The data set that has been kindly provided by Martin Schneider was obtained from growing of winter wheat.
It has roughly 5000 records for small-scale areas of a crop field, which contain the following attributes:

  • ID: numeric identifier
  • N1, N2, N3: there are three periods (at least in Germany) where fertilizer is applied; these values store the amount used per area
  • REIP32, REIP49: indexed value that measures the amount of sunlight reflected from the crop
  • EM38: electric conductivity of soil
  • Variant: categorical attribute, describes the management strategy applied to the area under consideration
  • tractive power: the amount of power that is needed to pull e.g. a plough
  • yield 2003, 2004: stores the yield from the respective area

The target is quite similar to the one in the sports science category:

  • learn neural networks from the data
  • feed the networks with current year’s input data
  • predict this year’s yield and / or
  • optimize the amount of fertilizer by simulating different amounts and predicting with the ANNs