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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
1. Antibiotics in manure did not negatively affect soil biological activity. Livestock manures applied to fields often contain veterinary antibiotics, and the effects of those antibiotics on soil microbial activity are not well known. In cooperation with the University of Missouri, ARS scientists at Columbia, MO, Pullman, WA, and Maricopa, AZ treated soils with two common veterinary antibiotics and looked for changes in the function and composition of the microbial community as well as the development of antibiotic resistance. When soils from vegetative filter strips (perennial, deep-rooted grasses or grasses plus trees (agroforestry) integrated with row crops across the landscape) were evaluated for microbial characteristics, no evidence of increased antibiotic resistance was found, and only a small, short-lived decrease in soil microbial activity was seen early after treatment. This suggests that, contrary to the anticipated disruption of the microbial community due to relatively large antibiotic doses, antibiotics did not affect microbial structure or function in vegetative filter strips. The retention of antibiotics in vegetative filter strips without negative effects on the associated soil microbial communities is important because critical soil biological processes are not disrupted. This is an additional benefit of this management practice that maintains or improves soil quality while increasing overall productivity and reducing environmental impact.

2. Soil quality assessment of conservation practices. Little is known about changes in soil quality in response to conservation management practices including vegetative filter strips integrated in row-crop production fields. In cooperation with the University of Missouri, ARS scientists at Columbia, MO evaluated soil aggregate stability and water-extractable organic carbon (C) as rapid indicators of soil quality change in vegetative filter strips within a no-till corn-soybean rotation cropping system in northwest Missouri. We found that critical soil quality indicators including aggregate stability and water-extractable organic C nearly doubled under grass and agroforestry vegetative filter strips compared to no-till areas without vegetative cover. The results show that the lack of a continuous, living root biomass in cropped fields leads to reduced production and retention of soil organic matter compared with the perennial vegetation in vegetative filter strips. Aggregate stability and water-extractable organic C were found to be rapid, cost effective indicators of short-term (10 year) changes in soil quality and confirms that conservation management practices implemented on claypan soils are effective in maintaining or improving overall soil quality.

3. In-season corn nitrogen adjustments based on soil texture and weather. Corn yield response to nitrogen fertilizer application can vary from one soil type to another and from year to year due to weather variations. ARS scientists from Columbia, MO were part of a team from across North America that examined the effects of soil and weather factors on corn nitrogen response across 51 sites representing a wide range of diverse weather and soil conditions. Soil and weather properties were found to have a pronounced effect, with yield response much greater on fine-textured soils than on coarse-textured soils. A new precipitation metric called “abundant and well-distributed rainfall” was developed and was important in helping to explain corn nitrogen response. These results along with improvements in weather forecasting will facilitate significant improvements to in-season nitrogen fertilization strategies, thereby increasing farmer profits and reducing nutrient losses off fields into ground and surface waters.

4. New approach uses sensor data to quantify subsoil variability. Because they allow collecting data rapidly and efficiently, apparent soil electrical conductivity (ECa) sensors are widely used to map within-field soil variability for guiding site-specific management. Simultaneous analysis of data from multiple ECa sensors can provide improved information on subsurface soil variations, but current mathematical and statistical techniques do not always give reliable results. ARS scientists in Columbia, MO developed a new approach for combining ECa sensor data that provided a better representation of measured variations of ECa in the soil profile than previous methods. With this new approach, users of ECa sensors may obtain more accurate estimates of how soil properties vary within the soil profile, providing better information on which to base management decisions and leading to improvements in crop productivity and reduced environmental impact.


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.

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.

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

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.

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.

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.

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.

Last Modified: 9/22/2014
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