S1074: Fostering Technologies, Metrics, and Behaviors for Sustainable Advances in Animal Agriculture

(Multistate Research Project)

Status: Active

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SAES-422 Reports

Annual/Termination Reports:

[08/09/2025] [08/12/2025]

Date of Annual Report: 08/09/2025

Report Information

Annual Meeting Dates: 05/20/2025 - 05/21/2025
Period the Report Covers: 10/01/2024 - 09/30/2025

Participants

Brief Summary of Minutes

Accomplishments

<h2>Accomplishments (multi-state activities align with the goals and objectives of S1074)</h2> <ul> <li>In Arkansas, Dr. Zhu and his team have focused their research and extension effort on Objective 3, particularly amending anaerobic co-digestion of poultry litter with wheat straw using biochar. Anaerobic co-digestion (Co-AD) of poultry litter (PL) and agricultural straw using biochar has rarely been practiced. Therefore, we conducted two sequential experiments to evaluate the effect of adding alkaline biochar on improving the batch Co-AD of PL and wheat straw. The feasibility experiment identified the advantages of adding biochar by the improved observed cumulative methane yield (CMYo, mL CH4/g VSsubstrate) of 9.7%; the increased removal rates of the substrate total solids (TSsubstrate) and volatile solids (VSsubstrate) of 15.2% and 14.2%, respectively; the enhanced abundance of both hydrolytic bacteria and methanogens, including hydrogegenotrophic Methanobacterium and, especially, the acetolactic Methanosaeta; and the 37.3% higher abundance of the methanogenic pathways, compared to the control. The interaction experiment showed that biochar dosage interacted with the initial substrate carbon-to-nitrogen ratio (C/N) and total solids level (TS). The developed mathematical models for CMYo and VSsubstrate removal by response surface methodology were significant, which predicted the optimal conditions being initial substrate C/N ratio 29.93, TS 6.98%, and biochar dosage 9.98% substrate. The optimized CMYo and VSsubstrate removal rates were 17.7% and 22.1% higher, respectively, than those of the control. These results support the utilization of biochar in improving the Co-AD of agricultural wastes, which have made significant contributions to improving anaerobic digestion of poultry litter with wheat straw supplemented with biochar particles.</li> <li>In Georgia, Dr. Chai’s team made significant advancements in applying machine vision and artificial intelligence technologies to precision poultry farming. Recognizing the importance of rooster behaviors—such as mating and movement—as indicators of productivity and welfare, the team addressed the challenges associated with manual behavior identification, which is often time-consuming and prone to cognitive bias and fatigue. To overcome these limitations, Dr. Chai’s group successfully implemented deep learning-based object detection techniques, particularly leveraging the YOLO (You Only Look Once) family of models, renowned for their real-time processing capabilities and accuracy. Unlike traditional detection methods, YOLO directly predicts bounding boxes and class probabilities in a single pass, offering a faster and more efficient approach. Originally introduced by Joseph Redmon in 2015, YOLO has become a leading framework across various industries, including agriculture—for its speed and precision. Dr. Chai’s research team effectively adapted YOLO models to detect roosters in complex environments such as cage-free (CF) poultry houses. This work marks a major step forward in the automation of animal identification in CF facilities, where no existing system currently distinguishes between hens and roosters. The study focused on detecting birds based on phenotypic traits such as comb size and body size, and it included a comparative analysis of model performance metrics. These accomplishments not only demonstrate the feasibility of applying deep learning in commercial poultry systems but also pave the way for more intelligent, data-driven management tools in the poultry industry.</li> <li>In Idaho, Dr. Chen’s team worked with other S1074 team members across the nation on holding the Waste to Worth 2025 conference in Boise during April 8-11, 2025. The Waste to Worth conference provided an engagement platform for S1074 members, livestock producers, and livestock industry partners to share ideas, research findings, and practices that support/improve a sustainable livestock industry. They contributed to the Idaho Sustainable Agriculture Initiative for Dairy (ISAID) project, a USDA Sustainable Agriculture Systems initiative, which involved principal investigators from Washington and North Carolina.</li> <li>In Minnesota, Dr. Cortus’ team has focused their research and extension effort on “Building Value in Baselines.” A Midwest multistate team used focus groups to evaluate the value of the dairy industry-promoted assessment tool, FARM ES. Furthermore, the focus group participants identified the feasible management strategies and actor-networks necessary to move sustainability initiatives forward. Building from this work and publication (Erickson et al., 2025), S1074 supported a workshop at the 2025 Waste to Worth Conference in Boise, ID, to accelerate adoption by strengthening a community of support for sustainability initiative practices. Options for mitigation pathways require a variety of advisory services. Through the workshop and participants, an accessible guide of resources to support sustainable action evolved and is publicly available at https://lpelc.org/moving-the-sustainability-needle/. This work involved MN and NC members, with partners from SD, NE, the National Pork Board, and Dairy Management Inc.</li> <li>In North Carolina, Dr. Sharara, in collaboration with Dr. Cortus at the University of Minnesota, developed and delivered a workshop, Moving the “Sustainability” Needle, to provide insights and exchange expertise on resources, opportunities and challenges in supporting the food animal industry’s sustainability efforts. As a product of this workshop, the team produced a workshop findings document aggregating the gained perspectives and making it public to practitioners and industry stakeholders. Dr. Sharara is working in collaboration with S-1074 colleagues from Iowa (Dr. Andersen and Dr. Ramirez) and Minnesota (Dr. Cortus) through a funded project by the National Pork Board (NPB) to investigate opportunities to improve nutrient cycling in the pork value chain. Through this project, collaborators are analyzing different stages of the pork value chain to examine interventions to reduce nutrient loss to ecosystems such as air, water, and soil emissions. Findings from this project will provide data and information necessary for recommendations for improving nutrient cycling.</li> </ul> <ul> <li>In Ohio, Dr. Zhao and her team have focused their research and extension effort on Objectives 1 and 3.</li> </ul> <ul> <li>For Objective 1, Dr. Zhao participated and presented air quality research at the Ohio Poultry Sustainability Summit organized by the Ohio Poultry Association on Oc. 10, 2024. Many large Ohio poultry producers participated in the Summit. University research, private industry products and services, and government programs supporting the sustainable development of poultry production were presented and discussed. Producers' feedback valued the direct personal connection and interactive discussions and Q&A sessions. Potential areas of collaboration were discussed. A Virtual Forum-“Dust & Disease in Egg Production” was organized on June 12. 2025 through collaborative efforts by a group of peers (Lingying Zhao, Professor and Extension Specialist, The Ohio State University; Brett Ramirez, Egg Industry Center, Associate Prof. Iowa State University; Lisa Bielke, Prestage Distinguished Scholar of Turkey Health, Prestage Department of Poultry Science, NCSU; and Lilong Chai, Associate Professor & Engineering Specialist, Department of Poultry Science, The University of Georgia)</li> <li>For Objective 3, Dr. Zhao had developed a new ventilation system for conventional egg production facilities, reviewed dust and pathogen control technologies, and shared the reviews at various research and extension meetings. She presented “Engineering Technologies for Air Quality Control in Poultry Houses” at the 2025 Georgia Precision Poultry Farming Conference -Virtual, held on May 6, 2025 and reviewed dust and pathogen control technologies at the “Virtual Forum-Dust & Disease in Egg Production.”</li> </ul> <ul> <li>In South Dakota, Dr. Yang and his team have accomplished the following tasks:</li> </ul> <ul> <li>He participated in the 2025 Minnkota Annual Meeting in May, organized by Dr. Erin Cortus at the University of Minnesota. He provided an update on animal structure environment research and extension activities in South Dakota. Minnkota is a collaborative association of university extension specialists, government agencies, animal producers, equipment suppliers, and barn builders, all focused on advancing sustainability in animal production.</li> <li>Yang’s team continued its collaboration with Dr. Yuanhui Zhang at the University of Illinois at Urbana-Champaign on a swine air quality project. This work involved visits to ten commercial swine farms for particulate matter sampling and monitoring, development of protocols for sampling, laboratory experiments, and data analysis, as well as identification of the best-performing low-cost particulate matter sensors for use in swine barns. A key outcome of this project was the development of a receptor modeling-based approach for particulate matter source attribution.</li> <li>Additionally, Dr. Yang’s team successfully developed an Excel-based odor footprint tool (NDOFT) for North Dakota, in partnership with the North Dakota Pork Council and the North Dakota Livestock Alliance. To support adoption of the tool, an online training workshop was delivered to eight animal industry representatives across the state, accompanied by the creation of two user guidance documents.</li> <li>Yang also continued his service on the Ag Cybersecurity Curriculum development team within the SDSU Extension program. During the reporting period, he contributed to the publication of five Extension articles. Other outreach efforts included two Extension trailers, one Extension presentation at the SD Ag Horizon conference, and a podcast interview. Furthermore, he delivered two Extension talks on odor and air quality to approximately 50 animal producers as part of the state CAFO Environmental Training, and four additional talks on manure safety, reaching around 120 participants.</li> </ul> <ul> <li>In TX, Dr. Liu maintains the Youtube channel @TexasManure, The content includes topics such as:</li> </ul> <ul> <li>Small-scale composting systems</li> <li>Food waste composting technologies</li> <li>Food waste anaerobic digesters</li> <li>Composting interviews with industry practitioners</li> <li>“Insights from Biosecurity Experts” series</li> </ul> <ul> <li>CA and USDA ARS Idaho engaged in a project to evaluate pre and post installation of vermifiltration on commercial dairy operation(s). This innovative manure management system will be a key innovation in food and farming systems should it prove effective. The research will facilitate evaluation of CA Air Resources Board spreadsheet to estimate emission reductions compared with the EU Cool Farm Tool. Comparisons of spreadsheet and tool-based estimates to actual emissions will be made.</li> <li>CA also evaluated nutrient uptake from duckweed at commercial scale in late summer/fall of 2024. However, by end of spring 2025 the commercial venture shuttered its doors due to insufficient financing.</li> <li>In Wisconsin, Dr. Akdeniz and his team managed to align their research and extension closely with the S1074 Objectives.</li> </ul> <ul> <li>For Objective 1, the team developed and shared articles and podcasts on the UW-Madison Extension website, including guidelines on ventilation design in dairy buildings, air quality, lighting, and labor efficiency in automated dairy operations. These resources help producers evaluate housing and management decisions. Research findings have been presented at the 2024 and 2025 ASABE Annual Meetings and the 2025 Midwest Climate Summit to broaden outreach. As we have made progress with our research and extension projects, we are ready to develop more collaborations in 2026.</li> <li>For Objective 2, the team used computational fluid dynamics (CFD) models to assess ventilation design and mitigate heat stress in dairy buildings. UAV-based methods are also used to directly measure air emissions from pastures, which enhances our understanding of nitrogen cycling. Together, these tools support sustainability in animal production.</li> <li>For Objective 3, the team’s work examined the effectiveness of ventilation systems, supplemental cooling in dairy buildings, and UAV-based monitoring technologies. They also evaluated micro-aeration in anaerobic digesters to improve methane production and reduce hydrogen sulfide emissions. These studies support practical technology adoption and future research on system improvements in animal agriculture.</li> </ul>

Publications

Journal Articles   <ol> <li>Zhan, Y., Zuo, B., Cao, X., Xiao, Y., & Zhu, J. (2024). Biochar enhanced anaerobic co-digestion of poultry litter and wheat straw: Performance, microbial analysis, and multiple factors’ interaction. Renewable Energy, 231, 120907. <a href="https://doi.org/10.1016/j.renene.2024.120907">https://doi.org/10.1016/j.renene.2024.120907</a></li> <li>Paneru, D., Sharma, M. K., Goo, D., Shi, H., Applegate, T. J., Chai, L., ... & Kim, W. K. (2025). Interactive effects of dietary deoxynivalenol and coccidial infection on growth performance, immune response, oxidative status, and gut health in pullets. Poultry Science, 105462.</li> <li>Paneru, B., Bist, R. B., Yang, X., Dhungana, A., Dahal, S., & Chai, L. (2025). Deep Learning Methods for Automatic Identification of Male and Female Chickens in a Cage-Free Flock. Animals, 15(13), 1862.</li> <li>Yang, X., Lu, G., Zhang, J., Paneru, B., Dhungana, A., Dahal, S., Bist, R. B., & Chai, L. (2025). Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model. Applied Sciences, 15(12), 6625.</li> <li>Yang, X., Zhang, J., Paneru, B., Lin, J., Bist, R. B., Lu, G., & Chai, L. (2025). Precision Monitoring of Dead Chickens and Floor Eggs with a Robotic Machine Vision Method. AgriEngineering, 7(2), 35. (Cover story).</li> <li>Subedi, S., Bist, R. B., Yang, X., Li, G., & Chai, L. (2025). Advanced Deep Learning Methods for Multiple Behavior Classification of Cage-Free Laying Hens. AgriEngineering, 7(2), 24.</li> <li>Yang, X., Bist, R. B., Subedi, S., Guo, Y., & Chai, L. (2025). The Application of Probiotics and Prebiotics in Poultry Production and Impacts on Environment: A Review. Encyclopedia, 5(1), 35.</li> <li>Islam, M. N., I. H. Mahdy, L. Chen, S. Wu, and B. He. 2024. Enhanced phosphorus bioavailability and reduced water leachability in dairy manure through hydrothermal carbonization: effect of processing temperature and CaO additive. Environmental Technology. <a href="https://doi.org/10.1080/09593330.2024.2430802">https://doi.org/10.1080/09593330.2024.2430802</a></li> <li>Erickson, M., Rovai, M., Villamediana, P., Schmidt, A. M., Stowell, R. R., & Cortus, E. L. (2025). Building value for dairy farmers and advisors in the Farmers Assuring Responsible Management Environmental Stewardship Program. Translational Animal Science, 9, txaf038. https://doi.org/10.1093/tas/txaf038</li> <li>Uguz, S., Sahin, Y.S., Kumar, P., Yang, X., Anderson, G. (2025). Real-time algal monitoring using novel machine learning approaches. Big Data and Cognitive Computing, 9(6), 153.</li> <li>Alahe, M. A., Chang, Y., Kemeshi, J., Won, K., Yang, X., Wei, L. (2025). Real-time agricultural image encryption algorithm using AES on edge computing devices. Computers and Electronics in Agriculture, 237, 110594.</li> <li>Haleem, N., Yuan, J., Uguz, S., Ucok, S., Gu, Z., Yang, X. (2025). Direct current (DC)-initiated flocculation of Scenedesmus dimorphus. Environmental Science and Pollution Research, 32(17), 11292-11298.</li> <li>Ucok, S., Yang, X. (2025). Chemical composition and methane production potential of agricultural residues: Olive pomace, cottonseed meal, and red pepper processing waste. Tekirdağ Ziraat Fakültesi Dergisi 22 (1), 195-204.</li> <li>Gong, A., Wang, G., Qi, X., He, Y., Yang, X., Huang, X., Liang, P. (2025) Energy recovery and saving in municipal wastewater treatment. Nature Sustainability, 8, 112-119.</li> <li>Kumar, P., Tiwari, S., Uguz, S., Li, Z., Samuel, S., Gonzalez, J., Zhang, Y., Yang, X. (2024). Bioaerosol downwind from animal feeding operations: A comprehensive review. Journal of Hazardous Materials, 480, 135825.</li> <li>Alahe, M. A., Wei, L., Chang, Y., Gummi, S. R., Kemeshi, J., Yang, X., Won, K., Sher, M. (2024). Cyber security in smart agriculture: Threat types, current status, and future trends. Computers and Electronics in Agriculture, 226, 109401.</li> <li>Akdeniz, N. L. Polzin. 2025. Ventilation fans offset potential reductions in milk margin from heat stress in Wisconsin dairy farms. Agriculture, 15(9): 955. https://doi.org/10.3390/agriculture15090955</li> <li>Yi, Y., N. Akdeniz, JM. Shutske, CY. Choi. 2025. Mitigating heat stress for agricultural workers using computational fluid dynamics (CFD). Energy and Buildings, 328, 115186. https://doi.org/10.1016/j.enbuild.2024.115186</li> <li>Jiang, L. Y. Yi, N. Akdeniz. 2024. Energy-saving cooling strategies for tunnel-ventilated dairy buildings: Computational fluid dynamics simulations and validation. Smart Agricultural Technology, 100576. https://doi.org/10.1016/j.atech.2024.100576</li> <li>Yang, D., Y. Wang, N. Akdeniz. 2024. Developing and field testing an unmanned aerial mapping method to measure air emissions from dairy pastures. Remote Sensing, 16 (16), 3007. https://doi.org/10.3390/rs16163007</li> <li>Jiang, L. Y. Yi, N. Akdeniz. 2024. CFD simulations of supplemental cooling techniques in cross-ventilated dairy buildings and associated greenhouse gas emissions. Computers and Electronics in Agriculture, 108480. <a href="https://doi.org/10.1016/j.compag.2023.108480">https://doi.org/10.1016/j.compag.2023.108480</a></li> <li>Gunawardana, D., Wang, X., Mahdaviarab, A., McCubbins, O. P., Landaverde, R., & Liu, Z. (2025). Virtual reality videos for delivery of extension educational materials on manure and mortality management: A pilot-study. The Journal of Agricultural Education and Extension, 1-23</li> <li>Mahdaviarab, A., Pahlavanyali, K., Cheng, R., Wang, X., Doria, J., Howe, J. A., Pineiro, J. M., Spencer, J., & Liu, Z. (2025). Emergency mass disposal of milk: Options and considerations. Journal of Environmental Management, 376, 124420.</li> <li>Zhang, Y., Lei, B., Mahdaviarab, A., Wang, X., & Liu, Z. (2025). Robust biochar yield and composition prediction via uncertainty-aware ResNet-based autoencoder. Biochar, 7(1), 1-16</li> </ol>   Conference Proceedings   <ol> <li>Islam, M. N., B. He., and L. Chen. 2025. Phosphorus recycling from dairy manure via hydrochar-experience from the lab-scale to pilot-scale hydrothermal carbonization prototype. Waste to Worth 2025, Boise, ID, April 8-11, 2025</li> <li>Das, A. K., and L. Chen. 2025. Ammonia recovery from anaerobically digested dairy manure using electrodialysis coupled with a hydrophobic gas-permeable membrane for stripping. Waste to Worth 2025, Boise, ID, April 8-11, 2025.</li> <li>Das, A. K., and L. Chen. 2025. Modeling of electrochemical ammonia removal from anaerobically digested dairy wastewater. Waste to Worth 2025, Boise, ID, April 8-11, 2025.</li> <li>Chen, L., M. N., Islam, and B. He, 2025. Hydrochar carbonization of dairy manure for phosphorus recovery and runoff risk mitigation. 2025 WSCS Annual Conference, Walla Walla WA, June 24-25, 2025</li> <li>Chen, L., and A. K. Das, 2025. Ammonia recovery from anaerobically digested dairy wastewater facilitated by in-situ acid and base generation in a transmembrane electro-chemisorption system. 2025 WSCS Annual Conference, Walla Walla WA, June 24-25, 2025</li> <li>Chen, L., M. N., Islam, and B. He. 2025. Phosphorus recycling from dairy manure via hydrochar-experience from the lab-scale to pilot-scale hydrothermal carbonization prototype. Waste to Worth 2025, Boise, ID, April 8-11, 2025</li> <li>Das, A. K., and L. Chen. 2025. Ammonia recovery from anaerobically digested dairy manure using electrodialysis coupled with a hydrophobic gas-permeable membrane for stripping. Waste to Worth 2025, Boise, ID, April 8-11, 2025.</li> <li>Das, A. K., and L. Chen. 2025. Modeling of electrochemical ammonia removal from anaerobically digested dairy wastewater. Waste to Worth 2025, Boise, ID, April 8-11, 2025.</li> <li>Islam, M.N., B. He, and L. Chen. 2025. Hydrochar carbonization of dairy manure for phosphorus recovery and runoff risk mitigation. Western Nutrient Management Conference, Reno, NV, March 4-6, 2025</li> <li>Das, A. K., and L. Chen. 2025. Ammonia recovery from anaerobically digested dairy wastewater facilitated by in-situ acid and base generation in a transmembrane electro-chemisorption system. Western Nutrient Management Conference, Reno, NV, March 4-6, 2025.</li> <li>Kumar, P., Uguz, S., Tiwari, S., Chang, Y., Yang, X. (2025). Field testing of low-cost PM sensors in animal production facilities. In 2025 Air Quality Measurement Methods and Technology Conference, Aurora, CO.</li> <li>Yang, Y., Thaler, R., Yang, X. (2025). Developing an odor footprint tool for animal agriculture in North Dakota. In 2025 ASABE North Central Regional Section Meeting, Fargo, ND.</li> <li>Khan, T., Yang, X. (2025). LoRaWAN-enabled IoT solution for smart farming. In 2025 ASABE North Central Regional Section Meeting, Fargo, ND.</li> <li>Yang, X. (2024). Particulate matter in swine barns. In Midwest Regional Agricultural Safety and Health 2024 Conference, Ames, IA.</li> <li>Ly, N. N. Akdeniz, Z. Zeng, C. Choi. 2025. Testing the efficacy of positive-pressure ventilation systems (PPTV) for indoor calf housing using computational fluid dynamics (CFD) simulations, ASABE Annual International Meeting, Toronto, Canada.</li> <li>Jiang, L., N. Akdeniz. 2025. Ventilation design for calf hutches using computational fluid dynamics (CFD) simulations, ASABE Annual International Meeting, Toronto, Canada.</li> <li>Froelich, E. N. Akdeniz. 2025. Optimizing microaeration rates in anaerobic digesters: comparative analysis under mesophilic and thermophilic conditions, ASABE Annual International Meeting, Toronto, Canada. </li> <li>Akdeniz, N. 2025. Online calculators for computing ventilation requirements of dairy buildings. ASABE Annual International Meeting, Toronto, Canada. </li> <li>Yang, D. N. Akdeniz. 2025. Direct air emission measurements using small-unmanned aircraft systems (sUAS) from livestock pastures in Wisconsin. ASABE Annual International Meeting, Toronto, Canada. </li> <li>Yang, D., N. Akdeniz. 2025. Direct measurement of spatial greenhouse gas emissions from livestock pastures. Midwest Climate Summit, Madison, WI.</li> <li>Yang, D., N. Akdeniz. 2024. Quantifying greenhouse gas emissions from dairy pastures using a flying air analyzer. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Froelich, E., N. Akdeniz. 2024. Improving anaerobic digestion of dairy manure by reducing hydrogen sulfide production through microaeration. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Li, J., N. Akdeniz. 2024. Ventilation design for automated milking system (AMS) buildings. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Cheng, R., Mahdaviarab, A., Pahlavanyali, K., Wang, X., Wang, H., and Liu, Z. Optimizing Biogas Production Through Anaerobic Co-Digestion of Poultry Carcasses and Litter. 2025. ASABE Annual International Meeting, Toronto, Canada.</li> <li>Pahlavanyali, K., Mahdaviarab, A., Cheng, R., Kincaid, N., Habib, M. R., Wang, X., Wang, H., and Liu, Z. Valorizing Organic Waste: Assessing the Fertilization Potential of Black Soldier Fly (Hermetia illucens) By-Products in Tomato Cultivation. 2025. ASABE Annual International Meeting, Toronto, Canada.</li> </ol>   Thesis/Dissertations  Cherotich, S. (2025). Depositions of Gas Phase NH3 and Particle Phase NH4+ in the Vicinity of Poultry Production Facilities. Ph.D. dissertation. Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC. <ol> <li>Jones, K. (2025). Technical and Economic Considerations of Anaerobic Digestion in Partially Nitrified Swine Manure. M.S. thesis. Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC.</li> <li>Khan, T. (2025). LoRaWAN-enabled IoT solutions for smart farming. M.S. thesis, South Dakota State University, Brookings, SD.</li> <li>Froelich, E. (2025). Optimizing microaeration in anaerobic digesters: A comparative study of batch and continuous systems under mesophilic and thermophilic conditions, M.S. thesis, University of Wisconsin-Madison, Madison, WI.  </li> </ol> <ol> <li>Zhou, Run. Novel Ag-Containing Photocatalysts and Their Performance Regulation and Applications to Hazard Organic Degradation. PhD diss., Water Management and Hydrological Science, 2025. Chairs: Zong Liu and Virender K. Sharma</li> </ol>   Extension and Outreach   <ol> <li>Chai, L (July 8, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/07/machine-vision-technologies-for-automatic-identification-of-male-and-female-chickens/">Machine Vision Technologies for Automatic Identification of Male and Female Chickens</a>.</li> <li>Chai, L (June 26, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/06/the-4th-u-s-precision-livestock-farming-conference/">The 4th U.S. Precision Livestock Farming Conference</a>.</li> <li>Chai, L (June 16, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/06/tracking-poultry-drinking-and-floor-eggs-with-an-innovative-depth-anything-model/">Tracking Poultry Drinking and Floor Eggs with an Innovative Depth Anything Model</a>.</li> <li>Chai, L (April 27, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/04/deep-learning-systems-for-automatic-egg-grading/">Deep Learning Systems for Automatic Egg Grading</a>.</li> <li>Chai, L (February 28, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/02/a-robotic-machine-vision-system-for-tracking-dead-chickens/">A Robotic Machine Vision System for Tracking Dead Chickens</a>.</li> <li>Chai, L (January 31, 2025). <a href="https://site.caes.uga.edu/precisionpoultry/2025/01/monitoring-perching-behavior-of-cage-free-hens-with-machine-vision/">Monitoring Perching Behavior of Cage-free Hens with Machine Vision</a>.</li> <li>Erickson, M., Sharara, M., & Cortus, E. (2025). Moving the “Sustainability” Needle. Workshop In Proceedings of the 2025 Waste to Worth Conference, Boise, ID. April 7-11, 2025. https://lpelc.org/moving-the-sustainability-needle/</li> <li>Erickson, M., Sharara, M., & Cortus, E. (2025). Building Value in Baseline Sustainability Assessments. Workshop In Proceedings of the 2025 Waste to Worth Conference, Boise, ID. April 7-11, 2025. <a href="https://lpelc.org/building-value-in-baseline-sustainability-assessments/">https://lpelc.org/building-value-in-baseline-sustainability-assessments/</a></li> <li>Wang-Li, L. (2024) The Role of Agriculture in Atmospheric Nitrogen Deposition: Sources, Impacts, and Management. Livestock and Poultry Environmental Learning Community (LPELC) Monthly Webinars. September 23, 2024. Recording link: https://lpelc.org/the-role-of-agriculture-in-atmospheric-nitrogen-deposition-sources-impacts-and-management/</li> <li>Zhao, L.Y. 2025. Engineering technologies for air quality control in poultry houses. Invited presentation at 2025 Georgia Precision Poultry Farming Conference-Virtual. May 6, 2025.</li> <li>Zhao, L.Y., T. Lim, and L. Chai.  2025. A review of dust and pathogen control technologies in poultry production facilities. Invited presentation at Virtual Forum-Dust & Disease in Egg Production. June 12, 2025      </li> <li> Zhao, L.Y.  2025. A new ventilation system to improve indoor environment and abate pathogen transmission in layer houses. Invited presentation at Virtual Forum-Dust & Disease in Egg Production. June 12, 2025   </li> <li>Zhao, L.Y. 2025. Measurement, Modeling, and Mitigation of Indoor Environment, Air Quality, and Air Emissions at Poultry Facilities. Invited presentation at the Ohio Poultry Association Summitt, Oct. 10, 2024.</li> <li>Yang, X., Nafchi, A., Brennan, J., Mehan, S., Vandermark, L., Sellars, S., Smart, A., Chang, Y., Wang, Y. (2025). Protecting Your Data: The Role of Authentication and Encryption in Agricultural Cybersecurity, SDSU Extension.</li> <li>Brennan, J., Vandermark, L., Mehan, S., Nafchi, A., Sellars, S., Yang, X. (2025). Be Cyber Aware: Text Message Cyber-Attacks (SMS Phishing - Smishing), SDSU Extension.</li> <li>Yang, X., Nafchi, A., Brennan, J., Mehan, S., Sellars, S., Vandermark, L. (2024). Choosing the Right Wireless Network Technologies for Agricultural IoT Applications. SDSU Extension.</li> <li>Brennan, J., Vandermark, L., Sellars, S., Mehan, S., Nafchi, A. M., Yang, X. (2024). The Growing Threat of Cyber Attacks in Agriculture. SDSU Extension.</li> <li>Nafchi, A., Smart, A, Yang, X., Mehan, S., Brennan, J. (2024). Cybersecurity Vulnerabilities in Precision Agriculture. SDSU Extension.</li> <li>Akdeniz, N. Before You Buy: A Farm Tech Investment Planning Guide, 2025 (link)</li> <li>Akdeniz, N. Balancing Technology and People: The Evolving Role of Farm Workers in Automation, 2025 (<a href="https://farms.extension.wisc.edu/articles/balancing-technology-and-people-the-evolving-role-of-farm-workers-in-automation/">link</a>)</li> <li>Akdeniz, N. Balancing Ventilation Costs and Milk Production Losses on Wisconsin Dairy Farms, 2025 (<a href="https://dairy.extension.wisc.edu/articles/balancing-ventilation-costs-and-milk-production-losses-on-wisconsin-dairy-farms/">link</a>)</li> <li>Akdeniz, N. Lighting in Dairy Buildings in Wisconsin, 2025 (link)</li> <li>Akdeniz, N. Ventilation Fan Noise in Dairy Buildings, 2025 (<a href="https://dairy.extension.wisc.edu/articles/ventilation-fan-noise-in-dairy-buildings/">link</a>)</li> <li>Akdeniz, N. Tunnel-ventilated dairy buildings, 2025 (<a href="https://dairy.extension.wisc.edu/articles/tunnel-ventilated-dairy-buildings/">link</a>)</li> <li>Akdeniz, N. Cross-Ventilation in Dairy Buildings, 2025 (<a href="https://dairy.extension.wisc.edu/articles/cross-ventilation-in-dairy-buildings/">link</a>)</li> <li>Akdeniz, N. Natural Ventilation in Dairy Buildings, 2025 (<a href="https://dairy.extension.wisc.edu/articles/natural-ventilation-in-dairy-buildings/">link</a>)</li> <li>Akdeniz, N. Air Quality in Calf Housing, 2025 (<a href="https://dairy.extension.wisc.edu/articles/air-quality-in-calf-housing/">link</a>)</li> <li>Akdeniz, N. Renovating Tie-Stall Barns for Indoor Calf Housing, 2024 (link)</li> <li>Akdeniz, N. Ventilation in Dairy Buildings, 2024 (link)</li> <li>Dairy Manure Management Workshop. Foundation for Food & Agriculture Research. July 2025, Denver, CO</li> <li>Manure Centrifuge & Dealing with Struvite. DOPA (Central TX), April 2025. Stephenville, TX</li> <li>TAMU AGSM 337 Guest Lecture: Anaerobic Lagoons. April 2025. College Station, TX</li> <li>Manure Happens: Dr. Zong Liu on Manure and Compost Management. Colorado State University AgNext podcast Ep.19. February 2025, Fort Collins, CO</li> <li>Manure and Mortality Management. Colorado State University General Seminar, Department of Animal Science. February 2025, Fort Collins, CO</li> <li>Advancing Manure Management in Texas. Seminar at Texas Tech CASFER, an NSF Engineering Research Center. January 2025, Lubbock, TX</li> <li>Manure Management. NRCS Nutrient Management Training, November 2024, Canyon, TX</li> <li>Digesters, Mortality Management, and Climate Smart Program Enrollment. DOPA (East Texas). October 2024, Sulphur Spring, TX</li> </ol>

Impact Statements

Date of Annual Report: 08/12/2025

Report Information

Annual Meeting Dates: 07/30/2024 - 07/30/2024
Period the Report Covers: 08/01/2023 - 07/31/2024

Participants

Lide Chen Idaho University of Idaho lchen@uidaho.edu
Zong Liu Texas Texas A&M University zongliu@tamu.edu
Mahmoud Sharara North Carolina N.C. State Univ. msharar@ncsu.edu
Jun Zhu Arkansas University of Arkansas junzhu@uark.edu
Lingying Zhao Ohio The Ohio State University zhao.119@osu.edu
Teng Lim Missouri University of Missouri limt@missouri.edu
Lingjuan Wang-Li North Carolina N.C. State Univ. lwang5@ncsu.edu
Xufei Yang South Dakota South Dakota State University Xufei.Yang@sdstate.edu

Brief Summary of Minutes

Accomplishments

<ul> <li>In Arkansas, the research and extension effort of Dr. Zhu and his team has focused on Objective 3. The major activities of this project have enabled the team to make significant progress in improving the anaerobic digestion of poultry litter with wheat straw by incorporating ferric oxide nanoparticles into the digestion process. Metallic nanoparticles, such as ferric oxide nanoparticles (FNP), have been utilized to promote methane fermentation. However, the appropriate use of ferric oxide nanoparticles in anaerobic co-digestion (Co-AD) of agricultural wastes, considering substrate characteristics as important factors, is rarely understood. The research conducted in the past year used response surface methodology and artificial neural network (ANN) to model methane yield (MY, NmL CH4/g VS added) from batch Co-AD of poultry litter (PL) and wheat straw (WS) with FNP supplementation. A statistical central composite design was applied to the input factors of ferric oxide nanoparticle dosage (mg/L), carbon-to-nitrogen ratio (C/N), and total solids level (TS, %), with a significant second-order quadratic model generated (R2 =0.9887). ANN developed a trained multilayer perceptron network with an even higher R2 (0.9947). These analyses showed that all factors had a significant effect on methane yield (the significance was in the order of C/N ratio > FNP dosage > TS), with significant interactions between C/N ratio and FNP, and between C/N ratio and TS. Numerical optimization achieved a maximum methane yield of 318.4 mL CH4/g VS added under the conditions of C/N 34.65, TS 5.28%, and FNP 19.39 mg/L. The trained artificial neural network coupled with the genetic algorithm generated a similar maximum methane yield prediction, 318.3 mL CH4/g VS added, under the optimal conditions of C/N 35, TS 4.24%, and FNP 17.42 mg/L. The results can give guidance to real operations and provide support for process simulation and optimization in other scenarios.</li> </ul>   <ul> <li>In Georgia (GA), Chai and his team have secured additional funding from USDA-NIFA, Georgia Research Alliance, and Egg Industry Center to work on multiple precision poultry production projects. Two select projects and corresponding achievements are shown below:</li> <li>Activity index detection: Chickens’ behaviors and activities are important information for managing animal health and welfare in commercial poultry houses. In this study, convolutional neural networks (CNNs) models were developed to monitor the chicken activity index. A dataset consisting of 1,500 top-view images was utilized to construct tracking models, with 900 images allocated for training, 300 for validation, and 300 for testing. Six different CNN models were developed, based on YOLOv5, YOLOv8, ByteTrack, DeepSORT, and StrongSORT. The final results demonstrated that the combination of YOLOv8 and DeepSORT exhibited the highest performance, achieving a Multi-Object Tracking Accuracy (MOTA) of 94%. Further application of the optimal model could facilitate the detection of abnormal behaviors such as smothering and piling, and enabled the quantification of flock activity into three levels (low, medium, and high) to evaluate footpad health states in the flock. This research underscores the application of deep learning in monitoring the poultry activity index for assessing animal health and welfare.</li> <li>Footpad dermatitis monitoring: Footpad dermatitis (FPD) is a common poultry condition that can negatively influence chickens’ production, welfare, and health. However, no automated tool for monitoring FPD in live chickens is currently available. The objective of this study was to develop and optimize deep learning models to monitor hens’ FPD scores (i.e., 0-2 scale with higher scores indicating poorer footpad conditions). A total of 700 Hy-Line W-36 hens were raised in four cage-free housing systems integrated with Electrostatic Particle Ionization and various bedding materials. A GoPro camera with an upward lens was placed inside a transparent box. Individual laying hens were placed on the top surface of the box to acquire RGB images. In addition, a thermal camera was used to record RGB and thermal images of footpads, and the images were manually scored to assess their footpad conditions. Preprocessing techniques (e.g., filtration, separation, and augmentation) were deployed to enhance dataset quality and size. Moreover, YOLOv8 models (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and YOLOv7 models (YOLOv7 and YOLOv7x) were comparatively evaluated for predicting FPD scores. The results show that the YOLOv8l outperformed other models, with higher recall (96.6%), mAP@0.50 (97.0%), and F1-score (95.0%). Additionally, the YOLOv8l-FPD model exhibited a high mAP@0.50 for score 0 (98.0%), score 1 (95.0%), and score 2 (97.9%) and F1-score (95.0%) for all FPD scores. Notably, using thermal images could result in faster convergence of model training and slightly better FPD score prediction performance than RGB images. The proposed technique can be useful for non-invasive automatic FPD scoring and further improve automation levels and animal welfare in the egg industry.</li> </ul>   <ul> <li>In Idaho, Dr. Chen and his team worked with colleagues from Washington State University and Oregon State University on developing proposal ideas that build symbiotic, climate-smart dairy and potato systems for sustainable agriculture. They also engaged in Dairy West and the Idaho Dairymen’s Association’s effort that involved scientists and industry professionals from the Pacific Northwest to collectively identify research gaps and priorities that help achieve the dairy industry’s sustainability goals. Additionally, the team contributed to the Idaho Sustainable Agriculture Initiative for Dairy (ISAID) project, a USDA Sustainable Agriculture Systems initiative, which involved principal investigators from Washington and North Carolina.</li> </ul>   <ul> <li>In Minnesota, Dr. Cortus and her team have focused on technology appraisal in the past reporting year. Nutrient and carbon partitioning and performance for swine manure management technologies. Through a National Pork Board-funded project, S1074 members are synthesizing nutrient transformations and partitioning in liquid swine manure undergoing anaerobic digestion, aeration, acidification, and solid-liquid separation. The work included a literature review in 2023/2024. While these manure treatment technologies are more mature than others, there is a lack of mass balance qualification of results, particularly when treatment comparisons are performed. However, by considering mass partitioning, we are better able to stack technologies and quantify performance through other analysis methods, like life cycle analyses. This work involves Minnesota, North Carolina, and Iowa S1074 members, in conjunction with animal nutritionists, geneticists, and data scientists.</li> </ul>   <ul> <li>In North Carolina, Dr. Wang-Li's group continued to analyze the air sampling data collected at NCDA Piedmont Research Station Poultry Unit and a commercial egg farm in Ohio State University, in collaboration with Dr. Lingying Zhao at The Ohio State University. This research project titled “Fate, Transport, and Transformation of Ammonia Emissions from Animal Feed Operations and Their Impacts on Air-Soil Health” aims at quantifying NH3 and particulate NH4+ dry depositions as impacted by NH3 emissions from poultry production units and their associated impact on soil health. It will fill the knowledge gap in NH3 deposition flux and velocities in this rural environment to help address environmental impacts and the sustainability of the poultry industry. Dr. Sharara led the coordination and delivery of a national webinar, through the Livestock and Poultry Environmental Learning Community (LPELC). The webinar, The Role of Agriculture in Atmospheric Nitrogen Deposition: Sources, Impacts, and Management, brought expertise from UW-Madison (Dr. David Gay), U.S. EPA (Jesse Bash), USDA ARS (Dr. Greg Zwick), and Dr. Sharara to provide technical specialists and consultants with a comprehensive of ammonia. Through this well-attended webinar (over 120 audience members from the U.S. and Canada), evaluations revealed a gain in knowledge of ammonia drivers, impacts, as well as interventions to reduce its release.</li> </ul>   <ul> <li>In Ohio, Dr. Zhao and her team have focused on assessing existing sustainability assessment tools in the past reporting year. Through two rounds of USDA SAS proposal development efforts, Dr. Zhao has collaborated with many peer researchers and developed a conceptual structure for a sustainability assessment tool for egg production, in reference to the sustainability framework published by the U.S. Roundtable for Sustainable Poultry & Eggs (US-RSPE) in 2022. She has started to build a case scenario about a one-million-bird layer operation in Ohio.</li> </ul>   <ul> <li>In South Dakota, Dr. Yang and his team collaborated with Dr. Erin Cortus at the University of Minnesota on the 2024 Minnkota Annual Meeting in April 2024. Minnkota is an association of university extension specialists, governmental agencies, animal producers, equipment suppliers, and barn builders dedicated to addressing sustainability issues in animal production facilities. This meeting was held on the South Dakota State University campus in conjunction with the 2024 ASABE North Central Regional Meeting. The team also collaborated with Dr. Yuanhui Zhang at the University of Illinois at Urbana-Champaign on a swine air quality project funded by the Foundation for Food and Agriculture Research. Through this project, they have reached out to 12 commercial swine farms to explore potential opportunities for field monitoring and data sharing. This project aims to enhance our understanding of particulate matter emitted from swine production facilities, including its characteristics, sources, and potential safety and health risks, to help address sustainability challenges facing the swine industry. Additionally, the team collaborated with the North Dakota Pork Council and the North Dakota Livestock Alliance to develop a grant proposal for an odor footprint tool for the state. This tool will establish odor setback distances between animal production facilities and their neighbors. This information is crucial for planning and zoning new or expanding facilities, thereby supporting the continued growth of North Dakota's animal industry. Within the state of South Dakota, Dr. Yang served on an Ag Cybersecurity Curriculum development team within the SDSU Extension program. A partial goal of this work is to facilitate the implementation of cybersecure precision livestock farming technologies among animal producers. These technologies often result in smaller environmental footprints. Out-of-state collaborators of this effort included the extension agents from the University of Idaho.</li> </ul>

Publications

<ol> <li>Xiao, Y., Tian, Y., Xu, W., & Zhu, J. (2024). Photodegradation of microplastics through nanomaterials: Insights into photocatalysts modification and detailed mechanisms. Materials, 17(11), 2755. <a href="https://doi.org/10.3390/ma17112755">https://doi.org/10.3390/ma17112755</a></li> <li>Bist, R. B., Yang, X., Subedi, S., Bist, K., Paneru, B., Li, G., & Chai, L. (2024). An automatic method for scoring poultry footpad dermatitis with deep learning and thermal imaging. Computers and Electronics in Agriculture, 226, 109481. https://doi.org/10.1016/j.compag.2024.109481</li> <li>Yang, X., Dai, H., Wu, Z., Bist, R. B., Subedi, S., Sun, J., Lu, G., Li, C., Liu, T., & Chai, L. (2024). An innovative segment anything models for precision poultry monitoring. Computers and Electronics in Agriculture, 222, 109045. https://doi.org/10.1016/j.compag.2024.109045</li> <li>Yang, X., Bist, R. B., Liu, T., Applegate, T., Ritz, C., Kim, W., & Chai, L. (2024). Computer vision-based cybernetics systems for promoting modern poultry farming: A critical review. Computers and Electronics in Agriculture, 225, 109339. https://doi.org/10.1016/j.compag.2024.109339</li> <li>Yang, X., Bist, R. B., Subedi, S., Wu, Z., Liu, T., Paneru, B., & Chai, L. (2024). A machine vision system for monitoring wild birds on poultry farms to prevent avian influenza. AgriEngineering, 6(4), 3704–3718. https://doi.org/10.3390/agriengineering6040219</li> <li>Saeidifar, M., Li, G., Chai, L., Bist, R. B., Rasheed, K. M., Lu, J., Banakar, A., Liu, T., & Yang, X. (2024). Zero-shot image segmentation for monitoring thermal conditions of individual cage-free laying hens. Computers and Electronics in Agriculture, 226, 109436. https://doi.org/10.1016/j.compag.2024.109436</li> <li>Yang, X., Bist, R., Paneru, B., & Chai, L. (2024). Monitoring activity index and behaviors of cage-free hens with advanced deep learning technologies. Poultry Science, 103(11), 104193. https://doi.org/10.1016/j.psj.2024.104193</li> <li>Yang, X., Bist, R. B., Paneru, B., & Chai, L. (2024). Deep learning methods for tracking the locomotion of individual chickens. Animals, 14(6), 911. https://doi.org/10.3390/ani14060911</li> <li>Paneru, B., Bist, R. B., Yang, X., & Chai, L. (2024). Tracking dustbathing behavior of cage-free hens with machine vision technologies. Poultry Science. Advance online publication. https://doi.org/10.1016/j.psj.2024.104289</li> <li>Bist, R. B., Poudel, K., Yang, X., Paneru, B., Mani, S., Wang, D., & Chai, L. (2024). Sustainable poultry farming practices: A critical review of current strategies and future prospects. Poultry Science. Advance online publication. https://doi.org/10.1016/j.psj.2024.104295</li> <li>Bist, R. B., Yang, X., Subedi, S., Paneru, B., & Chai, L. (2024). Enhancing dust control for cage-free hens with electrostatic particle charging systems at varying installation heights and operation durations. AgriEngineering, 6(2), 1747–1759. https://doi.org/10.3390/agriengineering6020100</li> <li>Bist, R. B., Yang, X., & Subedi, S., & Chai, L. (2024). Automatic detection of bumblefoot in cage-free hens using computer vision technologies. Poultry Science. Advance online publication. https://doi.org/10.1016/j.psj.2024.103780</li> <li>Bist, R. B., Yang, X., Subedi, S., Ritz, C. W., Kim, W. K., & Chai, L. (2024). Electrostatic particle ionization for suppressing air pollutants in cage-free layer facilities. Poultry Science. Advance online publication. https://doi.org/10.1016/j.psj.2024.103494</li> <li>Paneru, B., Bist, R., Yang, X., & Chai, L. (2024). Tracking perching behavior of cage-free laying hens with deep learning technologies. Poultry Science, 103(12), 104281. https://doi.org/10.1016/j.psj.2024.104281</li> <li>Bist, R. B., Yang, X., Subedi, S., Paneru, B., & Chai, L. (2024). An integrated engineering method for improving air quality of cage-free hen housing. AgriEngineering, 6(3), 2795–2810. https://doi.org/10.3390/agriengineering6030178</li> <li>Saeidifar, M., Li, G., Lu, J., Chai, L., Bist, R., & Yang, X. (2024). Automatic segmentation of birds using a combination of object detection and foundation image segmentation models. International Journal of Advances in Electronics and Computer Science, 11(7), 2394–2835.</li> <li>Das, A. K.  and L. Chen. 2024. A Review on Electrochemical Advanced Oxidation Treatment of Dairy Wastewater. Environments 2024, 11(6), 124; https://doi.org/10.3390/environments11060124</li> <li>Sapkota, S., A. Reza, and L. Chen. 2024. Optimization of Ammonia Nitrogen Removal and Recovery from Raw Liquid Dairy Manure Using Vacuum Thermal Stripping and Acid Absorption Process: A Modeling Approach Using Response Surface Methodology. Nitrogen 2024, 5(2), 409-425: https://doi.org/10.3390/nitrogen5020026</li> <li>Reza, A., L. Chen. and X. Mao. 2024. Response surface methodology for process optimization in livestock wastewater treatment: A review. Heliyon (DOI: https://doi.org/10.1016/j.heliyon.2024.e30326)</li> <li>Das, A.K., A. Reza, and L. Chen. 2024. Optimization of pollutants removal from anaerobically digested dairy wastewater by electro-oxidation process: a response surface methodology modeling and validation. Journal of Applied Electrochemistry (DOI: 10.1007/s10800-024-02113-z)</li> <li>Xiao, Y., Tian, Y., Xiong, H., Shi, A., & Zhu, J. (2024). Compact solar-powered plasma water generator: Enhanced on-site aged seed germination with the corona dielectric barrier discharger. Frontiers of Agricultural Science and Engineering. <a href="https://doi.org/10.15302/J-FASE-2024573">https://doi.org/10.15302/J-FASE-2024573</a></li> <li>Zhan, Y., & Zhu, J. (2024). Response surface methodology and artificial neural network-genetic algorithm for modeling and optimization of bioenergy production from biochar-improved anaerobic digestion. Applied Energy, 355, 122336. <a href="https://doi.org/10.1016/j.apenergy.2023.122336">https://doi.org/10.1016/j.apenergy.2023.122336</a></li> <li>Yin, Y., Qi, X., Gao, L., Lu, X., Yang, X., Xiao, K., Liu, Y., Qiu, Y., Huang, X., & Liang, P. (2024). Quantifying methane influx from sewer into wastewater treatment processes. Environmental Science & Technology, 58, 9582–9590.</li> <li>Rubel, R. I., Wei, L., Alanazi, S., Aldekhail, A., Cidreira, A. M., Yang, X., Wasti, S., Bhagia, S., & Zhao, X. (2024). Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community. Frontiers of Agricultural Science and Engineering, 11(2), 2376366.</li> <li>Uguz, S., Anderson, G., Yang, X., Simsek, E., Osabutey, A., & Min, K. (2024). Microalgae cultivation using ammonia and carbon dioxide concentrations typical of pig barns. Environmental Technology, 45, 5899–5911.</li> <li>Rubel, R. I., Wei, L., Wu, Y., Brozel, V., Gupta, S., Alanazi, S., Ameer, S., Sobhan, A., Das, B., Osabutey, A., & Yang, X. (2024). Greenhouse evaluation of biochar-based controlled-release nitrogen fertilizer in corn production. Agricultural Research, 13(1), 113–123.</li> <li>Haleem, N., Kumar, P., Uguz, S., Jamal, Y., McMaine, J., & Yang, X. (2023). Viability of artificial rain for air pollution control: Insights from natural rains and roadside sprinkling. Atmosphere, 14(12), 1714.</li> <li>He, Y., Gong, A., Osabutey, A., Gao, T., Haleem, N., Yang, X., & Liang, P. (2023). Emerging electro-driven technologies for phosphorus enrichment and recovery from wastewater: A review. Water Research, 246, 120699 Conference Proceedings   <ol> <li>Das, A. K., A. Reza, and L. Chen. 2024. Pollutants removal from anaerobically digested dairy wastewater by electro-oxidation process: A RSM optimization and modeling, ASABE AIM 2024, Anaheim, CA. July 28-31, 2024.</li> <li>Das, A. K. and L. Chen. 2024. Ammonia removal from dairy waste stream using combined chemical coagulation and photoelectron-Fenton process: A GRA-Taguchi, RSM, and ANN based optimization and modeling, ASABE AIM 2024, Anaheim, CA. July 28-31, 2024.</li> <li>Mohammad Nazrul, Islam, L. Chen, and B. Brian He. 2024. Mitigating phosphorus runoff risk and enhancing bioavailability in dairy manure via hydrothermal carbonization with CaO addition, ASABE AIM 2024, Anaheim, CA. July 28-31, 2024.</li> <li>Chen, L. and A. Reza. 2024. Ammonia removal and recovery from anaerobically digested liquid dairy manure using vacuum thermal stripping-acid absorption process. 64th Idaho Academy of Science and Engineering Symposium-17th Intermountain Conference on the Environment Joint Symposium-Sustainability & The Earth’s Climate, Pocatello, ID. April 5-6, 2024.</li> <li>Chen, L. and Reza, A. 2023. Ammonia removal and recovery from anaerobically digested liquid dairy manure using vacuum thermal stripping-acid absorption process: a GRA-Taguchi, RSM, and RSM-ANN based optimization and modeling. 2023 Northwest Bioenergy Summit, Kennewick, WA. October 10-12, 2023.</li> <li>Xiao, Y. and Zhu, J. 2024. Enhanced seed germination with solar-powered plasma water generator. ASABE 117th Annual International Meeting. Paper#: 2400189. Anaheim, CA. July 28-31, 2024.</li> <li>Cherotich, S., Wang-Li, L., Anderson, K., Classen, J., & Shi, W. (2024, July 28–31). Ammonia concentrations, deposition, and soil properties as impacted by the deposition in the near fields of a poultry production facility (Presentation No. 2400324). Paper presented at the 2024 ASABE Annual International Meeting (AIM), Anaheim, CA.</li> <li>Li, P., Herkins, M., Knight, R., Zhao, L., Akter, S., & Wang-Li, L. (2024, July 28–31). Comparison of three on-field measurement methods for low-level ammonia concentrations at ambient locations of a poultry layer production facility. Paper presented at the 2024 ASABE Annual International Meeting (AIM), Anaheim, CA.</li> <li>Zhu, H., E. Ozkan, J. Theodoro, H. Jeon, J. Campos, and L.Y. Zhao. 2024. Modified Design of Open-Circuit, Centrifugal-Fan Driven Wind Tunnel to Produce Uniform Laminar Air Flows. Presentation (No. 2401309) at 2024 ASABE Annual International Meeting, Anaheim, CA, July 28-31, 2024.</li> <li>Li, P., M. Herkins, R. Knight, L.Y. Zhao, S. Akter, L. Wang-Li, J.Q. Ni, and A. Heber. 2024. Comparison of three on-field measurement methods for low-level ammonia concentrations at ambient locations of a poultry layer production facility. Presentation (No. 2401175) at 2024 ASABE Annual International Meeting, Anaheim, CA, July 28-31, 2024.</li> <li>Geng, Y., D. Jepsen, L.Y. Zhao, T. Reponen. 2024. Assessing the protection provided by the N95 filtering facepiece respirators in grain dust environments: A case study of Ohio farmers.  Presentation (No. 2400691) at 2024 ASABE Annual International Meeting, Anaheim, CA, July 28-31, 2024.</li> <li>Herkins M., R. Knight, X. Tong, L.Y. Zhao, T. Yazbeck, J. Missik, G. Bohrer. 2023. Validating an ammonia dispersion model near a commercial poultry facility using AERMOD. Presentation at 2023 ASABE Annual International Meeting, Omaha, Nebraska, July 8-12, 2023. </li> <li>Haleem, N., Yuan, J., Uguz, S., Ucok, S., Gu, Z., Yang, X. (2024). DC-assisted flocculation of Scenedesmus dimorphus. In American Society of Agricultural and Biological Engineers (ASABE) 2024 Annual Meeting, Anaheim, CA.</li> <li>Kumar, P., Tiwari, S., Uguz, S., Yang, X. (2024). Microbial composition of swine barn bioaerosol using next-generation sequencing. In ASABE 2024 Annual Meeting, Anaheim, CA.</li> <li>Uguz, S., Kumar, P., Tiwari, S., Yang, X. (2024). Assessment of low-cost PM sensors for their applicability in swine barns. In ASABE 2024 Annual Meeting, Anaheim, CA.</li> <li>Alahe, M.A., Kemeshi, J., Chang, Y., Won, K., Yang, X., Sher, M. (2024). Securing agricultural data with encryption algorithms on embedded GPU-based edge computing devices. In 16th International Conference on Precision Agriculture, Manhattan, KS.</li> <li>Kumar, P., Tiwari, S., Haleem, N., Uguz, S., Yang, X. (2024). Bioaerosols downwind from animal production facilities: A landscape analysis of existing knowledge. In 2024 ASABE North Central Regional Section Meeting, Brookings, SD.</li> <li>Haleem, N., Yang, X., Yuan, J. (2024). DC-assisted flocculation of Scenedesmus dimorphus. In 2024 ASABE North Central Regional Section Meeting, Brookings, SD.</li> <li>Uguz, S., Yang, X., Anderson, G. (2024). Biological treatment of air pollutants from animal feeding operations using photobioreactor systems. In 2024 ASABE North Central Regional Section Meeting, Brookings, SD.</li> <li>Cheng, R., Liyanage, D., Mahdaviarab, A., Pahlavanyali, K., Zhang, Y., Wang, X., and Liu, Z. Enhancing Animal/Food Waste Management through Composting: A Comparative Analysis of Quality Improvement with Biochar/Additive. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Mahdaviarab, A., Cheng, R., Pahlavanyali, K., Wang, X., and Liu, Z. Adoption of Biogas Production from Animal Waste: Case Studies of Texas Farms. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Mahdaviarab, A., Cheng, R., Liyanage, D., Kincaid, N., Zhou, R., Li, Y., Wang, X., and Liu, Z. Identifying and Characterizing Animal Wastewater Lagoons via Satellite Remote Sensing. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Liyanage, D., Mahdaviarab, A., Zhou, R., Wang, X., and Liu, Z. Virtual Reality Videos for Delivery of Extension Educational Materials on Manure and Mortality Management. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Mahdaviarab, A., Pahlavanyali, K., Cheng, R., Wang, X., and Liu, Z. Estimation of Dairy Lagoon Water Quality Using Satellite Images. 2024. Data-Driven Intelligent Agricultural System Symposium, College Station, TX.</li> <li>Pahlavanyali, K., Cheng, R., Mahdaviarab, A., Galvan, L., Wang, X., and Liu, Z. Utilizing Black Soldier Fly (Hermetia illucens) Larvae for Optimizing Dairy Waste Management. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Zhang, Y., Cheng, R., Mahdaviarab, A., Wang, X., and Liu, Z. Accurate and Robust Biochar Yield and Composition Prediction via ResNet-Based Autoencoder. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> <li>Zhou, R., Cheng, R., Liyanage, D., Mahdaviarab, A., Wang, X., and Liu, Z. Photocatalytic Degradation of Organic Pollutants in Agricultural Wastewater by Novel Two-Dimensional Material. 2024. ASABE Annual International Meeting, Anaheim, CA.</li> </ol> </li> </ol>

Impact Statements

In Idaho, a research team, which includes engineers, economists, soil scientists, agronomists, and animal scientists from Washington, Oregon, and Idaho, has been formed to address challenges facing the Pacific Northwest (PNW) region’s dairy and potato production systems. Research ideas shared during the team’s meetings strengthened our capabilities to support the dairy and potato industries in PNW. Dairy sustainability research gaps and priorities for the Intermountain Region were identified. The identified priorities have been used for guiding research projects. Additionally, journal papers based on our ISAID project research have been published. These research findings have improved stakeholders’ knowledge of manure treatment.
OH leadership, with support through S1074 participation, supported USDA SAS proposal development, seminars on technology review, and the development of new technologies. These outcomes are expected to enable egg farmers to optimize indoor environmental management, improve animal health and performance, and reduce the detrimental impacts of diseases such as HPAI. The new ventilation systems will help egg producers address significant challenges in maintaining uniform bird distribution in cage-free housing, minimizing disease transmission, and effectively reducing heat or cold stress. Training provided to farmers will support the adoption of effective indoor environmental quality management and new ventilation systems, reducing HPAI and other disease outbreaks, ensuring stable egg supplies, and increasing egg production safety and efficiency in the U.S.
SD, MN, IA and NE collaborative work on the 2024 Minnkota Annual Meeting drew approximately 20 attendees from the Upper Midwest, including Iowa, Minnesota, Nebraska, and South Dakota. Held in conjunction with the 2024 ASABE North Central Regional Meeting, this allowed attendees to connect with a broader network of students, faculty, staff, and industry professionals. This multidisciplinary participation received overwhelmingly positive feedback.
In North Carolina, the LPELC webinar that Dr. Sharara organized, “The Role of Agriculture in Atmospheric Nitrogen Deposition …”, provided diverse stakeholder and industry groups with a comprehensive understanding of needs, challenges, and opportunities in managing the nitrogen cycle in food animal production. Our community expertise both in the mechanistic underpinnings of this cycle as well as broad implications to the farm and region, positions S-1074 to lead efforts in this sustainability dimension.
SD leadership in a swine air quality project, although in its early stages, has already yielded valuable data demonstrating the significant role of particulate matter in disease transmission. The team has identified over 100 pathogenic bacterial strains and approximately 60 antimicrobial resistance genes. These discoveries have been reported to the funding agency and the National Pork Board.
The AR team’s research and extension effort have provided key information to both the scientific community and the concerned industries about improving anaerobic digestion efficiency to treat dry poultry litter. The concerned industries, including poultry producers in not only Arkansas but also those poultry-heavy states, will benefit from the findings of this project because such technology is highly sought by them as well. The new information obtained from this project involving nanotechnology in the digestion process will increase the confidence of the poultry industry that the long-term, recalcitrant poultry litter issue may be resolved in the near future, so their continued growth will be sustained, and the consumers' demand for chicken meat will be satisfied.