TY - JOUR
T1 - The soiltestcorr R package
T2 - An accessible framework for reproducible correlation analysis of crop yield and soil test data
AU - Correndo, Adrian A.
AU - Pearce, Austin
AU - Bolster, Carl H.
AU - Spargo, John T.
AU - Osmond, Deanna
AU - Ciampitti, Ignacio A.
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2023/2
Y1 - 2023/2
N2 - The soiltestcorr R package is an open-source software designed to enable accessible and reproducible computation of correlation analyses between crop yield response to fertilization and soil test values. The package compiles a series of functions for analyzing soil test correlation data: (i) Cate & Nelson data partitioning procedure (graphical and statistical versions), (ii) nonlinear regression analysis (linear-plateau, quadratic-plateau, and Mitscherlich-type exponential models), and (iii) the modified arcsine-log calibration curve. The soiltestcorr enables users to correlate crop response to soil nutrient availability and estimate a critical soil test value and visualize results with ggplot without requiring advanced R programming skills. Finally, a web application that facilitates the use of the package is also offered for users with no background in R programming.
AB - The soiltestcorr R package is an open-source software designed to enable accessible and reproducible computation of correlation analyses between crop yield response to fertilization and soil test values. The package compiles a series of functions for analyzing soil test correlation data: (i) Cate & Nelson data partitioning procedure (graphical and statistical versions), (ii) nonlinear regression analysis (linear-plateau, quadratic-plateau, and Mitscherlich-type exponential models), and (iii) the modified arcsine-log calibration curve. The soiltestcorr enables users to correlate crop response to soil nutrient availability and estimate a critical soil test value and visualize results with ggplot without requiring advanced R programming skills. Finally, a web application that facilitates the use of the package is also offered for users with no background in R programming.
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U2 - 10.1016/j.softx.2022.101275
DO - 10.1016/j.softx.2022.101275
M3 - Article
AN - SCOPUS:85144020838
SN - 2352-7110
VL - 21
JO - SoftwareX
JF - SoftwareX
M1 - 101275
ER -