Soil-test correlation and calibration data are essential to modern agriculture, and their continued relevance is underscored by the expansion of precision farming and the persistence of sustainable soil management priorities. In support of transparent, science-based fertilizer recommendations, we seek to establish a core set of required and recommended information for soil-test P and K correlation and calibration studies, a minimum dataset, building on previous research. The Fertilizer Recommendation Support Tool (FRST) project team and collaborators are developing a national database that will support a soil-test-based nutrient management decision aid tool. The FRST team includes over 80 scientists from 37 land-grant universities, two state universities, one private university, three federal agencies, two private not-for-profit organizations, and one state department of agriculture. The minimum dataset committee developed and vetted a robust set of factors fo minimum dataset consideration that includes information on soil sample collection and processing, soil chemical and physical properties, experimental design and statistical analyses, and metadata

As part of the Fertilizer Recommendation Support Tool (FRST) project, the FRST database was developed to consolidate and preserve U.S. soil test correlation and calibration data. Legacy phosphorus (P) and potassium (K) soil test data that met a minimum requirement were included in the database. The FRST database initially included over 1,200 individual trials from a range of years, cropping systems, geographic regions, and management practices. The FRST database is being migrated from a Microsoft Excel spreadsheet to a relational database format housed within the USDA‐ARS Agricultural Collaborative Research Outcomes System (AgCROS) to be accessed via the online FRST decision support tool. Data will be continually added to the FRST database through an online submission form following peer review by the FRST team. The FRST database and associated decision support tool will aid researchers, extension associates, consultants, and farmers in improving fertilizer recommendations for crops across the United States.

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.

Managing a sustainable dairy farm requires balancing phosphorus (P) imports and exports that enter and leave through the farm gate. Over the long term, P surpluses will elevate soil‐test P concentrations above crop requirements through routine land applications of manure. The objectives of this study were aimed at Virginia dairy farms (a) to determine P mass balances, (b) to define potential guidelines for a sustainable and feasible zone of operation based on P balance and P use efficiency, and (c) to assess risk factors driving P surplus and P use inefficiencies. Data on farm‐gate P imports and exports via feed, manure, crops, fertilizers, bedding, animals, and milk were collected for 58 dairy farms in Virginia. There was no relationship between farm P balance and milk production, indicating that a P surplus was not necessary for good milk productivity. A feasible P balance limit was calculated below which 75% of farms could operate, and this was 18.7 kg P ha−1. Two risk factors were identified for farms having a P balance above this limit: (a) land application of poultry litter and (b) excessive import of P through feed. Combined dairy and beef operations generally had more land and a lower P balance, whereas having combined dairy and poultry did not raise the P balance as long as poultry litter was exported. Dairy farms in Virginia can operate with a sustainable P balance as long as they avoid using excessive poultry litter and pay attention to P imported through purchased feed.