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