Location: Genetics and Sustainable Agriculture Research
2021 Annual Report
Objectives
1. Develop more sustainable long-term soil health management systems for improved yields from humid, Southeast Agroecosystems.
1.1. Increase row crop yields in the upland soils of the South and Southeast by agronomic practices that improve soil physical and biological properties including application of organic- and inorganic-amendments and planting cover crops.
1.2. Develop soil water management strategies to increase the capture and storage of rain water in soil, minimize yield-robbing drought effects, and increase dryland and irrigated crop production in the South and Southeast.
1.3. Determine the environmental impact in soil, water, and air of proposed novel agronomic approaches on antibiotic resistance, emissions, and nutrient risks.
2. Develop improved decision support tools and technologies based on GxExM to optimize water use efficiency of rainfall and irrigation water for better yields from humid, Southeast Agroecosystems.
2.1. Develop techniques that utilize and integrate high resolution row crop canopy spectral images gathered during the growing season for in-season water management in cropping systems and fields characterized by high soil variability.
2.2. Implement databases, modeling tools, and decision-making paradigms for optimizing water management and crop yield.
3: Develop, optimize, and streamline a UAS operational system for agricultural research and pilot a regional ARS resource for improved data collection from UAS. The system will include: UAV selection process; UAV sensor selection process; flight planning; holistic software system to generate mosaics; handling potential PII information; and UAS-agronomic software that produces specific agronomic data from mosaics. The goals of this holistic system include data standardization and integration, development and release of new UAS technologies and capabilities, and increased ability for our UAS research to rapidly adapt to evolving technologies and policies. (NP216 C1: P1A; C4: P4A, P4B)
Approach
Several multi-year field plots will be established. These include a) cover crops for the major row cropping systems in then the southeast, b) planting various configurations of mixed cover crop species, c) cropping systems for land leveled fields, d) stabilizing dryland soybean production using cover crops and poultry litter, e) deep rooted cover crops and soil amendments and, f) cover crops and water use efficiency. From these field experiments we will measure effects on environmental quality, greenhouse gas emissions, and economics of each of the systems; environmental quality and antimicrobial resistance in each of the systems; contribution of soil organic matter to plant available water content in each of the systems; we will optimize yield by managing field variability, we will utilize high resolution thermal imaging to optimize irrigation management and we will model soil water requirements in each of the systems.
Progress Report
Field studies were designed to study integrated diverse winter cover crops with fall-applied poultry litter coupled with cotton or corn cash crops. Soil samples were collected from all studies. Soil biological analysis from all samples collected in FY 21 were processed for critical assays only. Critical litter bags were collected from in situ incubations to determine mass reductions. Soil samples were collected after harvest and analyzed for residual nitrate-N. Hundreds of samples have been archived for future DNA extraction and analysis. Only limited samples were extracted for DNA and processed. Samples were processed for enzyme and culture-based work for all studies, since these are critical assays. Sample DNA from a previous study were sequenced and analyzed. For Exp C, emission (soil CO2 flux via LiCor survey chamber) measurements have been taken at significant crop growth stages to coincide with litter bag collection as well as soil nutrient and biological evaluations. Similar methods at a reduced frequency were conducted for Exp B.
A complete dataset of this first year study has been gathered. These data include cover crop biomass separate by species, initial soil chemical properties, and cotton yield and growth. The data show the level of competition between the two cover crop species in the study (cereal rye and crimson clover) when planted as a mixed stand and the reduction of the competition when planted separately in alternating rows. Cotton planted after growing a cereal rye cover crop produced less and did not grow as tall as cotton planted on soil that did not have cover crop. This yield drag due to the cereal rye cover crop was also evident when the cotton received 2 ton/acre poultry litter in the fall. Cotton performed best after the legume crimson clover as the cover crop with or without poultry litter. The second year test has been started after taking soil samples and cover crop planted according to plan following fall poultry litter application. The second-year cover crop has been terminated and cotton has been planted as the second-year cash crop.
In accordance with the research objectives of this project works began to establish multisource remote sensing analytics to enhance crop field monitoring and control in the region of concern covering the experimental sites spread in eastern Mississippi. The new system with remote sensing big data operational and analytic protocols are creating in high-performance computing platform and standalone workstation with selected software and algorithms. Imagery of satellite and unmanned aerial system (UAS) have been acquired for potential studies of cover crops and other agronomic treatment and measurements. NASA SMAP L3 soil moisture products (36km, 9km and 1km (USDA NASS)) have been investigated over the state of Mississippi. Also, NASA MODIS LAI (500m) and NDVI (250m) products have also been investigated over the state of Mississippi. USGS Landsat 8 (30m), ESA Sentinel 2 (10m) and PlanetScope (3m) images have been investigated for classification of crop types in the regions within Mississippi based on the data of SMAP and MODIS. UAS imaging has been routinely performed to cover the fields of experiment B, C, D and E. The sensor used for experiment B, D and E has the broad bands of RGB and narrow bands of green, red, red edge and near infrared (NIR) while the senor used for experiment C has the narrow bands of blue, red, red edge and NIR in addition to thermal. The UAS data are for field analysis and scale up/down from the satellite data.
A field study was established to study integration of cover crop with animal and industrial byproducts to improve soil quality and crop yield. Cover crop was planted and killed, while treatments were applied prior to corn planting. Cover crop biomass was collected and recorded, while soil samples post cover crop kill and during the season were collected. Soil samples were collected and analyzed for critical biological and nutrient analyses. Lysimeter were deployed and water volumes were collected. Corn yield was recorded, and dry matter was recorded. Sensors were deployed to monitor soil moisture and temperature. Exp E emission (soil CO2 flux via LiCor survey chamber) measurements have been taken at significant crop growth stages to coincide with litter bag collection as well as soil nutrient and biological evaluations. For Exp D., 30 tubes of PR2 soil moisture measuring probes were installed. Biweekly soil moisture, leaf area index, plant height, plant cover, phenology, biomass, and leaf N using SPAD will be measured. Undisturbed soil core samples were collected at multiple depths from 30 plots early in the summer, and soil physical and hydrological properties were measured.
This relatively long-term study that involves five cover crop treatments and three fertility treatments is in its fourth year. In the fourth year as in the previous years, these cover crops and the fertility treatments were imposed in the fall and soybean planted in the spring at two planting dates. Data collected in collaboration with Mississippi State University included cover crop biomass, soil chemical analysis, soybean leaf area index, soybean chlorophyll index, and soybean yield. The data show that soybean fertilized with 2 ton/acre poultry litter grew much larger than soybean fertilized with four recommended fertilizers (phosphorus, potash, sulfur, and zinc). This suggests using poultry litter at this low rate in poor soils may be more effective and profitable than using multiple synthetic fertilizers. The cover crops showed some effects on soybean but these effects were not consistent and distinct after four years of testing. Benefits of continuing planting cover crops for more than four years is not indicated in this study at this point. The positive effects of poultry litter on soybean yield and growth have been immediate, distinct, and likely profitable.
Intact soil cores were extracted from field plots that received either no fertilization (control) or pelleted biosolids at a single, high rate of 37 Mg ha-1 (1,500 kg ha-1 total N and 10,180 kg ha-1 total C). The first cycle of a greenhouse study has begun. Soil samples from all experiments have been collected and archived for future DNA extraction and ARG assays.
A study that tests whether poultry litter alleviates Mn toxicity in cotton was continued in the same field. Limed and unlimed plots from a year ago were fertilized with either poultry litter, recommended synthetic N and other fertilizers, or left unfertilized. Data collected included soil chemical properties, leaf nutrient content, leaf are index, chlorophyll index, cotton lint yield, and plant height. The results show that liming is effective for reducing leaf manganese content in the acidic soil whether the cotton was unfertilized or fertilized with poultry litter. But this reduction in tissue manganese content did not lead to improved cotton yield. Fertilizing with poultry litter greatly increased cotton yield but the increases may not be due to the reduction in manganese alleviation. The ability of poultry litter to provide all nutrients needed for healthy plant growth and production probably alleviated nutrient shortage undiagnosed by typical soil testing.
Data collection protocols were developed and enhanced for high-throughput data streams with appropriate quality control procedures and innovative data management strategies were reviewed. In conjunction with NPS, three data collection software with unique data entry templates were preliminarily selected: 1) Farm Management (FM) for field operation event and background data collection, 2) Sample Master® Laboratory Information Management System from Accelerated Technology Laboratories (ATL-SM-LIMS) for GSARU Nutrient Analysis Laboratory, 3) ArcGIS Velocity from Esri for UAS/Drone Data collection. As software as a service (SaaS), these tools will connect with Microsoft Azure cloud, where the Decision Support Information (DSI) Platform of PDI will benefit GSARU scientists for scientific data mining, data integrity, and decision making. FM has been customized within the GSARU research environment and preliminarily optimized. GPS coordination data and field event data loading to the system is ongoing. Specification and functionality of ATL-SM-LIMS is carefully reviewed by most of potential users, and AAR is approved for the purchasing. ArcGIS Velocity will be introduced when the new GIS scientist is on board.
Through a Non-Assistance Cooperative Agreement (NACA) Mississippi State University studied management and stress-induced changes in plant health, influence of cover crops on cash crop, early detection of root-knot-nematode infestation, impacts of temperature on cover crop vegetative growth, applying radio frequency microwave using remote sensing from UAS for soil moisture mapping, and machine learning algorithms to estimate soil moisture from hyperspectral imagery. Through a NACA North Dakota State University validated and optimized current active-optical sensor algorithms using GreenSeeker RNDVI and Holland Scientific crop circle sensors with RNDVI and RENDVI for corn for spring wheat they developed algorithms for in season Nitrogen to optimize for yields during tillering, for protein at flag leaf, and began collecting data for yield enhancement algorithms for barley. Working with Grant Farm test site where research is translated into technology transfer via public-private partnerships. Established partnerships with 3 cooperating farmers in Red River Valley on fields with severe variability due to poor drainage and salt accumulation. Using remotely sensed data in determining variety qualities in breeding. An automous weed bot is learning to phenotype six major weeds Near InfraRed, multispectral, 3D and Red, Green, Blue. Developing a dataset to compare with revenue and cost to develop a model to estimate stochastic returns from adopting precision ag technologies.
Accomplishments
1. Nitrogen (N) fertilizer is a costly agriculture input for cotton growers and has narrowed grower's profits. Interest in using poultry litter as an alternative source of pant nutrients for cotton production has increased in the region. However, litter applications decompose rapidly, particularly in hot and humid south, and its derived-N losses through volatilization and leaching, reduces crop N use efficiency and poses a threat to the environmental pollution. Biochar and lignite have the potential to reduce N loss due to their cation and anion exchange capacity and water holding capacity. ARS researchers in Mississippi State, Mississippi, in collaboration with researchers at Mississippi State University, have discovered that the combination of biochar and lignite with poultry litter resulted in greater lint yield and N utilization and lower NO3-N in drainage as compared to poultry litter alone treatments. This management practice offers a novel approach to promote crop productivity, while reducing the environmental risk, could be used as a sustainable agronomical strategy.
2. Hen age affected manure characteristics but vaccination and dietary supplements did not. To sustain commercial egg production, innovative dietary inputs, their interaction with disease control agents, and effects on all aspects of the production system and bird health must be investigated. ARS researchers in Mississippi State, Mississippi, studied commercial layer chickens’ inoculation with F-strain Mycoplasma gallisepticum (FMG) and having diets supplemented with phytase (to make phosphorus in corn more available) and vitamin D3 (for improved performance and Ca retention) to determine the effects on manure characteristics. Of the studied parameters, only hen age affected the manure parameters by decreasing moisture content (4%) and generally increasing nitrogen (53%), carbon (7%), potassium (19%), and Zn (44%). The potential impact is that integrators need not be concerned that the supplemented diets or FMG inoculation will incur manure handling changes, but that changes in mineral excretion can be significant as hens age. Further, the data provide a resource for national manure inventories.
3. DNA sequencing reveals impact of fertilizer. Choice of fertilizer has an influence on the soil quality as well as crop yields. Fertilizer choice is often dictated by location and proximity to fertilizer sources, such as concentrated animal feeding operations or municipal wastewater treatment plants. However, the selection of fertilizer can also influence the soil microbiota as well as pathogen release into the environment. ARS researchers in Mississippi State, Mississippi, determined that use of various solid and liquid waste fertilizer products selects for specific soil microbiota beneath forage, as well as introduced pathogens and antimicrobial resistance. Land application typically begins in the spring, followed by harvest in early fall. Overall, pathogen levels dropped to control levels within weeks of application, while the influence on the soil microbiota was established early in the season. Antimicrobial resistance and associated genes dropped to control levels by the end of the season, however some elevated levels persisted. Returning to the site 4 years later showed little influence on the microbiota as qualitative and quantitative data suggested a return to near baseline levels. This indicates that fertilizer choice has a strong influence on the soil microbiota during season but requires reoccuring input.
4. Potassium-deficient wheat leaves have few if any sensitive spectral indicators of physiological stress. Leaf reflectance at specific wavelengths is associated with nitrogen (N) deficiency, but studies on spectral reflectance and potassium (K) deficiency are lacking. Two winter wheat varieties, Coker and Magnolia, were grown with and without N and K for 35 days in a greenhouse by ARS researchers in Mississippi State, Mississippi. Withholding K from the nutrient solution induced a 70% reduction in leaf K and a 8% reduction in carotenoids, without affecting total chlorophyll. As a result, a weak correlation was obtained between leaf K and chlorophyll (r2=0.15; P<0.05). Approximately 20% of the variation in leaf K was accounted for by reflectance (R) at 655 nm, with 24% of variation accounted for by a single-band ratio, R655/R380. Measurements of spectral properties in wheat are useful for detecting early nutrient deficiencies if the specific mineral deficiency is known.
5. Napiergrass is a highly productive forage and bioenergy crop with swine-effluent fertilization. In a three-year study (2011-2013) at a private swine farm in northeast Mississippi by ARS researchers in Mississippi State, Mississippi, ‘Merkeron’ napiergrass harvested in November removed 92% of nitrogen (N) and 73% of phosphorus (P) applied in lagoon effluent in 2013, the peak year of production (59 Mg ha-1). This can benefit swine farms that apply effluent to summer forage grasses grown for hay, as irrigation rates are determined by crop nutrient requirements coupled with soil N and P levels. Leaves harvested from mature plants are a forage product that would meet nutritional standards as animal fodder, but corresponding stems had lower forage nutritive value. Ethanol yield was approximately 36% lower in stems than leaves (98 vs. 153 g kg-1) and xylose yield was 7% lower (170 vs 183 g kg-1); however, stems account for a larger amount of lignocellulosic biomass. Potential ethanol yield was approximately 109 g kg-1 grass biomass, which corresponds to 139 L Mg-1 biomass.
6. Cover crop is considered as one of strategies to reduce rain-water loss and mitigate rainfed crop water stress. The impact of cover crop (CC) on soil water balance and agricultural production is closely depended on rainfall amount and distribution. ARS researchers in Mississippi State, Mississippi, applied RZWQM2 to investigate the impact of wheat CC on rainwater balance and use efficiency (WUE, grain yield per unit of evapotranspiration) in rainfed corn and soybean rotation under different rainfall patterns in eastern Mississippi.
7. Remote sensing data can be integrated into crop field monitoring.. Monitoring frequency needs to be adjusted for cloud cover, since this can be a problem for use of satellite imagery with relatively long revisiting cycles, such as 16 days of Landsat 8. MODIS and Planet both have high revisiting cycles (daily for raw data) to ensure the capture of images of some clear days from June to August in this area.
8. A new alternative method of poultry litter management strategy. Approximately 15 to 20% of poultry litter is composed of mineral elements needed for healthy plant growth. When litter is applied to the same field continuously for several years as a fertilizer, some of these elements such as phosphorus (P) accumulate in the soil and become a concern for environmental contamination if washed off to non-target surfaces such as water bodies. Currently, the most recommended management practice to prevent excess nutrient buildup in the soil is to apply just enough litter to meet the P need of the crop
9. Decomposition of manure in soil can be slowed with inorganic byproducts. One important purpose of applying manures to soils is to increase its level of organic matter since soils with high organic matter are productive. But manures, once applied and mixed with the soil, decompose quickly, and dissipate as carbon dioxide (CO2) leaving very little trace of organic matter in the soil.
Review Publications
Li, G., Huang, Y., Chen, Z., Chesser Jr, G.D., Zhao, Y., Purswell, J.L., Linhoss, J. 2021. Practices and applications of convolutional neural network-based computer vision systems in animal farming: a review. Sensors. 21(4):1492. https://doi.org/10.3390/s21041492.
Read, J.J., Adeli, A., Fairbrother, T.E. 2020. Harvest management effects on bermudagrass yield and nutrient utilization in a swine-effluent spray field. Journal of the Mississippi Academy of Sciences. 65:3.
Thakali, O., Tandukar, S., Brooks, J.P., Sherchan, S.P., Sherchand, J.B., Haramoto, E. 2020. The occurrence of antibiotic resistance genes in an urban river in nepal. Water. 12:450. https://doi.org/10.3390/w12020450.
Firth, A.G., Baker, B.H., Brooks, J.P., Smith, R.K., Iglay, R.B., Davis, J.B. 2020. Investigation of pathogenic bacterial transport by waterbirds: A case study of flooded and non-flooded rice systems in Mississippi. Water. 12:1833. https://doi.org/10.3390/w12061833.
Ouyang, Y., Zhang, J., Feng, G.G., Wan, Y., Leininger, T.D. 2020. A century of precipitation trends in forest lands of the Lower Mississippi River Alluvial Valley. Scientific Reports. 10:12802. https://doi.org/10.1038/s41598-020-69508-8.
Miles, D.M., Adeli, A., Brooks, J.P. 2020. Lignite coal and biochar reduce ammonia emissions from broiler litter. Journal of Agriculture and Environmental Science. 19(3):137-141. https://doi.org/10.3923/ijps.2020.137.141.
