Research Project: Closing the Yield Gap of Cotton, Corn, and Soybean in the Humid Southeast with More Sustainable Cropping Systems

Location: Genetics and Sustainable Agriculture Research

2023 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
Results from the first-year harvest were affected by a dry corn growing season but clearly showed that both vetch and crimson clover supplied substantial amount of N to corn. Preliminary data so far collected suggest that the practice of planting corn without killing the cover crop is a feasible practice to partially meet the N need of corn from legume cover crops. This experiment was designed to test whether competition between two cover crop species when planted as a mixed stand can be reduced if planted in alternate drill rows. Preliminary results show that cotton reflected the residual effect from the cover crop and poultry litter treatments imposed in the previous two years. But this effect seemed somewhat muted due to the extremely dry June and July the cotton experienced. The study aimed to achieve a balance between nitrogen supply and crop demand to optimize yield, improve soil health, and protect the environment. To evaluate the leaching loss of nutrients as a function of the cover crop growth period, suction cup lysimeters were installed in the field. Before cover crop termination, aboveground biomass was collected, dry matter yield recorded and analyzed for nutrient contents. In-situ litter bags were used to determine cover crop residue decomposition rate during the cash crop growing season. At the end of the growing season, an electrical conductivity mapper and digital penetrometer will be used to map the soil carbon and soil resistance, respectively. The residual effects of soil amendments applied in previous years on corn nutrient utilization and grain yield were evaluated as the presence of cover crop residues. Field sampling and uncrewed aerial vehicle (UAV) surveys were completed on three additional agricultural field sites in 2022 with three more planned for summer of 2023. Altogether, the dataset will include soil carbon stock estimates to 120 cm depth and 2,160 individual soil samples, coinciding with sensor estimates, and spanning nine farms distributed across the Red River Valley in North Dakota. Soil biological measurements were made on Exp C and E. Samples were collected throughout the cover crop and growing seasons. An investigation into the spatial variability was completed in conjunction with Mississippi State University, while additional samples were collected for an investigation on the effect of anthropogenic and environmental pressures on soil health biological indicators. Extracted DNA was processed for all studies. Fecal indicator bacteria were quantified and isolated from a collaborative study with Mississippi State University (MSU). A study on the presence and spatial distribution of wildlife (bear, duck, vulture, turkey, rabbit, and deer) antimicrobial resistance and genes was expanded. Greenhouse gas emissions continue to be monitored in Mississippi cropping systems integrating the efforts of the USDA-ARS Genetics and Sustainable Agriculture and Mississippi State University (MSU) Geosystems Research Institute (GRI). Recent progress includes uncrewed aerial vehicles (UAV)-carbon dioxide (CO2) system development and application, as well as new simultaneous ground measurement of nitrous oxide (N2O) and CO2 flux. In addition, a recent experiment investigating the effect of cover crop coverage percentage on the evolution of CO2 flux. Mississippi State University (MSU) - Conducted seven in situ flights to compare the atmospheric carbon dioxide (CO2) concentration above a corn field and its adjacent bare soil field using the uncrewed aerial vehicle (UAV)-CO2 system. Over seven flights of low altitude, the carbon dioxide (CO2) concentration above the bare field consistently showed significantly higher values than that above the corn field. The preliminary analysis on nitrous oxide (N2O) emission during cover crop season revealed that pea was prone to increase soil N2O emission. A small-size uncrewed aerial system (UAS) was outfitted with surface reflected Global Navigation Satellite System (GNSS) signals. We used a U-blox application board and a linear polarized antenna as the GNSS receiver to receive and record the reflected GNSS signal. To collect ground truth soil moisture (SM) measurements, 26 SM probes were deployed. For each observation, specular reflection points are calculated using the current UAS location and the orbit data of GNSS satellites. The study results show that the collected data from a GNSS receiver is enough to estimate surface SM in relatively low vegetated conditions. This experiment was designed to develop irrigation management with high resolution crop thermal images collected using uncrewed aerial vehicle (UAV)s. For this to be effective, a dry period of about 2 to 3 weeks during which the cotton crop enters some degree of water stress after the flowering stage would be ideal. Such a period did not occur in all four years this study was carried out. There was no visible water stress on the cotton in any of the years during the flowering or later growth stages. Further simulation modeling using model root zone water quality model (RZWQM2) under long-term diverse weather conditions assisted field experiments to determine the following results which were difficult or impossible for field studies to obtain. As compared with no CC scenario, model estimates indicated planting CC increased soybean yield. Long-term use of winter wheat CC, if managed similarly, can increase soil water storage. The root zone water quality model (RZWQM2) also determined the effect of wheat winter cover crop (WCC) on net nitrogen (N) mineralization and nitrate leaching in a 80-yr (1938 to 2017) corn-soybean rotation and soil water balance and dynamic under future 60-yr (2020-2079) climate conditions, in Mississippi Blackland Prairie. North Dakota State University (NDSU) - Additional data was collected in the greenhouse and at three field locations contributing to the large image dataset with different sensors red, green, blue (RGB), multispectral, hyperspectral, thermal, six different weed species, and eight crops. This image database is key to development of effective machine learning algorithms for weed identification. A new version of the multifunctional robotic platform (patent pending) was developed to conduct research on this objective. Mississippi State University (MSU) - We collected uncrewed ground vehicle (UGV) data at The R. R. Foil Plant Science Research Center, Mississippi State University, Mississippi State, MS. We collected a total of four initial datasets in corn and cotton rows. These datasets will be used to assess the trajectory quality from the Global Navigation Satellite System (GNSS) unit, point cloud density, and quality from light detection (LIDAR), red, green, blue (RGB), and multispectral camera calibration and orientation. Uncrewed aerial system (UAS) and Imaging: In accordance with the research Objectives 1 and 2 of this project, UAS remote sensing has been focused to continue establishing multisource remote sensing analytics to enhance crop field monitoring and control. Images have been acquired continuously from UAS in accordance with the imagery collected from satellite platforms for studies of cover crops and other agronomic treatment and measurements. The UAS data are for field analysis and scale up/down from the satellite data. North Dakota State University (NDSU) - The Big Data Pipeline Unit (BDPU) developed R scripts that allow users with little or no programming experience to run genomic prediction models using frequentist and Bayesian approaches. Genovix, a commercial database management platform for breeding trials and varietal selection, was successfully launched and released across the state at multiple NDSU Research Extension Centers where experimental trials are grown. The BDPU successfully deployed v1.3.1 of FielDHub, the Design of Experiments (DoE) App with advanced features such as sparse allocation algorithm and multi-location partially replicated designs to further optimize resource allocation on the field. A graduate student thesis was completed on assessing economic viability of site-specific weed management technology. The results from this work will aid in guiding future research direction for the technology and can be crafted into decision tools for farmers considering adoption. Data Management: Data collection, following ARS data integrity, from the unit wide NP 216 research project is a core objective. Additionally, throughout the year, raw data collection implementation is the major focus. Three raw data collection engines have been defined. For field operation data, Farm Management App has been successfully deployed along with the Research Tool, both from ARS PDI. The challenge is how to download the historical data from the APP efficiently and with research unit specific security. A relational database for laboratory data collection was initiated, and their integrated data format has been established. Site Scan for ArcGIS from Esri was evaluated as a raw drone data collection system and is good to move forward for formal implementation after the licenses are available from ARS PDI.

Accomplishments
1. Runoff in upland soils is very likely. Upland soils have low organic matter and are prone to water and nutrient losses during rainfall events, which can adversely affect non-irrigated crops, leading to reduced yields and economic losses. The insufficient availability of soil moisture during the critical growth stage of corn, particularly during grain filling, poses a significant limitation to production and consistent yield. ARS researchers in Starkville, Mississippi, in collaboration with researchers at Mississippi State University, discovered that integration of soil amendments such as lignite and flue gas desulfurization (FGD) gypsum with poultry litter and inorganic fertilizer N in the presence of cover crop residues increased soil organic carbon, reduced greenhouse gas emissions, improved soil infiltration and water storage capacity, conserved soil moisture and increased corn grain yield. This innovative management practice offers a novel approach for sustainable agricultural practices that promote both environmental and agronomic benefits for the growers.

2. An integrated scheme of remote sensing data and algorithms is suggested for advanced crop field monitoring, analysis, and interpretation. ARS researchers in Starkville, Mississippi, suggest this scheme for systemically conducting crop growth process modeling and analysis. This scheme includes data integration, algorithm integration and the pipeline between them. The data integration is to aggregate multisource remote sensing data, especially from UAS remote sensing, for developing a remote sensing big data platform. The algorithm integration is packages algorithms (statistics, pattern recognition and machine/deep learning) and their combinations and ensembles, which is pipelined with data integration for advanced crop growth process modeling, optimization, and control.

3. Correlating the effects of agronomic decisions at the molecular and chemical level to agronomic yields is difficult but possible. For this reason, it is often difficult to suggest one conservation practice to all land managers. ARS researchers in Starkville, Mississippi, in collaboration with MSU researchers utilized a structured decision-making paradigm to elucidate the effects of agronomic decisions at the molecular level and predict agronomic potentialities. Empirically collected data from a small plot field study was utilized in predictive models to suggest which indicator was most useful in ultimate model performance. Ultimately, soil carbon, genes predicting enzyme presence, and other environmental parameters were useful in the model and suggested that farmers/managers could utilize this approach to predict outcomes based on agronomic management, for example, the use of cover crop practices were most beneficial in a no till management to minimize losses and maintain soil C sequestration. Carbon credit systems could offset losses in yield when adopting climate-smart actions. As the need for yield outcomes balanced with ecosystem benefit increases in soil health research, the use of models more traditionally utilized in ecological management can be employed to predict outcomes of management practices. These outcomes can be based on fine resolution datasets such as carbon dioxide (CO2), soil carbon (C), and deoxyribose nucleic acid (DNA) to improve models at the molecular or chemical level which may provide the granularity needed to explain difficulties in management implementation.

4. Incorporating litter increased carbon dioxide (CO2) emission, but gypsum and lignite mitigated the effect. Agroecosystem resiliency seems a lofty goal but combined best management practices like soil amendments, organic fertilizer, and cover crops show promise although soil carbon dioxide (CO2) emissions are expected to increase with cover crops. ARS researchers in Starkville, Mississippi, incorporated flue gas desulfurization (FGD) gypsum and lignite with broiler litter application in a no-till corn study and found reduced soil CO2 emission with the amendments compared to litter alone. After the 3rd year of study, soil CO2 emission was greater in cover crops versus no cover crop, but the cover crop plots had more total carbon indicating increased carbon storage. In addition, cover crop plots had lower soil temperature, increased soil moisture, better soil infiltration, and higher corn yield. Use of FGD gypsum, lignite, and broiler litter enhanced soil properties and crop yield as a strategy for long term sustainability.

5. Poultry litter proved to be a superior fertilizer for dryland soybean production but incorporating cover crops into soybean cropping systems may be challenging. Dryland soybean farmers in the southeastern US face the challenge of poor production due to rainfall shortage. Incorporating cover crops and possibly poultry litter into their production systems may reduce the risk of yield loss and increase the profitability of soybean farming. ARS researchers in Starkville, Mississippi, and Mississippi State University researchers recently completed a 5-year study investigating the benefits of four different cover crop species in combination with two fertilizers to dryland soybean production in an eroded marginally productive upland soil in Mississippi. Each of the five years, the cover crops were planted in the fall and soybean was planted in the spring after chemically killing the cover crops and applying either poultry litter or synthetic fertilizers recommended based soil test results. The results showed that soybean fertilized with 2 ton/acre poultry litter grew much larger and produced 13% (7 bu/acre) more seed yield than soybean fertilized with four fertilizers (phosphorus, potash, sulfur, and zinc). But the commonly discussed benefits of cover crops did not manifest in soybean growth or yield in any of the 5 years. Winter planting any of the cover crops which included winter wheat, cereal rye, vetch, or mustard + cereal rye, relative to planting no cover crop which is the most common practice by soybean farmers, did not lead to any clear soybean yield increase. This shows that, without a clear soybean yield advantage, the adoption of cover crops for sustainable soybean cropping systems by soybean farmers in the region will be challenging. The 7 bu/acre yield advantage from fertilizing with poultry litter, however, is a good incentive that will likely lead to the inclusion of poultry litter as a key component of sustainable cropping systems in the southeastern United States.

6. Identifying indicators that are important for assessing soil health. Monitoring soil health and understanding the importance of specific indicators is necessary to apply a measurable metric to agronomic managements. ARS researchers in Starkville, Mississippi, location collected data for chemical, physical and biological indicators obtained from three treatments (no-fertilized control, no-organic fertilizer and poultry litter) in five different field experiments were used to screen a Minimum Data Set (MDS). The methodology followed a combination of principal component analysis (PCA), cluster analysis and expert’s opinion (EO) method. Results showed that the correlation between the MDS and total data set (TDS) was high (R2 =0.94). The chosen MDS included four chemical indicators (pH, organic carbon, total nitrogen and Mehlich-3 phosphorus), three physical indicators (bulk density, water-stable aggregate stability, available water capacity), and two soil biological indicators (dehydrogenase activity, heterotrophic plate count). When the selected chemical MDS was applied to all treatments of the five experiments, the MDS and TDS data fitted well (R2 =0.81), indicating that the soil indicators included in the MDS were the most important for soil health in this study. In conclusion, a MDS for soil health assessment was established for the experiments in northeast Mississippi. The results can provide fundamental guidance for researchers, growers, and stakeholders to evaluate soil health and optimize soil management.

7. Utilizing 80 years of cropping demonstrated winter cover crop increased annual N mineralization. ARS researchers in Starkville, Mississippi, location used 80 years of root zone water quality model (RZWQM2)-simulation demonstrated that, compared to winter fallow system, planting winter wheat cover crop (CC) into a corn-soybean system increased annual Nitorgen (N) mineralization by 15% (19 Ibs N ac-1), improved annual denitrification by 9% (1 Ibs N ac-1), and reduced annual nitrate loss to deep percolation by 20% (15 Ibs N ac-1). On the basis of a full year simulation, the wheat winter CC grown from early October to early April led to a 24% reduction in nitrate-N leaching (14 Ibs N ac-1). The efficacy of wheat winter CC in reducing nitrate leaching was better in wetter than dry winter months. Incorporating wheat winter CC into corn-soybean rotation is effective for promoting nitrogen mineralization and reducing nitrate loads to drainage deep percolation in humid regions.

8. End-to-end workflow tested for Site-Specific-Weed Control (SSWC). Herbicide application for weed control is a significant input cost for farmers. Traditional practice has been to apply herbicide across the entire field. New technology is emerging for SSWC, but at significant cost as it requires a new sprayer be purchased. North Dakota State University researchers through a cooperative agreement with ARS researchers in Starkville, Mississippi, developed and demonstrated a workflow using imagery captured by uncrewed aircraft systems (UAS) to discern weeds from crop plants (corn in this case), produce a prescription weed control map, and apply herbicide using existing commercial sprayer technology (with individual nozzle control) according to the prescription. A 50% reduction in the amount of herbicide applied was achieved in the field trial. The successful outcome has led to a larger scale test in 2023 by a cooperating North Dakota farmer to evaluate the workflow for other row crops and weed control methods.

9. Design of experiment (DoE) application for crop breeding trials achieves milestone. Development of new crop varieties is a well-established and methodical, but time-consuming process. Many years of development and testing precede the release of a new variety. Advanced software tools, databases, and analytics can improve efficiency and accelerate this process. North Dakota State University researchers through a cooperative agreement with ARS researchers in Starkville, Mississippi, in collaboration with partners have developed a suite of applications for this purpose. An updated version of FielDHub (v1.3.1), a design of experiments application, was released this year with advanced features to further optimize resource allocation in field trials. This open-source application recently surpassed 10,000 downloads with users worldwide since the initial version was released. This metric indicates a significant impact that extends far beyond the university’s own crop variety development programs.

10. Impact of soil moisture stress on leaf reflectance properties. Physiological, biochemical, and plant health factors influence leaf reflectance properties in response to stressors. Moisture stress imposed during maize pollination and grain filling had adverse effects on leaf reflectance properties associated with plant health and yield potential. Researchers at Mississippi State University through a cooperative agreement with ARS researchers in Starkville, Mississippi, assessed the influence of these factors on remote sensing. Further, drought stress-induced changes in greenness-related vegetation indices (CIgreen, CIred-edge, and Chlorophyll vegetation index) had an agreement with variations noted with manually measured plant health traits. Significant correlations between vegetation indices and yield components indicated that ear-leaf spectral reflectance properties can be used as proxy indicators to capture stress-induced variations in plant health. This study highlights the potential of using proximal sensing as a reliable and efficient screening platform for stress tolerance in crops.

11. Predicting yield under cropping systems. Using high-resolution temporal uncrewed aerial vehicle (UAV) imagery data, over 50 vegetation indices (VIs) were extracted at different growth phases of corn over three years. Researchers at Mississippi State University through a cooperative agreement with ARS researchers in Starkville, Mississippi, used a combination of either blue or red, Red Edge and near infra red (NIR)-based vegetative index (VI)s had a strong correlation with corn yield under rainfed cover cropping systems. Three-year results showed the best time to collect UAV data for yield estimation is around the reproductive and early-grain filling. Similarly, imagery data from three cotton growing seasons were used to determine how well canopy cover or fiber pixel area index explained yield variability. The canopy cover of cotton was moderately correlated with a yield (R2 of 0.44 to 0.68) under cover cropping systems. A strong correlation (R2 = 0.80) between the fiber pixel area index and cotton yield showed the potential applicability of UAV for estimating in-season cotton yield, as well as for monitoring cotton growth and development. Depending on the growth stage and crop, different VI's are important. Based on remote sensing data, pea is the most beneficial cover crop to be planted during fallow periods, as it can significantly improve the health of any cash crop.

12. Row crops’ response to stressors. Trait-based breeding relies on the identification of contrasting genotypes with specific secondary traits linked with yield. Projected climate change scenarios, including changes in temperature, precipitation, and soil quality, pose challenges to crop production. Researchers at Mississippi State University through a cooperative agreement with ARS researchers in Starkville, Mississippi, investigated these row crop responses. Exposure of cotton to these stressors substantially reduced the early-season growth and development processes. In response to stressors, there was a shift in resource partitioning towards roots rather than shoots. Tolerant genotypes exhibited less disruption in physiology and growth compared to susceptible genotypes. Natural variation in phenotypic traits related to plant health and biomass production is another potential source for crop improvement. The trade-off between pigment concentration and leaf size is evident in soybean, where chlorophyll content is significantly and negatively correlated with specific leaf area. A positive correlation was observed between above-ground biomass variability and both plant height and node numbers, highlighting their role in biomass accumulation. The soybean accessions exhibited extensive phenotypic diversity related to plant vigor, demonstrating the significant potential for enhancing crop performance in rainfed environments.

13. Uncrewed aerial vehicle (UAV) based soil moisture retrieval. One of the necessities of site-specific precision agriculture (PA) management is accurately measuring surface soil moisture (SM). This measurement provides better planned and managed irrigation water systems. However, high-resolution SM observations through SM probes can be time-consuming, costly, and inefficient for large heterogeneous areas. Researchers at Mississippi State University through a cooperative agreement with ARS researchers in Starkville, Mississippi, investigated the measurement of SM using UAV. The correlation between surface reflected soil moisture and measured in situ soil moisture values were assessed. The consistency and reliability of measurements were investigated concerning different elevation angles and crop cover. The study results show that the collected data from a receiver is enough to estimate surface SM in relatively low vegetated conditions. However, increased vegetation canopy attenuates signals and makes the SM estimation a more complex function.

Review Publications
Firth, A.G., Brooks, J.P., Locke, M.A., Morin, D.J., Brown, A., Baker, B.H. 2022. Soil microbial community dynamics in plots managed with cover crops and no-till farming in the Lower Mississippi Alluvial Valley, USA. Journal of Applied Microbiology. 134(2); 1-13. https://doi.org/10.1093/jambio/lxac051.
Hu, J., Miles, D.M., Adeli, A., Brooks, J.P., Podrebarac, F.A., Smith, R.K., Lei, F., Li, X., Jenkins, J.N., Moorehead II, R.J. 2023. Effects of cover crops and soil amendments on soil CO2 fluxes in Mississippi corn cropping system on upland soil. Environments. 10(2): 19. https://doi.org/10.3390/environments10020019.
Kumar, C., Mubvumba, P., Huang, Y., Dhillon, J., Reddy, K.N. 2023. Multi-stage corn yield prediction using high-resolution (UAV) multispectral data and machine learning models. Agronomy Journal. 13(5):1277. https://doi.org/10.3390/agronomy.
Ramamoorthy, P., Samiappan, S., Wubben, M., Brooks, J.P., Shrestha, A., Rajendra, P., Reddy, R., Bheemanahalli, R. 2022. Drought and root-knot nematode effect on cotton plant growth and detecting its health status using hyperspectral reflectance features. Remote Sensing. 14(16). https://doi.org/10.3390/rs14164021.
Adeli, A., Brooks, J.P., Read, J.J., Feng, G.G., Miles, D.M., Shankle, M.W., Jenkins, J.N. 2019. Corn and soybean grain yield responses to soil amendments and cover crop in upland soils. Journal of Plant Nutrition. 42(19):2484-2497. https://doi.org/10.1080/01904167.2019.1655046.
Adeli, A., Brooks, J.P., Read, J.J., Feng, G.G., Miles, D.M., Shankle, M.W., Barksdale, D.N., Jenkins, J.N. 2020. Management strategies on an Upland soil for improving soil properties. Soil Science. 51(3); 413-429. HTTPS://DOI.ORG/10.1080/00103624.2019.1709490.
Adeli, A., Brooks, J.P., Read, J.J., Barksdale, D.N., Jenkins, J.N. 2021. Pelleted biosolid and cover crop effects on major southern row crops. Journal of Plant Nutrition. 44(18); 2677-2690. https://doi.org/10.1080/01904167.2021.1927090.
Adeli, A., Brooks, J.P., Feng, G.G., Mozaffari, M., Jenkins, J.N. 2021. Integration of pelleted biosolids with cover crops for improving soil properties. Soil Science. 44(18); 2677-2690. https://doi.org/10.1002/saj2.20341.
Adeli, A., Brooks, J.P., Miles, D.M., Todd, M., Feng, G.G., Jenkins, J.N. 2022. Combined effects of organic amendments and fertilization on cotton growth and yield. Agronomy Journal. 2022;1-12. https://DOI.org/10.1002/agj2.21178.
Miles, D.M., Brooks, J.P., Adeli, A., Moore Jr, P.A. 2022. Broiler litter ammonia: caked, surface, and base moisture effects on emissions. International Journal of Poultry Science. 21(3):129-135. https://doi.org/10.3923/ijps.2022.129.135.
Tang, Q., Feng, G.G., Fisher, D.K., Zhang, H., Ouyang, Y., Adeli, A., Jenkins, J.N. 2017. Rain water deficit and irrigation demand of major row crops in the Mississippi Delta. American Society of Agricultural and Biological Engineers. 61(3):927-935.
Brooks, J.P., Smith, R.K., Aldridge, C., Chaney, B., Omer, A., Dentinger, J., Street, G.M., Baker, B.H. 2020. A preliminary investigation of Feral Hog (Sus scrofa) impacts on water quality. Journal of Environmental Quality. 49; 27-37. https://doi.org/10.1002/jeq2.20036.
Firth, A.G., Brooks, J.P., Locke, M.A., Morin, D.J., Brown, A., Baker, B.H. 2022. Dynamics of soil organic carbon and CO2 flux under cover crop and no-till management in soybean cropping systems of the Mid-South. Environments. 9(109). https://doi.org/10.3390/environments9090109.
Firth, A.G., Baker, B., Brooks, J.P., Smith, R.K., Iglay, R.B., Davis, B.J. 2020. Low external input sustainable agriculture: Winter flooding in rice fields increases bird use, fecal matter and soil health, reducing fertilizer requirements. Agriculture, Ecosystems and Environment. 300. https://doi.org/10.1016/j.agee.2020.106962.
Song, P., Xiao, Y., Brooks, J.P., Freguia, S., Zhou, B., Li, Y. 2020. Electrochemical biofilm control by remolding microbial community in agricultural water distribution systems. Journal of Hazardous Materials. 403. Article 123616. https://doi.org/10.1016/j.jhazmat.2020.123616.
Mukherjee, M., Gentry, T., Mjelde, H., Brooks, J.P., Harmel, R.D., Gregory, L., Wagner, K. 2020. Escherichia coli antimicrobial resistance variability in water runoff and soil from a remnant native prairie, an improved pasture, and a cultivated agricultural watershed. Water. 12(5):1251. https://doi.org/10.3390/w12051251.
Mukherjee, M., Laird, E., Gentry, T.J., Brooks, J.P., Karthikeyan, R. 2021. Increased antimicrobial and multidrug resistance downstream of wastewater treatment plants in an urbanizing watershed. Frontiers in Microbiology. https://doi.org/10.3389/fmicb.2021.657353.
Miles, D.M., Branton, S.L., Peebles, D.E., Burnham, M.R., Brooks, J.P., Moore Jr, P.A. 2021. Effects of supplemental dietary phytase & 25-hydroxycholecalciferol on excreta characteristics and nutrient content from commercial layers inoculated before or at the onset of lay with the F-strain of Mycoplasms gallisepticum. International Journal of Poultry Science. 20:209-214. https://doi.org/10.3923/ijps.2021.209.214.
Mukherjee, M., Kocian, L., Liles, C., Mustafa, N., Bullerjahn, G., Gentry, T., Brooks, J.P. 2021. Elevated incidences of antimicrobial resistance and multidrug resistance in the Maumee River (Ohio, USA), a major tributary of Lake Erie. Microorganisms. 9(5): 911. https://doi.org/10.3390/microorganisms9050911.
Ghimire, U., Gude, V.G., Brooks, J.P., Smith, R.K., Deng, D.D. 2021. Co-existing anammox, ammonium-oxidizing, and nitrite-oxidizing bacteria in biocathode-biofilms enable energy-efficient nitrogen removal in bioelectrochemical desalination process. Chemical Engineering Journal. 9(14):4967-4979. https://doi.org/10.1021/acssuschemeng.0c07883.
Ouyang, Y., Feng, G.G., Parajuli, P., Leininger, T., Wan, Y., Jenkins, J.N. 2018. Assessment of surface water quality in the Big Sunflower River Watershed of Mississippi Delta using nonparametic analysis. Water, Air, and Soil Pollution. 229. Article 373. https://doi.org/10.1007/s11270-018-4022-8.
Gao, F., Feng, G.G., Ouyang, Y., Jenkins, J.N., Lui, C. 2019. Simulating weekly available streamflow and pond water resources potential in Mississippi Delta. Water. 11:1271. https://doi.org/10.3390/w11061271.
Ouyang, Y., Feng, G.G., Renninger, H., Leininger, T., Parajuli, P., Grace, J. 2021. A STELLA-based model to simultaneously predict hydrological processes, N uptake and biomass production in a eucalypt plantation. Forests. 12:515. https://doi.org/10.3390/f12050515.
Ouyang, Y., Parajuli, P.B., Feng, G.G., Leininger, T.D., Wan, Y., Dash, P. 2018. Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds. Journal of Hydrology. 563:363-371. https://doi.org/10.1016/j.jhydrol.2018.06.017.
Xua, H., Li, A., Feng, G.G., Li, Y., Qin, Y., Lei, G., Cui, Y. 2018. The effects of asymmetric diurnal warming on vegetation growth of the Tibetan Plateau over the past three decades. Sustainability. 10:1103-1116.
Zhao, F., Ma, W., Kohler, P., Ma, X., Sun, H., Verhoef, W., Zhao, J., Huang, Y., Li, Z., Ratul, A.K. 2022. Retrieval of red solar-induced Chlorophyll fluorescence with TROPOMI on the Sentinel-5 precursor mission. IEEE Transactions on Geoscience and Remote Sensing. 60:1-13. https://doi.org/10.1109/TGRS.2022.3162726.