Covered anaerobic lagoons (CALs) are Latin America\'s main livestock waste treatment systems. Mexico has 680 CALs that present low biogas yields (0.05 m3 m-3 digester d-1) and low COD removal rates (< 60%). This work focused on diagnosing CAL´s low performance in dairy farms by determining and analyzing operational parameters. Seven CALs located in the main dairy basin of Mexico were analyzed. The sampling areas for each CAL were the supernatant, the active zone, settled sludge, and digester inlet and outlet. The variation of the process parameter values corroborated that CALs appeared stratified and not working as expected. The sludge zone, comprising 50-58% of total solids content and 1-15% of total CALs volume, showed an elemental compounds content suitable for organic fertilizer (340, 48, and 5 kg t-1 of C, N, and S, respectively). However, this zone contained, at least, 85% of the slowly hydrolysable material; the methanogenic potential was less than 87 mL CH4 g VS-1, and the C/N ratio ranged from 4.9 to 17, outside of the optimal range. The biogas produced did not exceed 60% of methane content and more than 3000 ppm of H2S. The sludge zone significantly influences the lagoon\'s dynamics since it is a nutrient sink. Furthermore, the lack of agitation is the leading cause for the low energy yield and the low removal of organic matter rate. This work provides valuable information to address the operational problems within the CALs improving our understanding that shall allow proposing reactivation alternatives.

Biotrickling filter (BTF) is often used for purification of waste gas from swine houses, with vital information still needed regarding interaction effects among multiple gas pollutants removal and also the formation of byproducts especially nitrous oxide (N2O, a strong greenhouse gas) due to the relative high NH3 concentration level compared to other gases. In this study, gas removal and N2O production were compared between two BTFs, where the inlet gas of BTF-1 contained NH3 and H2S while p-cresol was additionally supplied to BTF-2. At inlet load (IL) between 3.67 and 18.91 g m-3 h-1, removal efficiencies of NH3 exceeded 95% for both BTFs. As alternative strategy, adding thiosulfate improved H2S removal. Interestingly, presence of p-cresol to some extent promoted H2S removal at IL of 0.56 g m-3 h-1possibly due to effect on pH value of circulating solution. Similar to NH3, removal efficiencies of p-cresol were higher than 95% at an average IL of 2.98 g m-3 h-1. Gas residence time, pH of circulating solution and inlet loading were identified as key factors affecting BTF performance, but the response of individual gas compound to these factors was not consistent. Overall, p-cresol enhanced N2O generation although the effects were not always significant. High-throughput sequencing results showed that Proteobacteria accounted for the largest proportion of relative abundance and BTF-2 had much richer microbial diversity compared to BTF-1. Thermomonas, Comamonas, Rhodanobacter and other bacterial genus capable of denitrification were detected in both BTFs, and their corresponding abundances in BTF-2 (10.9%, 8.7% and 5.2%) were all greater than those in BTF-1 (0.4%, 0.3% and 2.0%), indicating that more denitrification may occur within BTF-2 and higher N2O could have been generated. This study provided evidence that organic gas components, served as carbon source, may increase the N2O production from BTF when treating waste gases containing NH3.

Digital twins aim to optimize practices implemented in various sectors by bridging the gap between the physical and digital worlds. Focusing on open-field agriculture, livestock farming, and forestry and reviewing the current applications in these domains, this paper reveals the multifaceted roles of digital twins. Diverse key aspects are examined, including digital twin integration and maturity level, means of data acquisition, technological capabilities, and commonly used input and output features. Through the prism of four primary research questions, the state of the art of digital twins, the extent of their achieved integration, and an overview of the critical issues and potential advancements are provided in the landscape of the sectors under consideration. The paper concludes that in spite of the remarkable progress, there is a long way towards achieving full digital twin. Challenges still persist, while the key factor seems to be the integration of expert knowledge from different stakeholders. In light of the constraints identified in the review analysis, a new sector-specific definition for digital twins is also suggested to align with the distinctive characteristics of intricate biotic and abiotic systems. This research is anticipated to serve as a useful reference for stakeholders, enhancing awareness of the considerable benefits associated with digital twins and promoting a more systematic and comprehensive exploration of this transformative topic.

Antimicrobial resistance (AMR) in livestock is a complicated and multi-sectoral risk that threatens public health in the interactions between humans, animals, and environment. Through their increased awareness of AMR issues, consumers can make a significant impact on regulations and strategies to reduce or eliminate the use of antimicrobials use. This study aims to provide evidence-based data for promoting the prudent use of antimicrobials (PUA) in the livestock industry to reduce the risk of AMR and increase animal welfare by identifying consumers\' intentions to support PUA practices in livestock farming. An online survey was conducted on 1000 respondents in South Korea to examine their intention to pay more for PUA practices in livestock farming at state and individual levels against their pro-animal attitude, risk perception of antimicrobial overuse, trust in antimicrobial overuse control, and perceived value of PUA practices. The survey data was analyzed using multiple linear regression to identify the determinants of Korean consumers\' support for PUA practices. Approximately 86.3% of the respondents supported government-level spending for PUA in livestock farming, and the same portion of respondents intended to pay more for livestock products that complied with the PUA principle. The four attitudinal variables-pro-animal attitude, consumers\' risk perception, trust in antimicrobial resistance control, and perceived value of PUA-positively affected both state- and individual-level support. Overall, our findings highlight the Korean consumers\' demand for reducing the risk of AMR and their perceived universal value of PUA for humans and animals.

Adverse health effects have been linked with exposure to livestock farms, likely due to airborne microbial agents. Accurate exposure assessment is crucial in epidemiological studies, however limited studies have modelled bioaerosols. This study used measured concentrations in air of livestock commensals (Escherichia coli (E. coli) and Staphylococcus species (spp.)), and antimicrobial resistance genes (tetW and mecA) at 61 residential sites in a livestock-dense region in the Netherlands. For each microbial agent, land use regression (LUR) and random forest (RF) models were developed using Geographic Information System (GIS)-derived livestock-related characteristics as predictors. The mean and standard deviation of annual average concentrations (gene copies/m3) of E. coli, Staphylococcus spp., tetW and mecA were as follows: 38.9 (±1.98), 2574 (±3.29), 20991 (±2.11), and 15.9 (±2.58). Validated through 10-fold cross-validation (CV), the models moderately explained spatial variation of all microbial agents. The best performing model per agent explained respectively 38.4%, 20.9%, 33.3% and 27.4% of the spatial variation of E. coli, Staphylococcus spp., tetW and mecA. RF models had somewhat better performance than LUR models. Livestock predictors related to poultry and pig farms dominated all models. To conclude, the models developed enable enhanced estimates of airborne livestock-related microbial exposure in future epidemiological studies. Consequently, this will provide valuable insights into the public health implications of exposure to specific microbial agents.

The creation of targeted policies and actions to help small-scale livestock keepers and reduce the risks associated with disease outbreaks in this sector is hampered by the scarcity of information about smallholder farmers. Smallholders play a crucial part in disease outbreaks containment, hence there is a need for better monitoring methods that take this population into account while gathering data. According to the literature, these communities frequently use social media as a channel for communication and information exchange. In this study we conducted social network analysis of an influential smallholder within the UK and visualised the user follower network. Additionally, we performed influential user analysis, Twitter user categorisation, and community detection to uncover more insights into the livestock farming networks. Our findings reveal distinct communities within the smallholder farming sector and identify influential users with the potential to impact information dissemination and animal health practices. The study also highlights the role of community structure in surveillance and control of animal diseases and emphasises the need for further research to refine our understanding of these communities and their unique characteristics. This work contributes to the growing body of literature on small-scale livestock farming in the UK and underscores the importance of incorporating smallholder communities into disease surveillance and control efforts.

Rodents in livestock farming constitute a threat to the one health approach. In the present observational case study, livestock farmers worked together with a pest controller within a pilot project. The aim of the study was to assess determinants associated with rodent-prevention potential. The study started in March 2019 on 24 livestock farms in a municipality in North Rhine-Westphalia/Germany. At the beginning of the project a survey on the determinants expected to be related to prevention potential was conducted. To determine the potential for rodent prevention, an expert person, who was not involved in the project before, assessed the on-site conditions of the farms after 1.5 years of project duration in 2020. The potential for rodent prevention was good for about half of the farms. There were significant differences in the willingness to make changes at the project\'s start between farms with a high and a low potential for rodent prevention after 1.5 years. There is a general need for action to provide farmers with more practical information on rodent control. This is aggravated by the insufficient advisory services offered to farmers. This study confirms the importance of implementing preventive measures in the control of rodents to ensure that anticoagulant rodenticides are handled responsibly to reduce the impact on non-target species.

BACKGROUND: Evidence on the public health relevance of exposure to livestock farm emissions is increasing. Research mostly focused on chemical air pollution, less on microbial exposure, while endotoxins are suggested relevant bacterial components in farm emissions. Acute respiratory health effects of short-term exposure to livestock-related air pollution has been shown for NH3 and PM10, but has not yet been studied for endotoxin. We aimed to assess associations between lung function and short-term exposure to livestock farming emitted endotoxin in co-pollutant models with NH3 and PM10.
METHODS: In 2014/2015, spirometry was conducted in 2308 non-farming residents living in a rural area in the Netherlands. Residential exposure to livestock farming emitted endotoxin during the week prior to spirometry was estimated by dispersion modelling. The model was applied to geo-located individual barns within 10 km of each home address using provincial farm data and local hourly meteorological conditions. Regional week-average measured concentrations of NH3 and PM10 were obtained through monitoring stations. Lung function parameters (FEV1, FVC, FEV1/FVC, MMEF) were expressed in %-predicted value based on GLI-2012. Exposure-response analyses were performed by linear regression modelling.
RESULTS: Week-average endotoxin exposure was negatively associated with FVC, independently from regional NH3 and PM10 exposure. A 1.1% decline in FVC was estimated for an increase of endotoxin exposure from 10th to 90th percentile. Stratified analyses showed a larger decline (3.2%) for participants with current asthma and/or COPD. FEV1 was negatively associated with week-average endotoxin exposure, but less consistent after co-pollutant adjustment. FEV1/FVC and MMEF were not associated with week-average endotoxin exposure.
CONCLUSIONS: Lower lung function in non-farming residents was observed in relation to short-term residential exposure to livestock farming emitted endotoxin. This study indicates the probable relevance of exposure to microbial emissions from livestock farms considering public health besides chemical air pollution, necessitating future research incorporating both.

Pig husbandry constitutes a significant segment within the broader framework of livestock farming, with porcine well-being emerging as a paramount concern due to its direct implications on pig breeding and production. An easily observable proxy for assessing the health of pigs lies in their daily patterns of movement. The daily movement patterns of pigs can be used as an indicator of their health, in which more active pigs are usually healthier than those who are not active, providing farmers with knowledge of identifying pigs\' health state before they become sick or their condition becomes life-threatening. However, the conventional means of estimating pig mobility largely rely on manual observations by farmers, which is impractical in the context of contemporary centralized and extensive pig farming operations. In response to these challenges, multi-object tracking and pig behavior methods are adopted to monitor pig health and welfare closely. Regrettably, these existing methods frequently fall short of providing precise and quantified measurements of movement distance, thereby yielding a rudimentary metric for assessing pig health. This paper proposes a novel approach that integrates optical flow and a multi-object tracking algorithm to more accurately gauge pig movement based on both qualitative and quantitative analyses of the shortcomings of solely relying on tracking algorithms. The optical flow records accurate movement between two consecutive frames and the multi-object tracking algorithm offers individual tracks for each pig. By combining optical flow and the tracking algorithm, our approach can accurately estimate each pig\'s movement. Moreover, the incorporation of optical flow affords the capacity to discern partial movements, such as instances where only the pig\'s head is in motion while the remainder of its body remains stationary. The experimental results show that the proposed method has superiority over the method of solely using tracking results, i.e., bounding boxes. The reason is that the movement calculated based on bounding boxes is easily affected by the size fluctuation while the optical flow data can avoid these drawbacks and even provide more fine-grained motion information. The virtues inherent in the proposed method culminate in the provision of more accurate and comprehensive information, thus enhancing the efficacy of decision-making and management processes within the realm of pig farming.

The increasing environmental abundance of reactive N (\'Nr\') entails many adverse effects for society such as soil degradation and eutrophication. In addressing the global surplus of N, there is a pressing need to quantify local sources and dynamics of Nr. Although quantified as an important anthropogenic source of Nr, the spatiotemporal patterns of ammonia (\'NH3\') emitted by dairy farming and its resulting pressure on local surface waters lacks quantification. Quantification could optimize farm management with minimized losses of valuable nitrogen and protection of freshwater ecology. This study aimed to unravel spatiotemporal dynamics of ammonia nitrogen emitted by a dairy farm in the atmospheric and aquatic geo-ecosphere. Atmospheric NH3 and aqueous ammonium (\'NH4+\') were determined over time, together with meteorological variables. Aquatic biomonitors (periphyton and phytoplankton) were employed to monitor the spatial impacts of cattle-stable emitted NH3. Atmospheric NH3 on the farm was significantly regulated by wind, sharply declining over increasing distances from the stable (average decrease in the dominant wind direction from 55.5 μg/m3 at 20 m to 5.8 μg/m3 at 500 m, in the other wind directions values decreased from 38.3 μg/m3 to 6.0 μg/m3). This was also reflected in local surface water concentrations of NH4+, with average concentrations decreasing from 37.0 mg [NH4+-N]/L at 65 m to 4.8 mg [NH4+-N]/L in the dominant wind direction, and from 1.2 to 0.7 in other directions. Periphyton biomass, total N (\"TN\") and δ15N all significantly reflected spatiotemporal dynamics of atmospheric NH3 and aqueous NH4+, as did phytoplankton TN. The cattle stable significantly influenced local water quality through atmospheric spreading of NH3, and both aquatic biomonitors were influenced by and reflected dairy farm emitted NH3 with a sharp dilution over distance. This study strongly underlines the importance of atmospheric transport of dairy farm emitted NH3 and its effects on local water quality.