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