CPC A01B 79/005 (2013.01) [A01B 79/02 (2013.01); G06N 20/00 (2019.01); G06Q 50/02 (2013.01)] | 19 Claims |
1. A computer-implemented method for training a predictive model for crop management comprising:
collecting a first data set about at least one global agricultural factor from a remote data collection service;
collecting a second data set about at least one local agricultural factor from a local data collection device;
assimilating the first and second data sets into a local database to create a first training data set comprising the collected first set of data and the collected second set of data;
training a predictive model using the first training data set to produce one or more measurable outcomes for the crop;
collecting a third data set about at least one global vineyard factor from the remote data collection service;
collecting a fourth data set about at least one local vineyard factor from the local data collection device; and
predicting a measurable crop outcome using the trained predictive model in response to the collected third data set and the collected fourth data set; wherein the predictive output comprises a mapping one of the group comprised of: a habitat suitability, a suggested varietal to plant, an expected quality of a crop, or a potential plantable crop varietal.
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