The amount of soil organic matter (SOM) is considered a key indicator of soil properties associated with higher fertility. Despite the ubiquity of assumptions surrounding SOM’s contributions to soil functioning, we lack quantitative relationships between SOM and yield outcomes on working farms. We quantified the relationship between SOM and yields of corn (Zea mays L.) and silage for a dataset of 170 fields arrayed across 49 farms in a network of growers based in Wisconsin and Minnesota, USA. As SOM concentrations increase, so do yields, though gains start to level off around 4% SOM. When examining the relationship between yield and soil health indicators representative of biologically active carbon pools, we found that mineralizable carbon (min-C) has a stronger relationship with yield than permanganate oxidizable C (POXC). Mineral fertilizer, manure, and SOM had relationships of similar magnitude with yield, highlighting that SOM in combination with exogenous inputs likely plays an important role in driving agricultural productivity in this region. An SOM by crop rotation interaction indicated that the impact of SOM on crop yields varied depending on rotation (continuous corn versus corn in rotation). That is, continuous corn had lower yields than corn in rotation despite higher SOM concentrations. Our findings provide insight into the relationship between indicators of soil health, farm management, and crop yields for a set of working farms and lend support to the goals of soil health initiatives that rest on building SOM in agricultural soils to improve agricultural outcomes.

Soil samples were collected across farm fields across Wisconsin and Minnesota across the years 2015, 2016, and 2017. Agronomic data were collected through interviews with participating farmers and were collected for each field. Field sampling of soils and yield was carried out within an 80-m² area on each farm. Yield data was determined as grain yield (n = 99) or silage yield (n = 71) based on how the field was to be harvested. For both silage and grain, yield data was collected by hand from three separate row lengths and harvested from a length of 3 m per row. Silage was cut 22.86 cm (9 inches) above the ground. The three areas for hand harvest were located by selecting three 3-m replicates that were from different rows within the sampling area and were staggered lengthwise. Replicates were selected to be representative of the sampling area. The three yield samples were aggregated to produce one yield estimate per field. Yield data contained both yields of grain (at 15.5% moisture) and silage (at 65% moisture), so conversion factors specific to Wisconsin were used to convert grain yield to silage yield (Lauer 2006). We then converted silage yields (tons per acre) to metric units (megagrams per hectare) by multiplying silage yields by 2.242. 

Soil series, texture class, drainage class and slope class information was collected for each sampling area during the year of data collection using GPS coordinates and the NRCS SSURGO database via the SoilWeb soil survey browser developed by the California Soil Resources Lab at the University of California-Davis. 

All fields were planted into corn the season soil samples were collected. Soil samples were also collected from within the same 80-m² area as yield data collection. In each area, three composite soil samples that each consisted of five soil cores were taken from a depth of 0 to 15 cm using a probe with an internal diameter of 2.5 cm. The soil samples collected from Minnesota fields were extracted to the same depth of 15 cm with a 3-inch diameter bulb planter and each composite soil sample consisted of five to 15 cores depending on the field size. 

Lab analysis for POXC and min-C followed established laboratory methods (see accompanying paper for specifics). Additional soil analyses (pH and SOM) were performed according to methods prescribed by Wisconsin’s agricultural department and standardized across Certified Soil Testing Laboratories across the state.

This dataset is comprised of two tabs in a single excel file. See the "metadata" tab for information pertaining to the variables measured and analyzed. The "data" tab includes measured field and lab data as well as extracted data from SSURGO.