Crop yield estimation using agronomic neural network
Abstract:
Systems and method for computing yield values through a neural network from a plurality of different data inputs are disclosed. In an embodiment, a server computer system receives a particular dataset relating to one or more agricultural fields wherein the particular data set comprises particular crop identification data, particular environmental data, and particular management practice data. Using a first neural network, the server computer system computes a crop identification effect on crop yield from the particular crop identification data. Using a second neural network, the server computer system computes an environmental effect on crop yield from the particular environmental data. Using a third neural network, the server computer system computes a management practice effect on crop yield from the management practice data. Using a master neural network, the server computer system computes one or more predicted yield values from the crop identification effect on crop yield, the environmental effect on crop yield, and the management practice effect on crop yield.
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