A spreadsheet for determining critical soil test values using the modified arcsine-log calibration curve

Abstract

Soil test correlation data are often used to identify a critical soil test value (CSTV), above which crop response to added fertilizer is not expected. Oftentimes, models are used to determine the CSTV from soil test correlation data, yet most commonly used models have inherent assumptions that may not be valid for these data. The arcsine-log calibration curve (ALCC) was developed in response to the statistical limitations of other commonly used models. A modified ALCC model using standardized major axis regression further improves this model's applicability to soil test correlation data. Here, we describe a Microsoft Excel spreadsheet for calculating CSTV from soil test correlation data using the modified ALCC model. The spreadsheet is available for download providing an accessible and easy-to-use tool for those who would like to use this method but who lack the experience with more sophisticated coding programs. The spreadsheet is available for download at http://www.ars.usda.gov/ALCC.