Objective 1: Develop decision support tools to support a GxExM approach in research and for on-farm implementation of sustainable and resilient cropping systems. 1a. Integrate improved soil-landscape information into decision support. 1b. Improve decision support for nitrogen management in corn and cotton. 1c. Develop and evaluate new soil information sources. Objective 2: Develop and evaluate sustainable cropping systems resilient to increasing climatic variability through the application of site-specific soil and crop management using a GxExM framework. 2a. Evaluate production and soil health of innovative cropping systems designed to reduce vulnerability across landscapes. 2b. Develop and implement an innovative site-specific management system and evaluate compared to conventional practice. (CMRB LTAR).
Our interdisciplinary team will employ a GxExM approach to address key knowledge and technology gaps limiting the development of landscape-based site-specific management systems. We will develop methods that use the spatial soil, crop, and yield data collected with precision farming technologies to assess production and production risk of current and alternative management systems. To better understand soil health impacts of different management systems, we will develop and evaluate laboratory methods for important indicators as well as electronic sensor technology that can be deployed for field measurements. We will evaluate management systems that increase nitrogen use efficiency and that incorporate landscape targeting of conservation measures for improved resilience to climatic variability. We will also conduct field research to evaluate the production, profitability, and environmental ramifications of bioenergy crops. We will participate in the LTAR comparison of conventional and “aspirational” production systems through measurement and analysis of production, soil health, and mass and energy fluxes. Products of this research will include soil health indicators, sensors for measurement of multiple soil properties, contributions to long-term datasets, and agricultural and conservation practices specifically designed to deal with landscape variability.
Progress under bjective 1, “Develop decision support tools to support a genetics-by-environment-by-management (GxExM) approach in research and for on-farm implementation of sustainable and resilient cropping systems.”: (1) An 8-state effort to investigate the performance of in-season corn nitrogen management tools has completed its third and final year of field data collection (49 site-years). An overview journal article describing this regional research led by a project scientist, in collaboration with researchers at 8 Land Grant universities, has been accepted for publication. Affiliated graduate students are currently completing degrees and preparing journal publications, with approximately 6-8 manuscripts anticipated over the next year. (2) Data collection for a regional, in-situ sensor-fusion project has been completed and analysis is underway. Datasets obtained at multiple field sites in Missouri and other Midwest states include soil electrical conductivity, soil strength, visible and near-infrared soil spectroscopy data, passive gamma emissions from the soil and, in the laboratory, mid-infrared spectroscopy. Analyses will relate combinations of sensor data to a range of laboratory-measured soil properties. (3) A total soil protein assay has been implemented in the laboratory and evaluation of the assay is underway on hundreds of soil samples representing a wide range of management systems in Missouri. A journal article comparing the results of potentially mineralizable nitrogen (PMN) assessment is underway. A collaborative effort has been initiated to develop a national algorithm for active carbon scoring in the Soil Management Assessment Framework (SMAF) model. The data from our regional soil health assessments will contribute to this effort. Progress under Objective 2, “Develop and evaluate sustainable cropping systems resilient to increasing climatic variability through the application of site-specific soil and crop management using a GxExM framework.”: (1) Laboratory re-analysis of soil health samples collected to evaluate differences due to perennial grass production vs. grain cropping is complete. Data analysis to compare soil health under grain and switchgrass production systems is in progress. (2) Long-term yield and yield stability of a precision agriculture system (PAS) was compared to conventional management in an accepted journal article. Additional profitability analysis comparing these two systems is nearly complete, with a journal manuscript expected to be submitted within three months. Data collection continues on this research field in support of Long-Term Agroecosystem Research (LTAR) objectives. (3) Laboratory analysis of the LTAR baseline soil health samples collected in 2016 for the PAS and conventional field-scale systems is substantially complete.
1. Bioenergy crops perform well on degraded soils. Marginal areas within fields, often from soil erosion, typically exhibit low or even negative profitability due to suppressed grain yield, and these areas are also disproportionately responsible for off-field sediment and agrochemical losses. In a series of related studies, ARS scientists and university cooperators at Columbia, Missouri studied the production potential and soil improvement associated with growing perennial warm-season bioenergy crops, specifically switchgrass and miscanthus, on marginal and vulnerable soil landscapes. Over a range of soils, income instability was greater for grain crops than for miscanthus or switchgrass, largely because of the higher impact of price volatility and weather variation on grain crops. Switchgrass production on highly eroded landscapes was more stable and equally profitable to corn-soybean grain production, and had greater nitrogen recovery efficiency. Miscanthus produced on degraded soils needed nitrogen fertilization only approximately 30% of the time and at relatively low rates compared to corn, establishing it as a low input crop. Results demonstrate how farmers and farm advisors can improve conservation and provide economic stability on marginal soils by targeted placement of perennial warm-season bioenergy crops.
2. Sensor data fusion improves soil health assessment. Claypan soils of the Midwestern United States are highly prone to erosion and other environmental concerns, making evaluation of soil health a priority. Because conventional soil sampling and analysis is expensive and time consuming, ARS scientists and university collaborators at Columbia, Missouri evaluated soil sensor data fusion techniques for a rapid and inexpensive alternative to traditional laboratory testing. Soil chemical, physical, and biological properties were measured in the laboratory and soil health scores were calculated. Combinations of sensor data, including reflectance spectroscopy, electrical conductivity, and penetrometer readings, were evaluated for estimating the soil health measurements, providing improved estimates of soil health over reflectance spectroscopy alone. This study benefits scientists and producers by demonstrating the potential for rapid and inexpensive soil health assessment in the field that will save time and money, provide valuable information to drive management decisions, and increase profitability.
3. On-farm assessment of soil health provides valuable information. Soil health assessment is becoming increasingly popular, yet large-scale (i.e., regional) information on the impact of management practices on different soils is not available through traditional plot-scale research studies. Information at this scale is needed to develop soil health scoring curves and interpretations for farmers. With assistance from the Soil Heath Institute, ARS scientists at Columbia, Missouri and Ames, Iowa evaluated a large dataset collected from on-farm trials across several Midwestern states. Valuable information, such as soil texture, relating to large-scale processes that control a soil’s inherent potential was extracted from the dataset. This study benefits the development of a useful and interpretable soil health assessment by showing the value of on-farm data that will ultimately help farmers make management decisions to optimize soil health and crop productivity.
4. Organic management systems optimized for soil health and productivity. Soil disturbance, such as tillage, is known to reduce soil health. However, tillage is a typically required in organic management systems to control weeds and maintain yield. ARS scientists and university cooperators at Columbia, Missouri evaluated the benefits of incorporating cover crops along with different tillage practices for organic corn and soybean systems in Missouri. Soybean in organic no-till yielded as well as the conventionally tilled organic systems and was the most successful when cover crop biomass was sufficient to suppress weeds. However, organic no-till corn yielded less than conventionally tilled organic corn, potentially due to nitrogen tie-up in the crimped cover crop. Overall, this research benefits producers, scientists, and policy makers by demonstrating the ability to incorporate reduced tillage practices into organic systems while allowing farmers to maintain yield and profitability.
5. Management practices impact large patch disease in turfgrass. Large patch disease is a fungus that affects zoysiagrass and other turfgrasses, causing extensive damage in golf course fairways and landscaped areas. ARS scientists at Columbia, Missouri and collaborators from multiple universities investigated several organic amendments and management practices for their effect on the development of large patch disease and on soil microorganisms. Amendments of chicken manure and a synthetic fungicide reduced large patch severity by 49% and 86%, respectively. Assessment of the soil microbial community suggested that mechanical aeration of turf may stress the fungal population, potentially reducing large patch disease. The results of this study will benefit managers of zoysiagrass, including sod producers, business landscapers, lawn care professionals, and managers of golf fairways by allowing them to make more informed management decisions.
Yost, M.A., Randall, B.K., Kitchen, N.R., Heaton, E.A., Myers, R.L. 2017. Yield potential and nitrogen requirements of Miscanthus × giganteus on eroded soil. Agronomy Journal. 109(2):684-695. doi: 10.2134/agronj2016.10.0582.
Zaibon, S., Anderson, S.H., Kitchen, N.R., Haruna, S.I. 2016. Hydraulic properties affected by topsoil thickness in switchgrass and corn-soybean cropping systems. Soil Science Society of America Journal. 80(5):1365–1376. doi: 10.2136/sssaj2016.04.0111.
Clark, K., Boardman, D.L., Staples, J.S., Easterby, S., Reinbott, T.M., Kremer, R.J., Kitchen, N.R., Veum, K.S. 2017. Crop yield and soil organic carbon in conventional and no-till organic systems on a claypan soil. Agronomy Journal. 109(2):588-599. doi: 10.2134/agronj2016.06.0367.
Zaibon, S., Anderson, S.H., Thompson, A.L., Kitchen, N.R., Gantzer, C.J., Haruna, S.I. 2016. Soil water infiltration affected by topsoil thickness in row crop and switchgrass production systems. Geoderma. 286:46-53. doi: 10.1016/j.geoderma.2016.10.016.
Yost, M.A., Kitchen, N.R., Sudduth, K.A., Thompson, A.L., Allphin, E. 2017. Topsoil thickness influences nitrogen management of switchgrass. BioEnergy Research. 10(2):465-477. doi: 10.1007/s12155-016-9811-6.
Cho, Y., Sudduth, K.A., Chung, S. 2016. Soil physical property estimation from soil strength and apparent electrical conductivity sensor data. Biosystems Engineering. 152:68-78. doi: 10.1016/j.biosystemseng.2016.07.003.
Veum, K.S., Sudduth, K.A., Kremer, R.J., Kitchen, N.R. 2017. Sensor data fusion for soil health assessment. Geoderma. 305:53-61. doi: 10.1016/j.geoderma.2017.05.031.
Cho, Y., Sudduth, K.A., Drummond, S.T. 2017. Profile soil property estimation using a VIS-NIR-EC-force probe. Transactions of the ASABE. 60(3):683-692. doi: 10.13031/trans.12049.
Conway, L.S., Yost, M.A., Kitchen, N.R., Sudduth, K.A., Thompson, A.L., Massey, R.E. 2017. Topsoil thickness effects on corn, soybean, and switchgrass production on claypan soils. Agronomy Journal. 109(3):782-794. doi: 10.2134/agronj2016.06.0365.
Yost, M.A., Kitchen, N.R., Sudduth, K.A., Thompson, A.L., Allphin, E. 2017. Topsoil thickness and harvest management influence switchgrass production and profitability. Agronomy Journal. 109(3):985-994. doi: 10.2134/agronj2016.09.0561.
Sadler, E.J., Sudduth, K.A., Drummond, S.T., Thompson, A.L., Chen, J., Nash, P.R. 2016. Inferring random component distributions from environmental measurements for quality assurance. Agricultural and Forest Meteorology. 237:362-370. doi: 10.1016/j.agrformet.2017.02.021.
Randall, B.K., Yost, M.A., Kitchen, N.R., Heaton, E.A., Stelzer, H.E., Thompson, A.L. 2016. Impact of rhizome quality on miscanthus establishment in claypan soil landscapes. Industrial Crops and Products. 85(2016):331-340. doi: 10.1016/j.indcrop.2015.12.040.
Karlen, D.L., Goeser, N., Veum, K.S., Yost, M.A. 2017. On-farm soil health evaluations: Challenges and opportunities. Journal of Soil and Water Conservation Society. 72(2):26A-31A. doi: 10.2489/jswc.72.2.26A.