Automatically assigning hybrids or seeds to fields for planting

Abstract

Techniques are provided for automatically assigning hybrid products or seed products to agricultural fields with optimal yield performance. In one embodiment, a computer-implemented method comprises using field assignment instructions in the server computer system, receiving, over a digital data communication network at a server computer system, grower datasets specifying agricultural fields of growers and inventories of hybrid products or seed products of the growers; using the field assignment instructions in the server computer system, obtaining over the digital data communication network at the server computer system, other input data comprising relative maturity values, historic yield values for the fields of the growers, and mean yield values for regions in which the fields of the growers are located; using the field assignment instructions in the server computer system, calculating pair datasets consisting of permutations of product assignments of two (2) products to two (2) fields from among the fields of the growers, and corresponding converse assignments of the same products and fields; inputting specified features of the pair dataset(s) to a trained machine learning model, to yield predicted POS values for each of the product assignments and its corresponding converse assignment; blending the predicted POS values for all fields with field classification data using an operations research model of other field data, to result in creating and storing score values for each of the product assignments and the corresponding converse assignments; using the field assignment instructions in the server computer system, generating and causing displaying at least the product assignments in a graphical user interface display of a client computing device.

Dependencies are inferred from the claim text.