The Fertilizer Recommendation Support Tool (FRST) will perform correlations between soil nutrient concentrations and crop response to fertilization from user-selected datasets in the FRST national database. Yield response for the nutrient of interest in a particular site-year is presented as relative yield (RY), a ratio of unfertilized yield to the maximum attainable yield (A). Several methods exist in the literature for estimating A and calculating RY but the effect of method choice on soil test correlation outcomes is undocumented. We used six published methods to calculate RY from site-year yield data for five published correlation datasets, and fit a generalized linear plateau (LP) model to each. The critical soil test value (at the LP join point) and RY intercept coefficients were not significantly affected by RY method for any of the datasets, and RY plateau was significantly affected by method for only one dataset. The top options after robust group discussions were the so-called MAX and FITMAX methods. We selected the MAX method, which defines A as the numerically highest treatment yield mean, as the most appropriate method for FRST because MAX represents maximal yield in responsive sites, is inclusive of trial data having a range of treatment numbers, limits RY to 100% (which allows options for transforming data), and is simpler to implement than FITMAX, which requires a decision tree to calculate RY for diverse trials.
|Journal||Soil Science Society of America Journal|
|State||Published - Sep 1 2022|
Bibliographical noteFunding Information:
We thank the source funding the FRST initiative: the USDA-ARS National Programs for Natural Resources and Sustainable Agricultural Systems (Grant 58-8070-8-016) and the USDA-NRCS (NR203A7500010C00C). We also appreciate early counsel from Peter Scharf, Professor Emeritus at the University of Missouri-Columbia, regarding dataset and modeling considerations.
We thank the source funding the FRST initiative: the USDA‐ARS National Programs for Natural Resources and Sustainable Agricultural Systems (Grant 58‐8070‐8‐016) and the USDA‐NRCS (NR203A7500010C00C). We also appreciate early counsel from Peter Scharf, Professor Emeritus at the University of Missouri‐Columbia, regarding dataset and modeling considerations.
© 2022 The Authors. Soil Science Society of America Journal published by Wiley Periodicals LLC on behalf of Soil Science Society of America.
ASJC Scopus subject areas
- Soil Science