2009 Annual Report
1a.Objectives (from AD-416)
Acquire new knowledge important for managing agricultural practices on spatially-variable soil landscapes and for assessing their impacts and sustainability. Develop and evaluate in-field sensing technologies and data interpretation methods for spatially- and temporally-variable soil properties important in assessing and managing soils and crops. Develop, implement at field scale, and assess innovative site-specific management systems for improved profitability and for water and soil quality.
1b.Approach (from AD-416)
In this project, our interdisciplinary team will address key limitations to the overall goal of developing sustainable, site-specific soil and crop management systems. We will investigate spatially-variable soil-plant water relationships on hydrologically complex soils and the use of soil and rhizosphere biological measurements for soil quality assessment. We will explore the use of commercial sensor technology to provide estimates of soil hydraulic properties and of soil quality indicator variables. Building on our previous research, we will combine multiple soil sensor technologies into integrated, on-the-go tools for efficiently mapping within-field soil variability. We will investigate and compare analysis techniques available for understanding relationships between soil and landscape properties and crop yield, and will develop site-specific estimators of productivity that can help assess production risk. Building on our decade of experience in measuring and understanding within-field spatial variability, we will assess the profitability and water and soil quality of site-specific management systems. Management system evaluations will include on-farm research with active participation by crop producers and crop advisors. Products of this research project will include soil quality indicators, sensors for measurement of multiple soil properties, and agricultural and conservation practices specifically designed to deal with landscape variability.
Soil quality indicators: (1) A study assessing the impact of Epiaqualf topsoil depth on grain and switchgrass productivity was initiated to better understand the implications for bioenergy feedstock production practices across landscapes. Effects of grain and switchgrass management practices on soil quality parameters are being assessed to help understand long-term environmental sustainability of bioenergy feedstock production. (2) Testing of a rapid field-based soil quality indicator that uses a dilute permanganate solution for assessing biologically-active soil organic matter was expanded to include soils from diverse management systems. Results showed that differences in active C were readily distinguished among soils under contrasting management. (3) Biological soil indicators including enzyme activities, soil organic C, and plant root density were highly correlated with a simple in-field physical test for soil shear strength, an indicator for resistance to water erosion. Results are important because the accepted connection of biological and physical properties of soils are further validated and can be readily demonstrated to the farmer. Sensor development and evaluation: (1) Investigated the ability of near-infrared (NIR) reflectance sensing to quantify differences in soil quality indicators before and four years after initiation of a conservation-oriented management system. Found that NIR data were not able to discriminate the temporal differences that were found with traditional laboratory analysis. (2) Evaluated soil apparent electrical conductivity (EC) for estimating topsoil depth on Epiaqualfs using both statistical regression-based and theoretical model-based approaches, finding that both gave very similar results. Analysis of site-specific data: Added additional data to a grain yield map database, increasing it to over 50,000 acre-years of data and merged the yield data with digitized soil map data on a 30m grid cell size. Ranked major soils in the database on the basis of their production potential and production risk for corn and soybean. Management system evaluation: (1) Continued a study evaluating precision conservation at the field scale, including cover crops, waterway stabilization, plant residue maintenance with no-till, targeting of crops to match the soil resource, and variable-rate nutrient applications. Sampling to assess soil quality changes since the inception of this project was conducted. Additional crop, water, and soil monitoring is ongoing. (2) A first cycle of field-scale experiments assessing active corn crop-canopy reflectance sensing for N fertilization was completed. Findings were used to initiate new field-scale studies designed to fill in knowledge gaps from the first studies and to assess new commercial sensor technology. (3) Completed analysis and interpretation of field data to document long-term cropping system and landscape position effects on soil compaction.
Soil quality under agroforestry documented for claypan soils. Grass buffer or agroforestry (pin oak trees) strips were previously established within a no-till corn-soybean cropping system on two adjacent watersheds to reduce soil erosion on a gently sloping claypan landscape in northeastern Missouri. Because little is known about how these conservation practices affect biological and physical properties that influence soil quality, we examined changes in soil carbon, bulk density and soil aggregation, and soil enzyme activity under grass and agroforestry buffers at different landscape positions. The cropped areas always had higher soil bulk densities than the grass or tree buffer strips, likely because perennial vegetation encourages greater rooting volume and higher porosity thereby lowering density. Higher aggregate stability in buffer areas also suggested an improved soil structure developed in the claypan soils, and soil carbon and soil enzyme activities were greater in the grass and agroforestry soils than in the cropped soils. These were directly related to decreased soil bulk density and increased aggregation, which suggests better aeration, water infiltration, and organic matter stabilization. Results are important because they quantify the improvement of soil quality attributes by the soil conservation practices of grass buffer and agroforestry strips established on landscapes prone to degradation by erosion and compaction.
NIR estimates of key soil profile properties. Sensors that can estimate soil properties without the need for sampling are a promising approach to obtaining the amount of data required to characterize spatially variable soils. Optical reflectance sensing of surface soils in the visible and near infrared (NIR) wavelength bands has been successful in this regard, but few have investigated this approach within the soil profile. In this research, laboratory visible-NIR reflectance measurements were obtained for surface and profile soil samples from five Midwestern states, and analyses related these data to soil physical and chemical properties. Good results were obtained for soil carbon, clay, cation exchange capacity, and calcium, and analyses identified appropriate spectral ranges and calibration techniques to improve accuracy. Because NIR measurements can be obtained quickly and inexpensively, these findings may lead to more efficient soil measurement techniques and improve soil management for production and environmental sustainability.
Crop reflectance sensing to guide corn nitrogen application. With increasing costs for crop inputs and environmental concerns associated with large amount of N from agricultural fields moving into streams, rivers, and the ocean, corn farmers are interested in better methods to help them precisely apply the rate of nitrogen (N) fertilizer. Since more N fertilizer in the U.S. is applied to corn than any other crop, interest is high for exploring new technologies, and therefore, this research was conducted to assess the utility of light reflectance sensors for determining the most profitable N rates in corn. Findings over all soil types demonstrate sensor-based variable-rate N fertilizer applications could generate an increase in returns ranging from $5 to $50 per acre, depending on the soil type; further, as fertilizer cost increases relative to the price of corn grain, the value of using canopy sensors for N management improved. Farmers will benefit because they can reduce excess N applications, which with increasing N fertilizer cost, should save them money. If fertilizer can be better matched with crop need, N loss to lakes and streams will be reduced and the environment will be improved.
5.Significant Activities that Support Special Target Populations
Continued collaboration with small and family farmers (one of which is a woman owner-operator of an organic farming enterprise) in monitoring on-farm soil quality attributes of various management practices.
Continued collaboration with Lincoln University (HBCU in Jefferson City, MO) investigating greenhouse gas emission. Project scientist is currently serving as co-advisor for 1 PhD and 1MS student conducting research on that project.
|Number of Other Technology Transfer||1|
Holan, S., Wang, S., Arab, A., Sadler, E.J., Stone, K.C. 2008. Semiparametric Geographically Weighted Response Curves with Application to Site Specific Agriculture. Journal of Agricultural, Biological, and Environmental Statistics. 13(4):424-439.
Jiang, P., He, Z., Kitchen, N.R., Sudduth, K.A. 2009. Bayesian Analysis of Within-Field Variability of Corn Yield Using a Spatial Hierarchical Model. Precision Agriculture. 10(2):111–127.
Jung, W.K., Kitchen, N.R., Sudduth, K.A., Kremer, R.J. 2008. Contrasting grain crop and grassland management effects on soil quality properties for a North-Central Missouri claypan soil landscape. Soil Science and Plant Nutrition. 54(6):960-971.
Adamchuk, V.I., Ingram, T.J., Sudduth, K.A., Chung, S. 2008. On-the-go mapping of soil mechanical resistance using a linear depth effect model. Transactions of the ASABE. 51(6):1885-1894.
Chung, S.O., Jung, I.K., Sung, J.H., Sudduth, K.A., Drummond, S.T. 2008. Analysis of Spatial Variability in a Korean Paddy Field Using Median Polish Detrending. Journal of Biosystems Engineering. 33(5):362-369.
Chung, S.O., Sudduth, K.A., Tan, J. 2008. Spectral analysis of on-the-go soil strength sensor data. Journal of Biosystems Engineering. 33(5):355-361.
La, W.J., Sudduth, K.A., Chung, S., Kim, H.J. 2008. Preprocessing and calibration of optical diffuse reflectance estimation of soil physical and chemical properties in the central USA. Journal of Biosystems Engineering. 33(6):430-437.
Massey, R.E., Myers, D.B., Kitchen, N.R., Sudduth, K.A. 2008. Profitability Maps as an Input for Site-Specific Management Decision Making. Agronomy Journal. 100:52-59.
Lee, K.S., Lee, D.H., Sudduth, K.A., Chung, S.O., Kitchen, N.R., Drummond, S.T. 2009. Wavelength Identification and Diffuse Reflectance Estimation for Surface and Profile Soil Properties. Transactions of the ASABE. 52(3):683-695.
Lee, K.S., Lee, D.H., Jung, I.K., Chung, S.O., Sudduth, K.A. 2008. Sampling and calibration requirements for optical reflectance soil property sensors for Korean paddy soils. Journal of Biosystems Engineering. 33(4):260-268.
Noellsch, A.J., Motavalli, P.P., Nelson, K.A., Kitchen, N.R. 2009. Corn Nitrogen Response Across a Claypan Landscape Using Polymer-Coated Urea and Anhydrous Ammonia. Agronomy Journal. 101:607-614.
Schomberg, H.H., Wietholter, S., Griffin, T.S., Reeves, D.W., Cabrera, M.L., Franzluebbers, A.J., Fisher, D.S., Endale, D.M., Novak, J.M., Balkcom, K.S., Raper, R.L., Kitchen, N.R., Locke, M.A., Potter, K.N., Schwartz, R.C., Truman, C.C., Tyler, D.D. 2009. Assessing indices for predicting potential N mineralization in pedogenically distinct soils under different tillage management systems. Soil Science Society of America Journal. 73(5):1575-1586.
Oueslati, O., Ben-Hammouda, M., Ghorbel, M.H., El Gazzah, M., Kremer, R.J. 2009. Role of Phenolic Acids in Expression of Barley (Hordeum vulgare) Autotoxicity. Allelopathy Journal. 23(1):157-166.
Udawatta, R.P., Kremer, R.J., Garrett, H.E., Anderson, S.H. 2009. Soil Eenzyme Activities and Physical Properties in a Watershed Managed Under Agrogorestry and Row-Crop Systems. Agriculture Ecosystems and the Environment. 131(1):98-104.