Location: Food Animal Environmental Systems Research
Title: A spreadsheet for determining critical soil test values using the modified arcsine-log calibration curveAuthor
Bolster, Carl | |
CORRENDO, ADRIAN - Kansas State University | |
PEARCE, AUSTIN - North Carolina State University | |
SPARGO, JOHN - Pennsylvania State University | |
OSMOND, DEANNA - North Carolina State University | |
SLATON, NATHAN - University Of Arkansas |
Submitted to: Soil Science Society of America Annual Meeting
Publication Type: Abstract Only Publication Acceptance Date: 8/29/2022 Publication Date: 11/9/2022 Citation: Bolster, C.H., Correndo, A.A., Pearce, A., Spargo, J., Osmond, D., Slaton, N. 2022. A spreadsheet for determining critical soil test values using the modified arcsine-log calibration curve. Soil Science Society of America Annual Meeting. https://scisoc.confex.com/scisoc/2022am/meetingapp.cgi/Day/2022-11-06. Interpretive Summary: Technical 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 which are not 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 values 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. |