Abstract

The technologies of precision agriculture were developed for application to site-specific crop management. Some of them require a high capital outlay, but two key component technologies, spatial analysis and global positioning systems, may both be obtained at relatively low cost. These technologies may be used profitably to improve crop management practices without the expenditures necessary for a full site-specific management program. In this paper we use exploratory spatial data analysis to study georeferenced rice production data collected on the farms of a group of Uruguayan rice growers. The objective was to identify the management practices that most distinguish farmers producing high yields from those producing low yields. A key challenge was to distinguish those differences in farmers’ management practices that were due to their different approaches to farming from those that were due to their responses to differences in the land quality of their individual fields. Using a combination of classification and regression trees and graphical analysis, the most distinguishing factors were identified to be early planting, adequate fertilization, and effective irrigation.

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