract: A computer-implemented method for recommending agricultural activities is implemented by an agricultural intelligence computer system in communication with a memory. The method includes receiving a plurality of field definition data, retrieving a plurality of input data from a plurality of data networks, determining a field region based on the field definition data, identifying a subset of the plurality of input data associated with the field region, determining a plurality of field condition data based on the subset of the plurality of input data, identifying a plurality of field activity options, determining a recommendation score for each of the plurality of field activity options based at least in part on the plurality of field condition data, and providing a recommended field activity option from the plurality of field activity options based on the plurality of recommendation scores.

Abstract: Techniques are provided for generating target success group of hybrid seeds for target fields include a server receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first field geo-location data for agricultural fields where the hybrid seeds were planted. The server receives second geo-locations data for target fields where hybrid seeds are to be planted. The server generates a dataset of hybrid seed properties that include yield values and environmental classifications for hybrid seeds and then a dataset of success probability scores that describe the probability of a successful yield on the target fields based on the dataset of hybrid seed properties and the second geo-location data. The server generates target success yield group of hybrid seeds and probability of success values based on success probability scores and a yield threshold. The server causes display of the target success yield group.