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1. Artificial Intelligence Applications in Animal Production Systems for Climate Resilience and Sustainability: A Comprehensive Review

   https://doi.org/10.3390/agriculture16111146  

   Abdel-Wareth, Ahmed_A A; Ahmed, Ahmed A; Taqi, Mohamed O; Salahudin, Md; Lohakare, Jayant (May 2026, Agriculture)

   The agricultural sector, particularly animal production, faces numerous unprecedented challenges driven by climate change, resource depletion, and an ever-growing global demand for quality food. These challenges are further compounded by the increasing environmental impact of livestock farming, including greenhouse gas emissions, overuse of water and land resources, and the destruction of vital ecosystems. Ensuring the sustainability of animal production systems while mitigating the negative environmental impacts of these factors is essential for future global food security. As the demand for animal-derived products continues to rise, there is a pressing need for innovations that can enhance productivity without compromising environmental integrity or animal welfare. Artificial intelligence (AI) has emerged as a transformative technology with the potential to revolutionize the animal production industry. AI-driven solutions offer promising avenues for optimizing production efficiency, enhancing animal health and welfare, and reducing the environmental footprint of livestock farming. Machine learning, sensor technologies, and advanced data analytics are being increasingly utilized to monitor and predict various aspects of animal farming, such as feed efficiency, disease prevention, and climate resilience. These technologies enable farmers to make data-driven decisions, fostering more sustainable and environmentally responsible practices. This review examines the integration of AI into animal production systems, emphasizing its applications in climate change mitigation, resource management, and advancing sustainability. The discussion addresses how AI technologies can be utilized to improve productivity while minimizing environmental impact and enhancing animal welfare. Additionally, the paper outlines future opportunities, challenges, and potential barriers to integrating AI technologies into livestock farming, thereby ensuring long-term sustainability amid global challenges. 

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2. Big data and smart-connected epidemiology in practice: the value for prevention and control of infectious diseases

   Martínez-López, B (December 2018, 99th Conference of Research Workers in Animal Diseases)

   Livestock industry is daily producing large amounts of multi-scale data (pathogen-, animal-, site-, system-, regional- level) from different sources such as diagnostic laboratories, trade and production records, management and environmental monitoring systems; however, all these data are still presented and used separately and are largely infra-utilized to timely (i.e., near real-time) inform livestock health decisions. Recent advances in the automation of data capture, standardization, multi-scale integration and sharing/communication (i.e. The Internet Of Things) as well as in the development of novel data mining analytical and visualization capabilities specifically adapted to the livestock industry are dramatically changing this paradigm. As a result, we expect vertical advances in the way we prevent and manage livestock diseases both locally and globally. Our team at the Center for Animal Disease Modeling and Surveillance (CADMS), in collaboration with researchers at Iowa State University and industry leaders at Boehringer Ingelheim and GlobalVetLINK have been working in an exceptional research-industry partnership to develop key data connections and novel Big Data capabilities within the Disease BioPortal (http://bioportal.ucdavis.edu/). This web-based platform includes automation of diagnostic interpretations and facilitates the combined analysis of health, production and trade data using novel space-time-genomic visualization and data mining tools. Access to confidential databases is individually granted with different levels of secure access, visualization and editing capabilities for participating producers, labs, veterinarians and other stakeholders. Each user can create and share customized dashboards and reports to inform risk-based, more cost-effective, decisions at site, system or regional level. Here we will provide practical examples of applications in the swine, poultry and aquaculture industries. We hope to contribute to the more coordinated and effective prevention and control of infectious diseases locally and globally. 

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3. Four decades of nitrous oxide emission from Chinese aquaculture underscores the urgency and opportunity for climate change mitigation

   https://doi.org/10.1088/1748-9326/ac3177  

   Zhou, Yangen; Huang, Ming; Tian, Hanqin; Xu, Rongting; Ge, Jian; Yang, Xiaogang; Liu, Rongxin; Sun, Yunxia; Pan, Shufen; Gao, Qinfeng; et al (November 2021, Environmental Research Letters)

   Abstract As the fastest growing food production sector in the world, aquaculture may become an important source of nitrous oxide (N 2 O)—a potent greenhouse gas and the dominant source of ozone-depleting substances in the stratosphere. China is the largest aquaculture producer globally; however, the magnitude of N 2 O emission from Chinese aquaculture systems (CASs) has not yet been extensively investigated. Here, we quantified N 2 O emission from the CASs since the Reform and Opening-up (1979–2019) at the species-, provincial-, and national-levels using annual aquaculture production data, based on nitrogen (N) levels in feed type, feed amount, feed conversion ratio, and emission factor (EF). Our estimate indicates that over the past 41 years, N 2 O emission from CASs has increased approximately 25 times from 0.67 ± 0.04 GgN in 1979 to 16.69 ± 0.31 GgN in 2019. Freshwater fish farming, primarily in two provinces, namely, Guangdong and Hubei, where intensive freshwater fish farming has been adopted in the past decades, accounted for approximately 89% of this emission increase. We also calculated the EF for each species, ranging from 0.79 ± 0.23 g N 2 O kg −1 animal to 2.41 ± 0.14 g N 2 O kg −1 animal. The results of this study suggest that selecting low-EF species and improving feed use efficiency can help reduce aquaculture N 2 O emission for building a climate-resilient sustainable aquaculture. 

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4. Zooarchaeological Analysis of a Spanish Late Colonial and Territorial Periods Site in Northern Rio Grande, New Mexico

   Jaramillo, Sara (April 2026, ScholarWorks at UMass Boston Andrew Fiske Memorial Center for Archaeological Research Publications)

   This poster examines faunal remains from El Rancho de las Golondrinas (LA 127375) to investigate animal production, consumption, and labor practices in northern New Mexico during the Late Colonial and Territorial periods. By applying standard zooarchaeological methods and comparing the assemblage to an earlier Spanish Colonial site (LA 20,000), the study explores changes and continuities in regional ranching economies under shifting political and economic conditions. Results indicate that sheep/goats (Ovis/Capra) and cattle (Bos taurus) remained the dominant domesticated animals, demonstrating the long-term importance of pastoralism in New Mexico. Variations in the relative abundance of livestock through time may reflect changes in labor organization, land use, and market participation associated with the transition from Spanish to Mexican and later U.S. governance. These findings highlight the resilience of herding-based economies and suggest that systems such as the partido livestock-leasing arrangement played a significant role in shaping animal production and labor relations in the region. 

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5. Global agriculture as an energy transfer system and the energy yield of world agriculture 1961-2013

   https://doi.org/10.1002/ep.12799  

   Boss, Stephen K.; Montana, Quinn; Barnett, Barbara (November 2017, Environmental Progress & Sustainable Energy)

   The global agricultural system is an energy transfer system converting solar radiation to stored chemical energy in the biosphere through photosynthesis and animal metabolism. Stored energy in the agricultural system is principally in the form of carbohydrates, proteins, fats, and oils that humanity appropriates for food, fiber, and fuel. The total annual production of global agriculture was tabulated using data from the Food and Agriculture Organization from 1961 to 2013. Annual agricultural production for each agricultural item (T y21) was converted to energy yield (kJ y21) utilizing published proximate analyses (% moisture, % protein, % carbohydrate, % fat/lipid, and % ash). Global agricultural energy yield grew linearly over the 1961–2002 interval. From 2002 onward, global agricultural energy yield also grew linearly, but at a rate 2 times the 1961–2002 rate. Overall, agricultural energy yield more than tripled from 1961 to 2013. Unsurprisingly, energy output of global crops dominated, averaging 85.560.4% of total energy output. Livestock and poultry production averaged 13.660.4% of annual agricultural energy output, while world fisheries and aquaculture averaged 0.860.1% of global energy output. From 1961 to 2013, the feeding potential of global agricultural energy yield exceeded the human metabolic energy requirement by an average multiple of 2.160.18. Thus, agricultural production is more than sufficient to feed “The Global Mouth” into the future, and feeding world population is not a production problem per se. Instead, the inability of global agriculture to meet worldwide food requirements results from systemic energy losses associated with significant global food waste, diversion of food energy as feed to livestock and poultry, and appropriation of primary agricultural output for biofuels synthesis. 

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