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An algorithm to fit boundary lines, using cubic smoothing splines, was written and used to identify yield responses to changes in soil properties. This method involves fitting a curve that represents the maximum yield response to each predictor value, which represents the yield potential at each soil property value. Boundary-line yield responses to individual soil properties were found to differ from responses found by fitting curves through the data scatter. The effects of correlated variables appeared to be lessened using the boundary line approach. Multivariate boundary-line models, based on the Law of the Minimum, were found to be useful for the identification of site-specific causes of yield variation and yield potentials. The boundary line was found to be a useful complement to more traditional data analysis techniques.

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