Skip to main content
ARS Home » Southeast Area » Booneville, Arkansas » Dale Bumpers Small Farms Research Center » Research » Research Project #436698

Research Project: Sustainable Small Farm and Organic Grass and Forage Production Systems for Livestock and Agroforestry

Location: Dale Bumpers Small Farms Research Center

2021 Annual Report


Objectives
Objective 1. Management systems for improved growth, handling and storage of harvested biomass for optimized quality and utilization for improved livestock management and positive environmental benefits. Sub-objective 1A. Forage and biomass production systems that better utilize nutrients to increase productivity and/or reduce energy and nutrient input requirements. Sub-objective 1B. Biomass harvest and storage systems that enhance the value of the feedstock for livestock production. Sub-objective 1C. Efficient strategies for producing livestock on forage-based diets, targeting optimal productivity. Sub-objective 1C1. Identification and selection of animal phenotypes that are productive and thrive on low-input pasture systems to minimize management inputs. Sub-objective 1C2. Understanding grazing behavior and spatial distribution of sheep naturally infected with gastrointestinal nematodes. Objective 2: Develop integrated tools to foster improved management of pasture and forages which maintain productivity while providing economic and environmental benefits. Sub-objective 2A. Measuring and monitoring system status and function at various scales. Sub-objective 2A1. Develop tools to identify environmental factors affecting forage production to maximize productivity and environmental/ecosystem benefits in diverse environments. Sub-objective 2A2. Utilize spatial information to develop site specific recommendations for warm season forage species, nutrient requirements and economic inputs for improved farm management. Sub-objective 2B. Provide tools that support management decisions and aid implementation. Sub-objective 2B1. Determine site specific recommendations coupling soil water availability with nutrient requirements to optimize forage production for economic sustainability. Sub-objective 2B2. Farm-scale recommendations that provides a decision support tools for producers that will allow optimization of farm management for whole farm productivity, economic viability and environmental sustainability. Sub-objective 2C. Pasture-based livestock management practices that improve resilience to climate change, conserve soil or protect water quality, optimizing production, conservation and environmental goals. Sub-objective 2D. Targeted grazing strategies to reduce invasive grasses and forbs and promote desirable perennial grasses and woody species. Sub-objective 2E. Grazing management strategies for maintenance of a diverse native plant pasture that serves livestock and wildlife including native pollinators. Sub-objective 2E1. Impact of grazing on insect pollinators and beneficial arthropod community in pasture ecosystems designed for multiple use of livestock grazing and pollinator habitat. Sub-objective 2E2. Impact of native forbs and grasses on insect pollinators and beneficial arthropods and plant- pollinator interactions in pasture ecosystems designed for multiple use of livestock grazing and pollinator habitat.


Approach
Our goal is to increase long-term sustainability of small farms by integrating management of pasture and silvopasture-based livestock systems to augment whole-farm productivity and profitability, encourage crop diversification which spreads biological and financial risk, and enhances ecosystem services. Involving both short- and long-term studies, we will determine practices that provide environmental and economic benefit to small farms. Studies will focus on improving forage and/or livestock production while enhancing soil, landscape and forage attributes at multiple scales. These studies include examining conventional and nonchemical parasite control on sheep production efficiency, grazing management on forage finished beef and lamb, and improving nutrient-use efficiency on forage pastures. Additionally spatial information will be used to understand interactions at multiple scales to develop decision support tools for increasing efficiency for soil-forage system management. We will also continue a long-term study that utilizes controlled watersheds to determine the impacts of various pasture management strategies (rotational grazing, overgrazing, haying, tree buffers) on pasture hydrology and nutrient runoff. To evaluate diversification, we will examine effects of integrating agroforestry management with crop and/or livestock production.


Progress Report
Sub-objective 1A. Poultry litter was applied by different methods, surface application and subsurface application. Subsurface application utilized an ARS patented prototype that injects litter under the soil surface. Surface treatments used a traditional litter broadcaster and control plots received no litter. Forage was harvested from the plots and sampled for P, K, Ca, Mg, S, protein, water soluble carbohydrates, and fiber components to determine nutrient utilization among the poultry litter amendment treatments. Statistical analysis has been completed and a manuscript has been drafted and submitted. Sub-objective 1B. A study was conducted on plots amended with surface poultry litter and sub-surface poultry liter and baled at different moistures. Prior to wrapping, bales were sampled with a bale probe and stored for later analysis. Bales were then wrapped and stored until the completion of the ensiling process. Post-ensiled samples were taken approximately 6 months after baling. Pre- and post-ensiled samples were analysis P, K, Ca, Mg, S, protein, waters soluble carbohydrates, and fiber components. These variables were regressed against bale moisture and many relationships were determined. Statistical analysis has been completed and a manuscript drafted and submitted. Subobjective 1C1.1. Out-of-season breeding of ewes (approximately 200 ewes (2018 – 2021), both organic and conventional management systems, age was 8 months to up to 10 years) were exposed to rams in Spring and Fall. Body weights, condition, hair coat score, rectal temperature, pregnancy and lambing rates were recorded. Multiple compared with single sire groups were used; the former increased pregnancy and lambing rate. Blood samples were analyzed to determine serum concentrations of progesterone, prolactin and cytochrome P450. Forage analyses and complete statistical analyses are pending. Another small study on a subset of ewes was conducted in 2019 and 2020 to determine the effect of endophyte-free or -infected tall fescue on serum concentrations of prolactin, rectal temperature weekly during breeding. Data were analyzed, an abstract presented, and manuscripts are in preparation. While body temperature increased and serum concentrations of prolactin decreased in ewes fed endophyte-infected compared with endophyte-free tall fescue in fall and winter, Cytochrome P450 activity did not differ, thus not a good marker for fescue toxicosis in sheep. Subobjective 1C1.3. There were 5,000 sheep from 21 farms across the U.S. genotyped using an ovine genotyping array (50K) SNP. All sheep had phenotypes for parasite resistance (fecal egg counts determined around the time of weaning). QC measures were applied for genome-wide association studies to identify possible genetic loci associated with resistance to gastrointestinal nematodes. A study on a smaller sub-population has been published (Becker et al., 2020) and a manuscript is being prepared on a follow-up study. An additional 600 samples from the same population were genotyped using a high density SNP for a more in depth look at genes responsible for parasite resistance and data are being analyzed. Subobjective 1C2. Weaned lambs that were naturally infected with gastrointestinal nematodes (GIN) were fitted with GPS collars for 72 hours weekly for six weeks to examine behavior in 2019. Measures of GIN infection (fecal egg counts, packed cell volume), rectal temperature and body weights were determined every 7 days. Data are being analyzed. The study will be repeated in 2022. Objective 2, Subobjective 2A. 2A1. The plots have been established with stands of bermudagrass (Cynodon dactylon L.) and tall fescue for the 3-year study. Soils samples for 3 soil types have been collected and are currently being analyzed. The forages are being monitored and sampled for yield, ADF and NDF to relate functional soil properties to forage productivity. 2A2. Soil samples have been analyzed for primary, secondary, and micronutrients. Total N concentration were determined and Mehlich-3 of all elements were determined using an ICP. GPS coordinates of each site were recorded using a hand-held GPS unit. A DEM of 1 m x 1m grid spacing was used to extract 20 terrain attributes within SAGAGIS and ArcGIS platforms for topographic information. These terrain attributes are being linked with soil properties to compare to forage metrics. For tree species, we have measured growth and estimated biomass. The data are currently being analyzed and utilized for a publication that has been submitted. Subobjective 2B. 2B1. Topsoil samples from tree alleys were collected based on topographic position representing high, low, and medium elevations. Samples were analyzed for N, P, K, Ca, Mg, S, Fe, Na, Mn, Zn, CU, and B. Total N was determined by high-temperature combustion. Mehlich-3 extractions of P, K, Ca, Mg, S, Fe, Na, Mn, Zn, Cu, and B were determined using an ICP. GPS coordinates of each point were recorded using a hand-held GPS unit. The data collected is being utilized to identify topographic functional units (TFU) using terrain attributes where the individual units are more homogeneous in terms of terrain properties and behave as a single functional unit in a landscape. The data are currently being analyzed and evaluated. 2B2. The field data has been collected using drivers with different levels of experience. The field topography and morphology is currently being analyzed to relate field shapes to driver experience to compare with precision auto-steer. The gaps and overlaps will be calculated to relate to efficiency gains or losses. Subobjective 2C. The 15 small watersheds (0.35 acre, 8% slope) are equipped with flumes and automatic water samplers. There are 5 treatments being evaluated with 3 replications per treatment in a completely randomized design. The treatments are; (1) hayed only, (2) over-grazed (continuous heavy grazing), (3) rotational grazing, (4) rotational grazing with an unfertilized buffer strip and (5) rotational grazing with an unfertilized riparian buffer. Sward height is monitored to ensure that overgrazing does not occur on the rotational grazing treatments. Samples have been collected for each runoff event and analyzed for pH, electrical conductivity, total P, SRP, soluble metals, total metals, total N, nitrate-N, ammonium-N, total solids, and total organic carbon. Soil samples are analyzed for Mehlich III P, and SRP (10:1 soil:deionized water). Data collection is ongoing and will be summarized for publication after 3 years of data collection. Subobjective 2D. A study was conducted on the effect of grazing intensity compared with mowing or no treatment on perilla mint growth and prevalence. In the first year, there were fewer perilla mint plants on plots that were mob grazed by sheep between May and September, but less consistent plant number differences between the mowed and non-mowed exclosure plots. The pasture was extremely weedy the following year and few perilla mint plants observed. Mob grazing may offer some control of perilla mint. No sheep exhibited signs of toxicity during the study. Subobjective 2E Subobjective 2E1. The impact of grazing native forb and grasses on bees and other insects in livestock pastures were examined. Native forages were established in 6-0.4 ha livestock plots and divided into grazed or non-grazed. Blue vane traps and yellow and blue pan traps were used to collect bees and other insects. Plant species composition in both types of pastures was also recorded. Bee communities were more diverse and higher evenness observed in non-grazed compared to grazed pastures, possibly due to differences in availability of flowering forages. However, bee abundance and species richness were similar among grazing treatments. Another study was conducted to examine the effects of grazing or no grazing of plots planted with native grasses and forbs important for pollinator habitat. Arthropod samples were collected using multiple collection devices (pan traps, nets, blue vein traps) to determine species and prevalence of pollinators within each grazing management treatment in 2018 and 2019. Thousands of arthropod samples were speciated and counted for bee and non-bee species. Manuscripts and dissertation are in preparation. Subobjective 2E2. Four different colors of pan traps (blue, green, yellow, and purple) were examined for their utility in sampling bees in livestock pasture ecosystem comprised of native forage species. We analyzed relative abundance, richness, similarity, and community assemblage patterns associated. The blue color traps were the most attractive to bees, and were effective for sampling bees in a livestock pasture ecosystem. Purple color traps were the second most effective, followed by yellow and green color traps. A manuscript was published (Acharya et al., 2021). Another study was conducted to assess the impact of different vane colors of a passive trap on wild bee sampling. There were 2230 bees recorded comprising 49 species, and five families. The most abundant species was Augochlorella aurata (25.8%), followed by Lasioglossum disparile (18.3%), L. imitatum (10.85%), Agapostemon texanus (10.8%), Melissodes veroninae (9.9%) and Halictus ligatus (4.7%). Traps with bright blue vanes captured the highest number of bees and most diverse bee species compared with bright yellow, dark blue, dark yellow, and purple vanes. Red vane traps captured the least diverse bee species. Out of the 49 bee species, only nine were found in all vane color types. Bright blue vanes attracted the greatest number of unique species. Vanes with higher light reflectance properties (within 400-600 nm range) attracted the highest number of bee species. These results suggest that bees respond differently to different light wavelength and reflectivity of vanes of passive traps, and such findings would be helpful in optimizing bee sampling methods.


Accomplishments
1. Development of genomic tools to identify gastrointestinal parasite resistant sheep. Perhaps the most important means of parasite control is parasite resistance within an animal. Genetic resistance to parasitic nematode infection (measured by low fecal egg counts relative to flock/herd mates) varies among individuals within a breed and is known to be moderately heritable; identification of genetic markers of resistance will have wide benefit in the sheep industry as dewormers are largely ineffective to control parasites in the animal. As the lead for a multi-institutional, multi-disciplinary team funded by NIFA's Organic Agriculture Research and Extension Initiative, ARS researchers in Booneville, Arkansas, along with research colleagues from Louisiana State University, Virginia Tech, Katahdin Hair Sheep International, University of Nebraska-Lincoln, and University of Idaho, used genomic techniques on 5,000 sheep from 21 farms across the US to identify potential sites on genes (chromosomes 2, 3, 16, and 23) associated with resistance to gastrointestinal parasites in sheep. This information is important to sheep producers, scientists, veterinarians, and extension specialists aiming to quantitatively improve genetic parameters and parasite resistance in sheep without the use of dewormers.

2. Selection for fertility and ability to breed out-of-season in sheep permits maximized reproductive performance. Concentrations of a specific hormone called, anti-Mullerian hormone (AMH), has been shown to predict fertility in beef cattle; breeding values generated by data collection over generations is valued as well. ARS researchers in Booneville, Arkansas, and colleagues from the University of Arkansas determined that AMH was not useful in predicting fertility or out-of-season breeding (breeding during spring or long days vs. short) ability in sheep, but estimated breeding values generated by the National Sheep Improvement Program were useful in predicting performance of first time lambing. This information is important to sheep producers, scientists, veterinarians, and extension specialists aiming to improve reproductive performance in sheep.

3. Many tractors are now equipped with global positioning system (GPS) technology linked to the steering mechanism to guide tractors for field operations. ARS researchers in Booneville and Fayetteville, Arkansas, along with colleagues from the USDA ARS Poultry Production and Products Safety Unit in Fayetteville and University of Arkansas developed an automated method for rapid determination of spatial coverage of precision agriculture technologies, such as auto-guided tractors and other self-propelled machinery that reduce over-application of on-farm nutrients and inputs by 10-20%. It is estimated that auto-guided tractors reduce on-farm inputs by as much as 20% and can save producers $10.8-13.5 million annually by improving gains in equipment efficiency and enhancing yields. Currently, roughly half of large-scale row crop producers are using tractor guidance, however, 82% of the total farms in the U.S. are small farms but are largely not adopting these cost and environmental saving technologies. This team: 1) developed a method to calculate overlaps and gaps, and 2) quantified overall gains by tractor guidance systems. Tractor guidance systems likely result in reduced input-use and shorter in-field operation time leading to improved economic and environmental savings. Our approach to estimate tractor guidance efficiency on small farms using actual field research is novel and may aid in adoption of tractor guidance, thus potentially improving efficiency gains on 82% of U.S. farms.

4. Hay is the most inexpensive nutritional supplement to maintain cattle weight during winter months and forage nutritional value changes throughout the year due to the onset of maturity. Forage value cannot be improved through the hay or baleage making process, however, baleage is advantageous because it allows farmers to harvest forage at peak nutritive value in early spring, when frequent rains typically deter dry hay making. ARS researchers in Booneville, Arkansas, utilized poultry litter as a fertilizer, either applied by broadcasting or below the soil surface (sub-surface), and forage was baled at different moistures to evaluate any interactions among poultry litter application methods and the different moistures. Bale moisture is known to greatly affect the final post-ensiled bale; however, enough moisture must be present to provide an environment for the microbial populations that carry out fermentation. Therefore, increased bale moisture results in greater production of volatile fatty acids and therefore a lower pH which stabilizes and preserves the wrapped bale overtime. Our results indicated that there were no interactions between poultry litter application method and bale moisture, with only minor differences between broadcast and sub-surface applied litter on baleage nutritive value. This research provides a tool for farmers which allows them to manage hay production to optimize nutritional quality of hay.

5. Machine learning is a powerful analytical tool and increasing usefulness for understanding complex interactions. ARS researchers in Booneville, Arkansas, have incorporated machine learning into digital soil mapping techniques. With digital soil mapping, the machine learning techniques have provided tools for grouping soils that demonstrate similar responses in crops, forages and trees related to soil-landscape features. The new method development has demonstrated that tree species differ in growth rates and biomass depending on the spatial location. When the machine learning-based soil maps are used for management decisions, research has demonstrated corn and bean yields increased by 20-30% in rainfed systems. This research contributes to overall farm efficiency, mitigation of the effects of climate change, informed management options for improving water quality and overall farm efficiency. With increased computational processing power, these tools can be used for global precision management in all agricultural systems to optimize production.


Review Publications
Jiang, Y., Sun, Z., Wang, Q., Sun, Z., Jiang, Z., Gu, H., Libohova, Z., Owens, P.R. 2020. Characteristics of a typical loess profile with a macroscopic tephra layer in the northeast China and the paleoclimatic significance. Geoderma. 198:105043. https://doi.org/10.1016/j.catena.2020.105043.
Martinez, A., Camberato, J., Owens, P.R., Ashtekar, J.M. 2020. Using terrain algorithms on a digital elevation model to evaluate yield potential in oil palm. Journal of Oil Palm Research. https://doi.org/10.21894/jopr.2020.0092.
Mauri, E.N., Viola, M.R., Norton, L.D., Owens, P.R., Mello, C.R., Pinto, L.C., Curi, N. 2020. Hydrosedimentological modeling in a headwater basin in Southeast Brazil . Revista Brasileira De Ciencia Do Solo. https://doi.org/10.36783/18069657rbcs20200047.
Chai, J., Alrashedi, S., Coffey, K., Burke, J.M., Feye, K., Ricke, S., Park, S., Edwards, J.L., Zhao, J.C. 2020. Endophyte-infected tall fescue affects rumen microbiome in grazing ewes at gestation and lactation. Frontiers in Veterinary Science. 7:1-13. https://doi.org/10.3389/fvets.2020.544707.
Zhoudong, J., Wang, Q., Libohova, Z., Adhikari, K., Brye, K.R., Sun, Z., Sun, F., Jiang, Y., Owens, P.R. 2021. Fe-Mn concentrations in upland loess soils in mid-continental north America: A step towards dynamic soil survey. Catena. 202:105273. https://doi.org/10.1016/j.catena.2021.105273.
Jiang, Z., Wang, Q., Brye, K.R., Adhikari, K., Sun, F., Sun, Z., Chen, S., Owens, P.R. 2020. Quantifying organic carbon stocks using a stereological profile imaging method to account for rock fragments in stony soils. Geoderma. 385:114837. https://doi.org/10.1016/j.geoderma.2020.114837.
Jiang, Z., Wang, Q., Adhikari, K., Brye, K.R., Sun, Z., Sun, F., Owens, P.R. 2020. A vertical profile imaging method for quantifying rock fragments in gravelly soil. Catena. 193:104590. https://doi.org/10.1016/j.catena.2020.104590.
Sorokin, A., Owens, P.R., Lang, V., Zhou-Dong, J., Micheli, E., Krasilnikov, P.V. 2020. "Black soils" in the Russian Soil Classification system, the US Soil Taxonomy and the WRB: quantitative correlation and implications for pedodiversity assessment. Catena. 196:104824. https://doi.org/10.1016/j.catena.2020.104824.
Franco Jr, J.G., Gramig, G., Kenneth, B., Hendrickson, J.R. 2021. Cover crop mixtures enhance stability but not productivity in a semi-arid climate. Agronomy Journal. 113(3):2664-2680. https://doi.org/10.1002/agj2.20695.
Jiang, Y., Sun, Z., Owens, P.R., Adhikari, K., Wang, Q., Dorantes, M.J., Read, J.J., Ashworth, A.J., Libohova, Z. 2019. Spatial distribution of soil phosphorus, calcium, and pH after long-term broiler litter application. Journal of Environmental Quality. 48:594-602. https://doi.org/10.2134/jeq2018.11.0406.
Mechineni, A., Kommuru, D.S., Terrill, T.H., Kouakou, B., Lee, J.H., Gujja, S., Burke, J.M., Kannan, G. 2020. Forage type and transportation stress effects on gut microbial counts and meat quality in goats. Canadian Journal of Animal Science. 00:1-8. https://doi.org/10.1139/cjas-2019-0145.
Acharya, R.S., Leslie, T., Fitting, E.P., Burke, J.M., Loftin, K., Joshi, N.K. 2021. Color of pan trap influences sampling of bees in livestock pasture ecosystem. Biology. 10(445):1-14. https://doi.org/10.3390/biology10050445.
Owens, P.R., Dorantes, M.J., Fuuentes, B., Libohova, Z., Schmidt, A. 2020. Taking Digital Soil Mapping to the Field: Lessons learned from the Water Smart Agriculture soil mapping project in Central America. Geoderma Regional. 22:e00285. https://doi.org/10.1016/j.geodrs.2020.e00285.
Nieman, C.C., Schaefer, D.M., Maroney, M., Nelson, K., Albrecht, K.A. 2020. Hepatogenous photosensitivity outbreak after coccidiosis in grazing Holstein steers. Veterinary Sciences. 7(4):186. https://doi.org/10.3390/vetsci7040186.