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United States Department of Agriculture

Agricultural Research Service

Research Project: LANDSCAPE-BASED CROP MANAGEMENT FOR FOOD, FEED, AND BIOENERGY

Location: Cropping Systems and Water Quality Research

2013 Annual Report


1a. Objectives (from AD-416):
Develop and evaluate food, feed, and bioenergy cropping systems resilient to increasing climatic variability through the application of site-specific soil and crop management. Develop biological assays and soil sensors that are capable of describing soil quality variations between diverse management systems and across landscapes.


1b. Approach (from AD-416):
In this project, our interdisciplinary team will 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 and yield data collected with precision farming technologies to determine where on the landscape to best place alternative crops, such as perennial bioenergy crops. We will also conduct field research to evaluate the production, profitability, and environmental ramifications of bioenergy crops. To better understand soil quality impacts of different management systems, we will develop systems incorporating biological assays and electronic sensor technology that can be deployed for field measurements. We will evaluate site-specific management systems that increase nitrogen use efficiency and that incorporate landscape targeting of conservation measures for improved resilience to climatic variability. Management system evaluations will include on-farm research with active participation by crop producers and crop advisors. Products of this research will include soil quality indicators, sensors for measurement of multiple soil properties, and agricultural and conservation practices specifically designed to deal with landscape variability.


3. Progress Report:
Progress under project objective 1, “Develop and evaluate food, feed, and bioenergy cropping systems”: (1) Analyses relating yield maps to landscape properties led to specification of metadata, including weather and management information, that are required to better understand interactions among soil resources, weather, and management and their effects on crop yield. A journal manuscript is in preparation. (2) A method to develop environmental index maps has been formalized for Goodwater Creek and is being applied to Long Branch Watershed, with application to other tributaries of Mark Twain Lake planned for early FY14. Methods to compare environmental and productivity maps have also been formalized. Results have been documented in a poster and proceedings paper. (3) Weather conditions in 2011 and 2012 resulted in establishment failures for the willow biofuel cropping system at the Centralia Research Farm. That cropping system has been converted to miscanthus, which was planted earlier this year. A fourth year of data is being obtained on the effects of landscape and soil conditions on switchgrass management and yield. Data analysis and publication are planned for 2014. (4) Field studies are underway to evaluate interactions of corn hybrid, population, and site-specific nitrogen (N) management systems. When combined with similar studies in Nebraska and North Dakota, results will be used for regional analysis and interpretation of the factors important for site-specific N management. (5) Data collection is proceeding on studies evaluating the effect of soil background differences on crop reflectance sensors used for N management. Additional field studies are planned in 2014, as are studies evaluating the ability of sensors to separate the effects of drought stress and N stress. (6) The 2013 cropping season will complete 10 years (5 rotation cycles) of the Precision Agriculture System at the Centralia Research Farm. Grid soil sampling for fertility was completed in the spring of 2013. Additional sampling for soil quality will be conducted later this year. A 10-year analysis of yield and profitability will begin after harvest data are available. Progress under project objective 2, “Develop biological assays and soil sensors for describing soil quality”: (1) A previously developed soil quality model (the Soil Management Assessment Framework; SMAF) differentiated crop management-landscape systems based on derived soil quality indexes using a small set of soil quality indicators, which is a limitation of SMAF. We found several additional parameters, including active carbon and microbial enzyme activity to be excellent candidate indicators to supplement SMAF, based on high correlations with SMAF scores. Inclusion of these and other indicators could potentially improve sensitivity of the model in fully evaluating impacts of soil management. (2) Laboratory-measured visible and near-infrared soil reflectance spectra were found to be good estimators of several biological indicators of soil quality. Spectra were also well-correlated with SMAF scores, showing this to be a promising avenue for development of a sensor-based soil quality index.


4. Accomplishments


Review Publications
Veum, K.S., Goyne, K.W., Kremer, R.J., Motavalli, P.P. 2012. Relationships among water-stable aggregates and organic matter fractions under conservation management. Soil Science Society of America Journal. 76(6):2143-2153.

Sudduth, K.A., Myers, D.B., Kitchen, N.R., Drummond, S.T. 2013. Modeling soil electrical conductivity-depth relationships with data from proximal and penetrating ECa sensors. Geoderma. 199:12-21.

Kremer, R.J. 2013. Interactions between plants and microorganisms. Allelopathy Journal. 31(1):50-71.

Kim, H., Sudduth, K.A., Hummel, J.W., Drummond, S.T. 2013. Validation testing of a soil macronutrient sensing system. Transactions of the ASABE. 56(1):23-31.

Kim, H., Kim, W., Roh, M., Kang, C., Park, J., Sudduth, K.A. 2013. Automated sensing of hydroponic macronutrients using a computer-controlled system with an array of ion-selective electrodes. Computers and Electronics in Agriculture. 93:46-54.

Kim, S., Hong, S., Sudduth, K.A., Kim, Y., Lee, K. 2012. Comparing LAI estimates of corn and soybean from vegetation indices of multi-resolution satellite images. Korean Journal of Remote Sensing. 28(6):597-609.

Unger, I.M., Goyne, K.W., Kremer, R.J., Kennedy, A.C. 2013. Microbial community diversity in agroforestry and grass vegetative filter strips. Agroforestry Systems. 87:395-402.

Unger, I.M., Goyne, K.W., Kennedy, A.C., Kremer, R.J., McLain, J.E., Williams, C.F. 2013. Antibiotic effects on microbial community characteristics in soils under conservation management practices. Soil Science Society of America Journal. 77:100–112.

Tremblay, N., Bouroubi, M.Y., Belec, C., Mullen, R.W., Kitchen, N.R., Thomason, W.E., Ebelhar, S., Mengel, D.B., Raun, W.R., Francis, D.D., Vories, E.D., Ortiz-Monasterio, I. 2012. Corn response to nitrogen is influenced by soil texture and weather. Agronomy Journal. 104(6):1658-1671. DOI:10.2134/agronj2012.0184.

Chung, S., Sudduth, K.A., Motavalli, P.P., Kitchen, N.R. 2013. Relating mobile sensor soil strength to penetrometer cone index. Soil & Tillage Research. 129:9-18. DOI: 10.1016/j.still.2012.12.004.

Kremer, R.J., Souissi, T. 2013. Phytotoxicity assessment for potential biological control of leafy spurge by soilborne microorganisms. Australasian Plant Pathology. 42(4):441-447.

Last Modified: 10/18/2017
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