Understanding the Effects of Cover Crops and Nutrient Management on Microbial Carbon Use Efficiency and Nitrogen Mineralization

Study site  

The experimental sites were in three regions across Pennsylvania: Northumberland-Lycoming, Lancaster, and Centre counties that comprises 4 on-farm locations (Figure 1). Two sites were on commercial organic farms, and one was at the Russell E. Larson Agricultural Research Center. The climate in Pennsylvania is warm and humid during summer, where most of the corn production does not require irrigation. Average air temperature and cumulative precipitation were calculated for April to October for the experimental sites. The time frame selected corresponds to the corn growing season in Pennsylvania. Detailed site descriptions are provided in Table 1. The weather information was retrieved from the National Oceanic and Atmospheric Administration (NOAA) database and the National Weather and Climate Center of USDA-NRCS.

Table 1.  Environmental and soil conditions of farm locations in Pennsylvania  

^{* Average air temperature and cumulative precipitation were calculated for April to October, corresponding to the corn growing season in Pennsylvania.} 

Experimental design   

The experimental design was a Randomized Complete Block Design with four replicate blocks. The experimental design for this study started with selecting and managing cover crops at each site. On the commercial farms, farmer-collaborators chose the cover crop treatments for each year, while the research station experiment utilized a subset of three treatments from a larger group of 12, including a no-cover crop control. Specific details about the cover crop types used in the study are outlined below and summarized in Table 2. Cover crops were planted in the fall and terminated in the spring, with the exception of Northumberland in 2021. 

The size of the N rate plots differed by location. At the research station, plots were 9 meters long and 4 meters wide with a 1.5-meter buffer zone, whereas at the on-farm sites, plots measured 15 meters in length and 5 meters in width, with buffer zones of 2.5 meters. The six N-levels were established as 0, 30, 60, 120, and 240 lb N/ac. Although experimental fields were divided into six N-levels for the N decision-support tool assessment, to complete the objectives of this proposal, were considered only 0, 120, and 240 lb N/ac treatments. For yield response analysis, the variety among N additions between sites was evaluated through a regression model. Because the on-farm trials are under organic production, N additions were performed using Chilean Nitrate fertilizer, a naturally occurring mineral N source allowed in organic production.  Because Chilean nitrate is a mineral source of nitrogen (sodium nitrate), results from the study can also be extrapolated to conventional farmers that use mineral fertilizers such as urea and urea-ammonium-nitrate solution. Response to nutrient management with fertilizer additions were compared to on-farm nutrient management practices (with four external experimental plots at each side of the experimental fields), according to the manure applications performed by farmers.  

Table 2. Cover crop treatments,  termination dates and fertilization dates  for experimental sites  

  ^{† FR, forage radish (Raphanus sativus L.); OA, oat (Avena sativa L.); RC, red clover (Trifolium pratense L.); CC, crimson clover (Trifolium incarnatum L. ‘Dixie’); RG, annual ryegrass (Lolium multiflorum Lam.); SB, soybean [Glycine max (L.) Merr.]; TR, triticale (× Triticosecale Wittm. ex A.); WH, wheat (Triticum aestivum); WP, winter pea (Pisum sativum)}

Soil sampling   

To accomplish the soil analysis related to the objectives of this study, soil samples were collected three times per year: before cover crop termination (baseline), during early corn growth (around V6 stage), and near corn harvest (Figure 2). Fifteen soil cores (1.9 cm diameter, 0-20 cm depth) were taken from random spots in each plot and combined into a composite sample. For analysis, 10 g of soil was extracted using 2M KCl and nitrate (NO3-) and ammonium (NH4+) were measured by Flow Injection Analysis (FIA). Another subsample was dried, ground, and sieved for further analysis. Total soil organic carbon (SOC) and nitrogen were determined by dry combustion. Baseline fertility tests measured P, K, Ca, Mg, S, Zn, and Cu using the Mehlich-3 method and inductively coupled plasma optical emission spectrometry (ICP-OES). Soil pH was measured in a 1:1 soil-water mixture, cation exchange capacity (CEC) was calculated from the Mehlich-3 extract, and soil texture was determined by the hydrometer method.

Cover crop biomass (Objective 1) 

Cover crop biomass was measured in the spring just before termination, and for the Lancaster County farm in 2022, it was also measured in the fall when peak growth occurred, as the mix included species that die over winter. Biomass was collected by cutting the aboveground plants at soil level from two randomly selected small areas (0.25 m²) in each plot (Figure 3). The plant material was dried in an oven at 65°C for at least two weeks before the dry weight was recorded. The nitrogen content of the biomass was calculated by multiplying the total dry biomass (kg/ha) by the nitrogen concentration, which was determined through lab analysis. 

Estimation of microbial carbon use efficiency (Objective 1 & 2) 

Microbial carbon use efficiency (CUE) and nitrogen mineralization were assessed using the buried litterbag technique. Litterbags, containing 5 grams of air-dried cover crop litter with varying C:N ratios (details in Table 3), were buried 10 cm deep in plots at the time of N fertilizer application, four weeks after corn planting (Figure 4). The litter was collected from field sites before termination, and the C and N concentrations were measured using dry combustion analysis. Each experimental plot received litterbags corresponding to three nitrogen rates: 0, 120, and 240 lb N/ac. Five litterbags for each C:N ratio were buried in each plot and periodically removed throughout the growing season. This allowed for tracking N release from the litter over time. Litterbags were rinsed at the start to account for leaching of soluble components, ensuring that measurements reflected the more stable fractions of biomass. The decomposition data were used to model CUE using the equation from Manzoni et al. (2008), which separates the effects of leaching and microbial processing on C and N losses.  

Although the first method to evaluate microbial CUE was completed, the second procedure proposed in this study is still in progress. Briefly, soil samples were incubated for 5 days at 15°C before analysis. The 18O-water tracing method uses 18O-labeled water incorporated into microbial DNA to calculate total microbial growth and then microbial CUE. A subsample of soil (0.25 g) was labeled with 18O water to reach 20.0% 18O in the final soil water content. Samples were placed in vials to incubate at 15°C for up to 48 hours, during which microbial respiration was measured. After the incubation, a 1 mL gas sample was taken to determine CO2 concentration with a LICOR-7100 infrared gas analyzer. Soil was frozen at –20°C until DNA extraction. DNA extraction was conducted using a kit and following the manufacturer’s protocol (n=288). DNA samples were dried and sent to a lab facility for δ18O quantification. We are currently waiting to have this information to proceed with further steps. Cumulative respiration data described above will be used for the calculation of CUE with 18O-water according to Spohn et al. (2016b). 

Microbial communities (Objective 2) 

Phospholipid fatty acid (PLFA) analysis was conducted in July 2024 at a third-party lab on samples from the 2022 experiments, along with 10 samples from 2021 for cross-comparison. A preliminary analysis is included in this report. The Next Generation Sequencing (NGS) analysis, performed on 2021 samples, assessed the size, composition, and structure of the soil microbial community. DNA was extracted, and PCR targeted the amoA gene for nitrification potential, the V3 region of the 16S rRNA for bacteria, and the ITS1 region for fungi. Amplicon sequencing and bioinformatics was conducted at Penn State.  

Agronomic measurements (Objective 3 & 4) 

After corn reached maturity, yields at the commercial farm locations were measured by harvesting two rows, each five meters long. The plants were cut above the brace roots, with ears separated from the rest of the biomass. The ears were weighed, and a subsample of three ears per plot was analyzed for moisture content and shell-out percentage, allowing conversion of fresh ear weight to grain weight at 15.5% moisture. At the research station, corn was harvested using a small plot combined that measured grain weight and moisture content with an onboard scale and sensor. 

An ANOVA was performed to identify outliers, using studentized residuals beyond ±2.5. An F-test (α = 0.10) was used to determine if the experiment was responsive to nitrogen (N) additions. If significant, a quadratic plus plateau model was applied to find the optimal N rate. The significance of the linear and quadratic terms was used to evaluate the N response. If the F-test showed significance but no visible response was apparent, least squares means were checked to see if the zero N treatment was significantly lower than other N levels. If not, the site was classified as non-responsive, following White et al. (2024) for recalibrating the pre-sidedress nitrate test (PSNT). 

N recommendation model (Objective 3 & 4)  

To improve nitrogen (N) fertilizer recommendations for corn, we adapted a biogeochemical model from Arrington et al. (2024), which is used in White et al.'s (2024) N fertilizer decision tool. The model takes into account N contributions from decomposing cover crops and the breakdown of soil organic matter. It includes microbial processes, considering microbial carbon use efficiency (CUE) and the C:N ratio between microbes and their food. Microbial CUE is based on soil texture (sand and clay content) and is averaged over the growing season. The model predicts corn yields without fertilizer by using N from the soil and cover crops, and the difference between this unfertilized yield and potential yield helps determine the N fertilizer recommendation. We modified the tool to factor in soil texture, C concentration, and C:N ratio, along with site-specific microbial CUE from litterbag decomposition, and compared these N recommendations to the agronomic optimum N rate for each site.