Abstract

Zoning of agricultural fields is an important task for utilization of precision farming technology. A method based on fuzzy indicator model theory for definition of zones with different levels of productivity is considered. Fuzzy indicator model for identification of zones with different levels of productivity is based on two general types of fuzzy indicators: the individual fuzzy indicator (IFI) type and the combined fuzzy indicator (CFI) type. IFIs are defined as a number in the range from 0 to 1, which reflect an expert concept and are modeled by an appropriate membership function. CFI is defined using fuzzy aggregated operations. The theoretical considerations are illustrated with this example based on data collected from a precision agriculture study in central Texas, USA. Soil samples were collected at different points, taking into account the actual longitude and latitude for each of these points. Because the experimental data (as in many cases) contained information only about a limited number of parameters, the calculations were restricted in this study. In this study, the parameters grain yield, total carbon (C), total nitrogen (N), and available phosphorus (P) were utilized. Using the author’s computer program, fuzzy indicators IFI/CFI was calculated for each zone separately. Utilizing results of calculations maps of zones with different levels of productivity were built.

This work is licensed under a Creative Commons Attribution 4.0 License.