Winter cover crops play a dual role in agricultural N management. They can scavenge soil residual N during the winter fallow period and supply N to the succeeding main crop following termination. Cover crops also provide many other ecosystem services including improved soil aggregate stability, soil carbon (C) sequestration, reduced erosion and runoff losses, and weed suppression. Despite their ability to provide many agroecosystem services, cover crops are planted on less than 1% of US cropland. Increased costs, minimal yield benefits, and the perception among farmers that benefits from cover crops accrue slowly are some of the major barriers for cover crop adoption.
In the state of Maryland, the adoption of winter cover crops is very high due to the Maryland Cover Crop Program (MCCP), which provides farmers with incentives to help offset cover crop expenses. The main goal of the MCCP is to enhance soil N scavenging and reduce nitrate (NO3–) loading into the Chesapeake Bay; the impact of cover crops on N cycling in the subsequent cash crop is not emphasized by the program. Farmers are aware that grass cover crops increase N fertilizer requirements due to N immobilization. However, farmers may not know how much N is being released or immobilized by their cover crops and end up applying more or less fertilizer than required by the succeeding main crop. Over-application undermines the goals of MCCP, while under-application may reduce yields and discourage future cover crop use. Thus, it is critical to adjust N fertilizer application based on N availability from cover crop residue decomposition to optimize N use efficiency and corn (Zea mays L.) performance.
The large variability in climate between years and among farms makes it difficult to accurately assess soil N availability from cover crop surface residues. Climate has a strong effect on residue decomposition, with decay rates accelerating proportionately with increasing soil moisture and temperature. Previous cover crop decomposition studies in the region were used to validate an existing N management decision support tool. It was observed that the existing tool often do not accurately predict soil N availability from surface residues. Model performance has been influenced by fluctuations in moisture and temperature at the soil surface. The soil environment has much lower fluctuations in moisture and temperature, key factors in driving decomposition. This projects aims to understand N mineralization kinetics from surface-applied cover crop residues in controlled laboratory conditions and improve the performance of existing decision support tool to accurately predict N availability from surface-applied cover crop residues in no-till corn systems.
Corn is the most common cash crop in the US, with high N demand and relatively low N use efficiency. Thus, there has been interest in improving N management in corn systems. Using data from on-farm and controlled laboratory experiments, this project aims to extend the applicability of the existing decision support tool to better manage N in cover crop based no-till corn systems. Finally, this project will likely contribute to the increased adoption of cover crops in the mid-Atlantic US as more farmers and agricultural professionals become proficient in the use of this new decision support tool. Therefore, findings from this project not only impact the performance of cover crop-based no-till corn systems at the farm level, but also support the goals of the MCCP and NE-SARE through increased cover crop adoption at the state and regional levels, respectively.
The specific objectives of the proposed project are to:The specific objectives of the proposed project are to:
(1) Assess the ability of cover crops to scavenge soil N. I hypothesize that soil N scavenging by cereal cover crops will be higher under conditions that favor high drainage (i.e. coarse-textured soils and high rainfall areas).
(2) Determine how cover crops affect N availability to the succeeding corn in no-till cropping systems. I hypothesize that the net effect of cover crops on soil N availability depends on cover crop species, growth stage, quality at termination, soil type, and climatic conditions during the corn phase.
(3) Determine the interactive effect of soil moisture and temperature on soil N availability from surface-applied cover crop residues. I hypothesize that soil N availability from surface-applied cover crop residue decomposition will increase with increasing soil moisture and temperature.
(4) Assess the effects of cover crops on no-till corn yields. I hypothesize that cover crops will have neutral or positive effects on no-till corn yields.
(5) Evaluate and improve the accuracy of the existing Cover Crop Nitrogen Calculator tool in predicting soil N availability from surface-mulched cover crop residues in no-till corn systems. I will use data from multi-farm experiments (Objective 2) to evaluate the accuracy of the calculator and improve it using data from controlled laboratory experiments (Objective 3).
Objectives (1-2) and (4-5) are components of larger study design aimed at understanding the economic and environmental services of winter cover crops in the mid-Atlantic US (Maryland, Pennsylvania, North Carolina, South Carolina, and Georgia). These objectives will be better addressed by including as many farms as possible with wider soil types and climates. On-farm experiments will be conducted on at least 75-80 farms across the mid-Atlantic US; the majority of these on-farm experiments will be funded from the NRCS-CIG. The NE-SARE Graduate Student Grant will be used to cover part of the expenses in conducting on-farm experiments on 15 sites located at Maryland and Pennsylvania. Based on previous work from Dr. Mirsky’s lab, it is evident that the existing tools do not accurately predict soil N availability from surface residues due to great fluctuations in moisture and temperature . Therefore, controlled microcosm studies (Objective 3) are needed to parameterize and improve the accuracy of existing tools for use in cover crop based no-till corn systems (Objective 4). I will explicitly use the NE-SARE Graduate Research Grant to conduct laboratory microcosm studies to answer Objective 3.
Winter cover crops play a critical role in nitrogen (N) management, both as N scavenger while growing and as N supplier to the succeeding main crop while decomposing. Many farmers believe non-legume cover crops immobilize soil N and make it less available to the main crop, while legume cover crops supply N to the main crop during decomposition. However, they often do not know how much N is being immobilized or released by their cover crops. Farmers, therefore, find it very difficult to manage N for the succeeding main crop. Although few decision support tools such as Cover Crop Nitrogen Calculator are available, they often do not accurately predict soil N availability from surface-mulched residues. In this project, I propose to assess the performance of winter cover crops in the mid-Atlantic US, their impact on soil N scavenging, soil N availability, and no-till corn yields, and improve the performance of existing tools in predicting soil N availability from surface-mulched residues in no-till corn (Zea mays L.) systems. This research will be conducted on 35-40 farms across mid-Atlantic US and laid out in strip corn plots with and without cover crops. By the end of this project, farmers will benefit from an improved decision support tool, which they can use to adjust N fertilizer requirements and mange N effectively in cover crop based no-till corn systems. This will lead to increased adoption of cover crops and improved agricultural sustainability.
Objectives (1-2) and (4-5): These objectives will be addressed by conducting multiple on-farm experiments across the mid-Atlantic US. Experiments will be conducted in separate fields each year to demonstrate the short-term benefits of cover crops on soil N scavenging and soil N availability in no-till corn systems. The experiment will be established as a strip-plot design with and without cover crops. There will be two sub-plots within each strip-plot. Data on cover crop biomass, residue quality, soil N scavenging, soil N availability from residue decomposition, and corn yields will be collected.
Farmers and extension agents will be directly involved in this project. With the help of county extension agents, I will contact the farmer-collaborators with a project description and request for their participation. Farmers will manage both cover crops and the subsequent corn crop. Farmers will make all farm management decisions including cover crop species, planting and termination methods/timings, fertilization, and irrigation. Growers will be required to either not plant a cover crop in the no cover crop control strips or spray with a herbicide ~10 days after planting. Since we will not dictate farmers’ management, this experiment will permit us to examine the short-term benefits of cover crops under a wide range of soil types, climatic conditions, and management practices. If required, assistance will be provided to farmers in developing the no cover crop strips (i.e., transport UTV mounted herbicide sprayer for cover crop termination).
Data Collection: At all farm sites, cover crop biomass will be sampled from two separate m2 quadrants in each subplot in the spring prior to termination. The fresh weight of cover crop biomass will be recorded and used to construct cover crop litter bags to assess their decomposition kinetics (see Objective 2 below). A subset of this sample will be weighed fresh and then oven-dried at 60°C and dry weight recorded. The biomass samples will be mechanically ground and analyzed for C and N concentrations using CN elemental analyzer (Leco TruMac CN, St. Joseph, MI). A subsample will be sent to the University of Georgia analytical laboratory to determine the residue quality (cellulose, hemi-cellulose, and lignin content) using near-infrared spectroscopy (NIRS).
To address Objective 1, I will collect deep soil core samples (0-100 cm) each fall before cover crop planting and each spring after cover crop termination across all farms. Four deep soil cores will be sampled per subplot using a hydraulic soil probe, transferred immediately into the cooler, and stored in freezer at -18°C until further processing. During processing, all four soil cores from each subplot will be composited and homogenized into 0-30 cm, 30-60 cm, and 60-100 cm depth increments. Subsamples will be taken from composited soils and oven-dried at 105°C for 48 hours to determine the moisture content. The remaining composited sample will be air-dried and ground to pass through a 2-mm sieve before analysis. Approximately 2.0 g of finely ground soil will be extracted with 20 mL of 2M KCl solution and analyzed for inorganic N (NH4+-N and NO3–-N) concentrations using LACHAT QuikChem 8500 series (Hach Co., Loveland, OH). The total N contents in the soil profile in the fall (before cover crop planting) and spring (after cover crop termination) will be compared to determine the ability of cover crops to scavenge soil N in the winter.
Objective 2 will be addressed by conducting residue litter bag studies in which the amount of cover crop biomass and N remaining in the litter bags will be tracked over time. The dimension of each litter bag is 60 by 26 cm. I will prepare residue litter bags using the fresh biomass sampled from each subplot. There will be two sets of six litter bags to examine decomposition kinetics of cover crop surface residues in each subplot. Fresh weight of cover crop biomass will be evenly distributed within the litter bags. Out of six bags, one bag will be sampled on the same day as termination. The remaining five bags will be deployed on the soil surface in between corn rows using landscape staples. The leftover litter bags will be retrieved over time after 2, 2, 3, 4, and 4 weeks of termination to determine mass loss on an ash-free basis. Upon retrieval, the litter bags along with biomass will be oven-dried at 60°C for two weeks, and the dry weight recorded. The oven-dried biomass will then be ground and a subsample will be analyzed for C and N concentrations using a CN elemental analyzer (Leco TruMac CN, St. Joseph, MI). Data on cover crop biomass and C and N content will be used to fit cover crop decay and N release curves for each site.
To address Objective 3, I will conduct laboratory microcosm experiments in temperature-controlled growth chambers at three different temperatures (15, 25, and 35 ˚C) and five different water potential regimes (-5.0, -1.5, -0.5, and -0.03 MPa). Microcosms of soil with surface-applied cover crop residues will be prepared and incubated in a dynamic-flow through system. There will be four cover crop treatments: (a) early kill cereal rye (Secale cereale L.), (b) late kill cereal rye, (c) crimson clover (Trifolium incarnatum L.), and (d) a control treatment (soil without residue). The incubation will last for 120 days. Three replicates of each treatment combination will be destructively sampled at 0, 15, 30, 60, 90, and 120 days to determine N mineralized over time. In total, I will prepare 720 microcosms (4 cover crop treatments × 3 temperatures × 4 moisture regimes × 5 destructive sampling days × 3 replicates).
Microcosm preparation and data collection: Surface soil (0-15 cm) will be collected from one of the no-till corn production field at Beltsville Agricultural Research Center (BARC) (Beltsville, MD), air-dried, and then ground to pass through a 2-mm sieve before use. Each microcosm will contain 100 g of air-dried soil moistened to appropriate water potential regimes. Characteristic moisture content and water potential relationships will be first developed for both soil and cover crop residues to determine the amount of water that needs to be added in each microcosm. Before adding cover crop residues, microcosms without cover crop residues will be pre-incubated for a week at respective temperature and water potential regimes. One set of microcosms will be prepared for carbon dioxide (CO2) measurements throughout the incubation period. These microcosms will be transferred into mason jars fitted with butyl rubber septa on each gas sampling day for one hour. The remaining sets of microcosms will be destructively sampled over time and then extracted with 2M potassium chloride (KCl) solutions to measure inorganic N (NH4+-N and NO3–-N) concentrations using LACHAT QuikChem 8500 series (Hach Co., Loveland, OH). Data on C and N mineralization will be used to fit decay curves for each of the three different cover crop residues.
To address Objective 5, corn ears will be hand-harvested in both cover and no cover crop strips from the center two rows of each subplot. The ears will be shelled after oven-drying at 60°C for two weeks and then weighed for grain yields. The grain yields will be adjusted to 14% moisture content before reporting. Differences in corn grain yields between bare fallow and cover crop plots will be linked to cover crop biomass and residue quality, soil, environmental, and management factors to identify the impact of cover crops on corn grain yields.
To evaluate the performance of the UGA Cover Crop Nitrogen Availability Calculator (Objective 5) in predicting soil N availability from surface-mulched cover crop residue decomposition in no-till corn systems, I will compare the modeled soil N availability data with the measured N release data from litter bag studies (Objective 2). The soil N availability from cover crop residues decomposition in no-till corn systems will be modeled using UGA Cover Crop Nitrogen Availability Calculator. This calculator is based on the Crop Environmental Resource Synthesis (CERES-N) model, a well-known model that has been successfully proven to predict C and N mineralization from incorporated cover crop residues. The calculator requires data on cover crop biomass, residue quality (percent N, soluble carbohydrates, cellulose, and lignin content), and climate (surface soil moisture content and temperature) to predict the timing and amount of N released. Data on cover crop biomass and residue quality will be measured at termination. Surface soil (0-5 cm) moisture content and temperature at the residue-soil interface will be continuously monitored and recorded throughout the corn growing season using CS655 soil water content reflectometer (Campbell Scientific, Inc., Logan, UT) and DS18B20 digital thermometer (Maxim Integrated Products, Inc., San Jose, CA), respectively. Based on past research, it is evident that these dynamic simulation models do not accurately predict soil N availability from surface-mulched residue decomposition because temperature and moisture fluctuate greatly in surface mulches . I will use the data collected from controlled laboratory incubation experiments (Objective 3) to validate and refine the parameters of the CERES-N model and consequently the Cover Crop N Availability Calculator tool for use in no-till corn systems with surface-mulched cover crop residues.
I am processing my soil and biomass samples. The litter bag decomposition assay samples were partially analyzed, data from which have been presented in the 2018 ASA-CSSA-CSA and 2018 NorthEast Cover Crop Council (NECCC) conferences held at Baltimore and Pennsylvania, respectively. The soil cores were collected in the fall at the time of cover crop planting and again in the spring at the time of cover crop termination from this participating farms. I am currently processing the litter bag samples collected during the 2018 on-farm study.
The preliminary incubation experiment designed to determine the lower water potential limit at which the microbial activity (hence, cover crop decomposition) ceases has been successfully completed. Based on the results from preliminary incubation experiment, I determined the water potential range for the full factorial cover crop decomposition experiment designed under controlled laboratory conditions. The full factorial laboratory experiment (objective 3) has been completed. I have already analyzed the headspace gas samples to determine the rate of cover crop decomposition. The destructive soil samples were extracted with 1 M KCl to extract inorganic N which was then analyzed colorometrically via LACHAT analyzer. I will organize the data, analyze it, and present the findings in my next report submission. The data from this incubation experiment will also be used to validate and parameterize the Cover Crop N Calculator which is based on CERES-N model.
Education & Outreach Activities and Participation Summary
I conducted a workshop/ field day in Kent county UMD extension office, Eastern MD. Around 40 farmers participated in the workshop where I laid out the objectives of this on-farm research. I demonstrated the methodology of biomass sampling, soil core sampling, cover crop decomposition assay using nylon litter bag, and soil water monitoring using the custom-developed soil water sensors. Many farmers in the workshop were already involved in our research. Some of the farmers who were new to us showed great interest to be the part of our project. They were highly interested in our project. We are going to facilitate our on-farm effort in their farms in this upcoming year.
During the 2018 ASA-SSSA-CSA tri-society meeting, the organic and cover crop societies conducted a field day at the USDA Beltsville Agricultural Research Center (BARC) research farms at Beltsville, MD. We had more than 100 participants in this field day; including farmers, researchers, ag. professionals, and extension agents. During this on-farm demonstration, I got an opportunity to talk about my on-farm research. I demonstrated the use of litter bag to assess cover crop decomposition, and the use of custom-developed soil water sensor technology for monitoring the soil water in systems with and without cover crops.
During the 2018 ASA-SSSA-CSA tri-society meeting at Baltimore, MD, I presented two oral talks and showcased one poster. My oral talks were:
1. Cover crop decomposition in no-till corn systems: controlling factors.
2. Cover crop reduce nitrate leaching in agro-ecosystems: a global meta-analysis.
The title of my poster was: When does cover crops reduce nitrate leaching more effectively? a meta-analysis.
During the 2018 NorthEast Cover Crop Council (NECCC) conference held at Penn State University, I presented a poster entitled “Cover crop decomposition in no-till corn systems: Controlling factors”.
I have also published two meta-analysis articles in peer-reviewed journals. The articles were:
1. Thapa, R., H. Poffenbarger, K. Tully, V.J. Ackroyd, M. Kramer, and S.B. Mirsky. 2018. Biomass production and nitrogen accumulation by hairy vetch-cereal rye mixtures: a meta-analysis. Agronomy Journal. 110(4): 1197-1208.
2. Thapa, R., S.B. Mirsky, and K. Tully. 2018. Winter cover crops reduced nitrate leaching in agro-ecosystems: a meta-analysis. Journal of Environmental Quality. 47(6): 1400-1411.