Pattern Mining in Grassland Science

By Jens Harbers

grasland science pattern mining agriculture

This article presents ideas on how pattern mining can be applied in grassland science, where there is a high demand for rule pattern recognition, evaluation, and selection. In principle, vegetation data are well suited for pattern mining because they are available in a table structure that can be easily read by a program. Some of the application areas are listed below:

1. Suggestion of suitable plants to increase biodiversity in a field.

2. Identify and analyze patterns that favor the occurrence of harmful organisms in order to develop effective counterstrategies in pasture management.

3. Optimization of cattle grazing of grasslands, as environmental factors can also be related to plant traits with pattern mining. Animal specific factory can be included if necessary.

4. Optimization of organic fertilization on extensive areas (also sub-area specific) in order to harvest high yields for food purposes on the one hand, but not to endanger biodiversity on the other hand.

5. Identification of limitations and disadvantages of pattern mining and to adapt the algorithms accordingly.

6. Combine expert knowledge (farmers, consultants, scientistsn and other stakeholders) with data driven algorithms to enhance Grassland Sciences.

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