Bacterial Communities of House Flies from Dairy Farms Highlight Their Role as Reservoirs, Disseminators, and Sentinels of Microbial Threats to Human and Animal Health.

Adult house flies (Musca domestica L.) inhabiting dairy farms not only are nuisance pests but also harbor and disseminate bacteria. We examined the bacterial community composition, diversity, environmental sources, and prevalence in individual adult female house flies and cattle manure samples collected monthly from Florida, North Carolina, and Tennessee dairy farms between May and August 2021. Individual house flies carried diverse bacterial communities, encompassing all bacterial taxa (100%) identified across manure samples, and additional species likely acquired from the animals. Bacterial community assemblage in house flies and manure samples within farms varied by month. Some taxa were differentially associated with either house flies (Corynebacterium, Acinetobacter, and Staphylococcus) or manure samples (Treponema, Succinivibrio, and Clostridia). House fly bacterial communities mostly contained specialist species originating from manure, with several taxa (Escherichia, Corynebacterium, Turicibacter) being potential pathogens of livestock and humans. These findings further support the role of house flies as carriers of cattle-associated bacteria, including pathogens, and their potential for disseminating these microbes among cattle and to neighboring environments. Since their bacterial communities provide a snapshot of their surrounding environment, house flies also serve as effective sentinels in xenosurveillance strategies.

An agroecological approach to preparation and use of a milk protein production baseline.

Commercial dairy production occurs in a complex management environment, but increasingly, the dairy manager is expected to provide detailed reporting of productivity and environmental outcomes, for which conventional research methods double-blind crossover or case:control trials are inappropriate. This paper demonstrates the development of a milk protein production monitoring tool using a temporal (baseline) control in longitudinal, census-type investigations of modulation of system performance in response to factor change. It utilises farm-derived current and historical data, and contrasts seasonal responses with those achieved on neighbouring farms in a 2 × 2 contingency table. The approach is then shown to be useful in assessing the effect of two approaches to moderating milk urea concentration. Firstly, milk urea content can be monitored as it falls due to reduced feed protein content, and this fall can be arrested when milk protein content starts to decline relative to the value expected for the herd at any lactation stage. Secondly, by providing a dietary intervention aimed at increasing the availability of metabolic energy in the last month before calving, udder development can be augmented, leading to greater protein secretion capacity, meaning greater utilisation of circulating amino acids, and thus more limited substrate for urea synthesis. Thus, the changing impact of differing nutrition practices on dairy herd nitrogen excretion to environment can be followed with daily precision. In principle this approach can provide useful insights into a wide range of practical management interventions.

"They Can't Possibly Understand What I'm Going Through": Female Farmers' Perspectives on Barriers to Care in Georgia.

The purpose of this study was to explore female farmers' perspectives on barriers to engaging with resources for physical and mental healthcare faced by agriculture producers in the state of Georgia. In-depth interviews were conducted with female farm owners and managers (n = 16) across the state. Interviews were recorded and transcribed, and researchers coded interviews separately before thematic analysis was used to identify common themes. Three primary themes were identified: (i) formal healthcare challenges, (ii) stigma, and (iii) cultural norms. Formal healthcare challenges included time constraints, healthcare costs, and a lack of cultural competence from healthcare providers. Both community and self-stigma were identified as barriers to engaging with mental health resources. Cultural norms that acted as a barrier to care included the prioritization of farm operations, self-reliance, pride, and the minimization of health concerns. Interviewees identified gender differences in the impact of stigma and cultural norms, reporting that these sociocultural barriers were more prominent among older, male producers. Central to many of these barriers is the concept of 'farm identity', where farmers' commitment to their operations consistently trumped concerns about physical or mental health. Future efforts to improve health outcomes among farmers should utilize the concept of farm identity as a guide for tailoring interventions and improving cultural competence among rural healthcare providers.

An Improved Instance Segmentation Method for Complex Elements of Farm UAV Aerial Survey Images.

Farm aerial survey layers can assist in unmanned farm operations, such as planning paths and early warnings. To address the inefficiencies and high costs associated with traditional layer construction, this study proposes a high-precision instance segmentation algorithm based on SparseInst. Considering the structural characteristics of farm elements, this study introduces a multi-scale attention module (MSA) that leverages the properties of atrous convolution to expand the sensory field. It enhances spatial and channel feature weights, effectively improving segmentation accuracy for large-scale and complex targets in the farm through three parallel dense connections. A bottom-up aggregation path is added to the feature pyramid fusion network, enhancing the model's ability to perceive complex targets such as mechanized trails in farms. Coordinate attention blocks (CAs) are incorporated into the neck to capture richer contextual semantic information, enhancing farm aerial imagery scene recognition accuracy. To assess the proposed method, we compare it against existing mainstream object segmentation models, including the Mask R-CNN, Cascade-Mask, SOLOv2, and Condinst algorithms. The experimental results show that the improved model proposed in this study can be adapted to segment various complex targets in farms. The accuracy of the improved SparseInst model greatly exceeds that of Mask R-CNN and Cascade-Mask and is 10.8 and 12.8 percentage points better than the average accuracy of SOLOv2 and Condinst, respectively, with the smallest number of model parameters. The results show that the model can be used for real-time segmentation of targets under complex farm conditions.

Wild sympatric rodents inhabiting pig farm environments may facilitate the spillover of Enterocytozoon bieneusi from pig farms.

Enterocytozoon bieneusi is a zoonotic pathogen prevalent in mammalian and avian hosts across the globe. Wild small mammals, being abundant worldwide, serve as important sources of zoonotic disease transmission to humans. Here, 227 fecal samples were collected from five rodent and shrew species on 34 pig farms in China to investigate the prevalence and molecular characterization of E. bieneusi. The overall prevalence of E. bieneusi was 17.18% (39/227), with a distribution of 23.53% (32/136) in Rattus tanezumi, 8.62% (5/58) in Rattus norvegicus, and 8.00% (2/25) in Mus musculus. Eight E. bieneusi genotypes were identified, comprising four known genotypes: D (n = 8), EbpC (n = 8), PigEBITS7 (n = 9), and EbpA (n = 2), and four novel genotypes: CHPR1 (n = 7), CHPR2 (n = 1), CHPR3 (n = 2), and CHPR4 (n = 2). This study is the first to report E. bieneusi in rodents from pig farms in Henan, Shaanxi, and Shanxi Provinces in China. The host range of genotype EbpC was expanded with its first detection in M. musculus and R. tanezumi. All identified E. bieneusi genotypes belong to group 1, raising concerns about these sympatric rodents being reservoirs of zoonotic transmission. Moreover, the widespread distribution of genotype EbpC suggests potential cross-species transmission between sympatric rodents and domestic pigs. Our findings highlight the potential role of sympatric rodents in facilitating the spillover of E. bieneusi from pig farms, which could pose a potential public health threat.

Title: Les rongeurs sympatriques sauvages vivant dans les élevages porcins peuvent faciliter la propagation d'Enterocytozoon bieneusi. Abstract: Enterocytozoon bieneusi est un pathogène zoonotique répandu mondialement chez les hôtes mammifères et aviaires. Les petits mammifères sauvages, abondants dans le monde entier, constituent d'importantes sources de transmission de maladies zoonotiques à l'homme. Ici, 227 échantillons fécaux ont été collectés auprès de cinq espèces de rongeurs et de musaraignes dans 34 élevages porcins en Chine pour étudier la prévalence et la caractérisation moléculaire d'E. bieneusi. La prévalence globale d'E. bieneusi était de 17,18 % (39/227), avec une distribution de 23,53 % (32/136) chez Rattus tanezumi, 8,62 % (5/58) chez Rattus norvegicus et 8,00 % (2/25) chez Mus musculus. Huit génotypes d'E. bieneusi ont été identifiés, dont quatre génotypes connus (D (n = 8), EbpC (n = 8), PigEBITS7 (n = 9) et EbpA (n = 2)) et quatre génotypes nouveaux (CHPR1 (n = 7), CHPR2 (n = 1), CHPR3 (n = 2) et CHPR4 (n = 2)). Cette étude est la première à signaler la présence d'E. bieneusi chez des rongeurs provenant d'élevages porcins des provinces du Henan, du Shaanxi et du Shanxi en Chine. La gamme d'hôtes du génotype EbpC a été élargie avec sa première détection chez M. musculus et R. tanezumi. Tous les génotypes d'E. bieneusi identifiés appartiennent au groupe 1, ce qui soulève des inquiétudes quant au fait que ces rongeurs sympatriques soient des réservoirs de transmission zoonotique. De plus, la large distribution du génotype EbpC suggère une transmission interspécifique potentielle entre les rongeurs sympatriques et les porcs domestiques. Nos résultats soulignent le rôle potentiel des rongeurs sympatriques dans la facilitation de la propagation d'E. bieneusi à partir des élevages porcins, ce qui pourrait constituer une menace potentielle pour la santé publique.

A two-stage subsynchronous oscillation assessment method for DFIG-based wind farm grid-connected system.

In the power system, the wind farm based on Doubly-Fed Induction Generator (DFIG) may lead to Subsynchronous Oscillation (SSO), which poses a challenge to the stability of the power grid. In order to accurately evaluate SSO, this paper proposes a new evaluation method. It is divided into two main stages: firstly, the interference level of Phasor Measurement Unit (PMU) data is identified by using the classification model based on Upper Confidence Bound (UCB) and Double Deep Q Network (DDQN). Then, an SSO parameter estimation model based on Local Feature Fusion Transformer (LFF-Transformer) network is designed for data with different interference levels. Experimental results show that the errors of eRMSE-f and EMAPE-F are 0.001 and 0.003 respectively, and the errors of eRMSE-δ and EMAPE-δ are 0.009 and 0.015 respectively. In terms of training and testing time, this method is 90 s and 18 s respectively, which is significantly better than Multi-SVR and Multi-CNN. After application, the frequency deviation decreased from 0.05 to 0.02 Hz, the voltage deviation decreased from 3.5 to 1.5%, the power fluctuation decreased from 10 to 5 MW, the SSO frequency decreased from 1.5 Hz to less than 0.5 Hz, and the SSO damping ratio increased from 0.08 to 0.15. This shows that the proposed method effectively increases the stability of the power grid.

Influence of rainfall on size-resolved bioaerosols around a livestock farm.

Bioaerosols, capable of transporting microorganisms, can impact human health and agriculture by spreading to nearby communities. Their transmissions are influenced by various factors, including weather conditions and human activities. However, the scarcity of detailed, taxon-specific data on bioaerosols' sizes limits our ability to assess risks associated with bioaerosols' generation and spread. This study examined the composition and size of bioaerosols at a livestock farm and a non-agricultural site, focusing on how bioaerosols evolve at different locations and meteorological conditions. The location had an impact on bioaerosol samples. We conducted 16S rRNA gene amplicon sequencing to identify bacteria genera in bioaerosols. We observed consistently higher concentrations of bioaerosols across all sizes at the livestock farm, and samples from the livestock farm exhibited greater bacterial diversity, where we identified Staphylococcus and Corynebacterium as the most abundant species. The effects of rainfall on bioaerosol diversity are complex, suggesting a dynamic interplay between bioaerosol removal and generation. After rainfall, the bioaerosol fraction of particles larger than 2.5 µm increased by nearly 400% compared to post-rain levels. Conversely, for bioaerosols below 1 µm size, the fraction decreased by 50%. Furthermore, the sequencing results showed that precipitation differentially responded to the abundance of various genera in the bioaerosols. Moreover, even for the same genus, the response to precipitation varied depending on the size of the bioaerosols. Our research reveals how size, location, and environmental conditions influence bioaerosol dynamics, enhancing our understanding of bioaerosol formation and transmission.

A comprehensive review of antibiotic resistance gene contamination in agriculture: Challenges and AI-driven solutions.

Since their discovery, the prolonged and widespread use of antibiotics in veterinary and agricultural production has led to numerous problems, particularly the emergence and spread of antibiotic-resistant bacteria (ARB). In addition, other anthropogenic factors accelerate the horizontal transfer of antibiotic resistance genes (ARGs) and amplify their impact. In agricultural environments, animals, manure, and wastewater are the vectors of ARGs that facilitate their spread to the environment and humans via animal products, water, and other environmental pathways. Therefore, this review comprehensively analyzed the current status, removal methods, and future directions of ARGs on farms. This article 1) investigates the origins of ARGs on farms, the pathways and mechanisms of their spread to surrounding environments, and various strategies to mitigate their spread; 2) determines the multiple factors influencing the abundance of ARGs on farms, the pathways through which ARGs spread from farms to the environment, and the effects and mechanisms of non-antibiotic factors on the spread of ARGs; 3) explores methods for controlling ARGs in farm wastes; and 4) provides a comprehensive summary and integration of research across various fields, proposing that in modern smart farms, emerging technologies can be integrated through artificial intelligence to control or even eliminate ARGs. Moreover, challenges and future research directions for controlling ARGs on farms are suggested.

Mother-Daughter Vessel Operation and Maintenance Routing Optimization for Offshore Wind Farms Using Restructuring Particle Swarm Optimization.

As the capacity of individual offshore wind turbines increases, prolonged downtime (due to maintenance or faults) will result in significant economic losses. This necessitates enhancing the efficiency of vessel operation and maintenance (O&M) to reduce O&M costs. Existing research mostly focuses on planning O&M schemes for individual vessels. However, there exists a research gap in the scientific scheduling for state-of-the-art O&M vessels. To bridge this gap, this paper considers the use of an advanced O&M vessel in the O&M process, taking into account the downtime costs associated with wind turbine maintenance and repair incidents. A mathematical model is constructed with the objective of minimizing overall O&M expenditure. Building upon this formulation, this paper introduces a novel restructuring particle swarm optimization which is tailed with a bespoke encoding and decoding strategy, designed to yield an optimized solution that aligns with the intricate demands of the problem at hand. The simulation results indicate that the proposed method can achieve significant savings of 28.85% in O&M costs. The outcomes demonstrate the algorithm's proficiency in tackling the model efficiently and effectively.

Treatment of water extract of green tea during kale cultivation using a home vertical farming appliance conveyed catechins into kale and elevated glucosinolate contents.

The growing interest in healthy diets has driven the demand for food ingredients with enhanced health benefits. In this study, we aimed to explore a method to enhance the bioactivity of kale using a home vertical farming appliance. Specifically, we investigated the effects of treating kale with a green tea water extract (GTE; 0.1-0.5 g/L in nutrient solution) for two weeks before harvest during five weeks of kale cultivation. GTE treatment did not negatively affect the key quality attributes, such as yield, semblance, or sensory properties. However, it led to the accumulation of bioactive compounds, epicatechin (EC) and epigallocatechin gallate (EGCG), which are typically absent in kale. In the control group, no catechins were detected, whereas in the GTE-treated group, the concentration of EC and EGCG were as high as 252.11 and 173.26 µg/g, respectively. These findings indicate the successful incorporation of catechins, known for their unique health-promoting properties, into kale. Additionally, GTE treatment enhanced the biosynthesis of glucosinolates, which are key secondary metabolites of kale. The total glucosinolate content increased from 9.56 µmol/g in the control group to 16.81 µmol/g in the GTE-treated group (treated with 0.5 g/L GTE). These findings showed that GTE treatment not only enriched kale with catechins, the primary bioactive compounds in green tea but also increased the levels of glucosinolates. This study, conducted using a home vertical farming appliance, suggests that bioactivity-enhanced kale can be grown domestically, providing consumers with a nutrient-fortified food source.

A Scoping Review on the Impact of COVID 19 on Vulnerable Populations: LGBTQ+ Persons, Persons Experiencing Homelessness, and Migrant Farm Workers in the US.

Purpose: The goal of the National Center for Medical Education Development and Research Center (NCMEDR) is to support the education and training of medical students in the care of vulnerable populations. Access to primary care services in the US is fundamental to the health and wellness of all people regardless of their socioeconomic status. LGBQ+ persons, (lesbian, gay, bisexual, transgender, queer, and other sexual and gender minority), Persons Experiencing Homelessness (PEH), and Migrant Farm Workers (MFW) are among the most underserved, marginalized, and socially vulnerable groups in the US. NCMEDR in the Department of Family and Community Medicine at Meharry Medical College was established in part, with funding from the Department of Health and Human Services (DHHS) and the Health Resources and Services Administration (HRSA). NCMEDR was developed to provide educational pathways for transforming medical education and clinical practice in the US by ascertaining whether medical students were being trained to provide primary care, and behavioral health services to LGBTQ+ persons, PEH, and MFW. Here we focus on the impact of the COVID-19 pandemic on these specific populations because they represent marginalized groups that have been heavily impacted by the pandemic, have poor social determinants of health (SDOH), and are more likely to be uninsured, and are less likely to engage primary care providers outside of emergency room care. Methods: In this study, a scoping literature review was conducted to assess the impact of COVID-19 on primary care of LQBTQ+ persons, PEH, and MFW. Results and Discussion: The pandemic provided a serious health disparities gap for the defined vulnerable populations under review by the NCMEDR. The pandemic identified the need for transformative measures for clinical practices, medical education, and health care policies required for implementation to improve health care for vulnerable groups. We make recommendations for interventions with defined populations that may influence clinical, environmental health, and SDOH in the COVID era. Conclusions: The COVID pandemic directed the need for medical schools, health care and social organizations to intervene in new and different ways in vulnerable and marginalized communities. The recommendations provide a model for advancing health equity, access, quality, utilization, care coordination, and treatment.

Research Note: Effects of on-farm and hatchery hatching on broiler performance, intestinal lesions, and immune response during a subclinical necrotic enteritis challenge.

The effects of traditional and on-farm hatching systems on broiler performance and health under a subclinical necrotic enteritis (NE) challenge were evaluated in this study. A 2×2 factorial study explored the effects of place of hatch (on-farm hatched [OFH] vs. hatchery hatched [HH]) and NE challenge (nonchallenged vs. challenged) on broilers. Cobb 500 eggs (∼E19) were acquired from a commercial hatchery; 840 eggs were placed in pens on clean shavings in prewarmed floor pens and allowed to hatch out, while 927 eggs were placed in a hatcher set under standard practices. On day (d) of hatch, all chicks were weighed and randomly distributed to 4 treatments (8 replicate pens each and 30 birds/pen). The OFH birds were placed immediately after sorting while HH birds were placed back in the hatcher overnight to simulate commercial hatchery procedures. After placing HH birds, feed and litter in the challenge group pens were sprayed with a live oocyst coccidia vaccine as a predisposing factor to NE. The small intestines of 3 male chicks per pen were scored for NE lesions (n = 24) on d 8 (peak NE challenge) and jejunal samples were collected from 1 bird per pen for RNA extraction and qPCR on d 8 and d 14. Data were analyzed using JMP Pro17 and significance between treatments was identified by LSD (P ≤ 0.05). Regardless of the hatching system, the subclinical NE challenge caused a significant reduction in average daily gain (ADG) and average daily feed intake (ADFI), and increased feed conversion ratio (FCR) until d 28 (P ≤ 0.05). Moreover, OFH birds exhibited significantly better growth (P ≤ 0.05) through d 28 but had similar performance to HH birds by d 42. There were no significant differences in NE lesion scores between HH and OFH groups. In conclusion, OFH system resulted in better broiler performance compared to HH system under both no-challenge and challenge conditions during the starter and grower periods. This practice may hold potential for further exploration by the industry as an alternative to traditional hatching, aiming to improve the welfare and productivity of broilers.

Smart aquaculture analytics: Enhancing shrimp farming in Bangladesh through real-time IoT monitoring and predictive machine learning analysis.

Water quality is a critical factor in shrimp farming, and the success of shrimp production is closely tied to the overall condition of the water. Challenges such as rapid population growth, environmental pollution, and global warming have led to a decline in fisheries production, particularly in the freshwater shrimp sector. This study addresses these challenges by monitoring multiple water parameters in shrimp farms, including pH, temperature, TDS, EC, and salinity. Traditional manual monitoring systems are known to be cumbersome, time-consuming, and lacking real-time capabilities. Consequently, a continuous and automated monitoring system becomes imperative for efficient and real-time metrics handling. This study introduces a real-time freshwater shrimp (locally named Galda, i.e., Macrobrachium Rosenbergii) farm monitoring system. The proposed system incorporates technologies such as microcontroller-based physical devices, IoT, cloud storage with service, machine learning models, and web applications. This integrated system enables users to remotely monitor shrimp farms and receive alerts when water parameters fall outside the optimal range. The physical implementation involves a set of sensors for collecting data on water metrics in shrimp farms. Regression analysis is employed for predicting next-day values, and a newly developed decision-based algorithm classifies shrimp production levels into low, medium, and maximum categories using six well-known classification algorithms. The system demonstrates a high success rate for next-day predictions (r2 of 0.94) by multiple linear regression, and the accuracy in classifying shrimp production is 97.84 % by Random Forest. Additionally, a 'Smart Aquaculture Analytics' web application has been developed, offering features such as real-time dashboards, historical data visualization, prediction and classification tools, and automated notifications to farmers in Bangladesh.

Influence of increasing noise at the offshore wind farm area on fish vocalization phenology: A long-term marine acoustical monitoring off the foremost offshore wind farm in Taiwan.

The rapid increase of offshore projects at Taiwan Strait in recent decade has been debated for elevated noise levels. However, there are no studies on long-term assessment of noise levels and impact of noise on marine organisms. The passive acoustic monitoring was conducted at the foremost wind farm area in Taiwan to assess the sound levels and the impact of noise on fish vocalization behavior. Predominately, in the soundscape around the Taiwan Strait, two chorusing types (Type 1 and Type 2) from the Sciaenid family of fishes exist. Ambient sound levels significantly increased from 2014 to 2019, while the chorusing Types 1 and 2 were observed in a lower percentage of the recordings. Additionally, chorusing peak intensity and duration significantly reduced over the years for both choruses. This is the first field-based evidence to demonstrate the consequences of increasing anthropogenic noise having the potential to alter the vocalization behavior of the fish.

Aesthetic grading causes food losses without financially benefiting farmers: Micro-level evidence from China's fresh apple supply chain.

International literature is lacking quantified information about the impact of raising demands for attractive appearances and the private standards on food loss and associated effects on the economy, the environment and social issues. Given the global scale and significance to food consumption and health, fresh apples were selected for researching the issues. By focusing on China, the major production region of fresh apple in the world where the effects of aesthetic preference and shape abnormality are substantial, the present study aims to gain insights into the on-farm grading processes and different marketing channels for fresh apples in China. It was discovered that 35% of the volume in China's major production areas of fresh apples were graded by aesthetic characteristics such as ripeness, colour, fragrance, bruising, intactness and appealing appearance. About 17.1% of production on average were considered as food losses mainly caused by such grading schemes. Favouring 'perfect' appearance; however, the grading did not yield economic benefits for smallholders. Lastly, direct procurement by supermarkets had a depressive effect on the price of fresh apples at the farm gate. The study has a unique value for global debates and actions against food loss and waste as it quantifies on-farm post-harvest losses of fresh apples by different agri-food chain organizations in China with respect to mass and economic value.

Comparative Analysis of Animal Welfare in Three Broiler Slaughterhouses and Associated Farms with Unsatisfactory Slaughterhouse Results.

The objective of this study was to assess the health and welfare of 70 commercial broiler flocks (transport batches) in three distinct slaughterhouses based on various indicators including emaciation, dirty feathers (DFs), footpad dermatitis (FPD), hock burn (HB), breast burn (BB), breast blister, breast ulcer, ascites, septicemia/abnormal color, cellulitis, extensive traumatisms, dead on arrival (DoA) and condemnation rate. Assessment scales ranging from 0 (absence) to 2 (severe) were used for DFs, FPD, and HB, while a 0 (absence) to 1 (present) scale was applied to BB, breast blisters, and breast ulcers. The prevalence of total condemnation causes (emaciation, ascites, septicemia/abnormal color, cellulitis, and extensive traumatism) and DoA were recorded and presented in percentages. Three flocks presented condemnation rates higher than 4% and 11 flocks presented DoA rates higher than 0.5%. Twenty-one flocks achieved grade 1 (warning) for FPD and 14 achieved grade 2 for FPD (alarm). Extensive trauma was observed in 0.01% of the slaughtered animals, and no flock reached the threshold of 2%. Breast blisters and breast ulcers lesions were not observed in the studied flocks. The significant positive associations observed for the presence of severe footpad dermatitis (FPD2), severe hock burns (HB2), and breast burns (BB1) indicate simultaneous occurrences. Absences of hock burns (HB0) and breast burns (BB0) were also associated. Eleven houses that obtained the worst results for welfare indicators at slaughterhouses were audited. FPD, HB, DoA, and the condemnation rate were the most crucial indicators for identifying farms with inadequate welfare conditions. These indicators should be systematically integrated into the welfare monitoring of broilers in slaughterhouses. Audits conducted on farms detected some noncompliance with regulatory welfare standards and suggested improvements in environmental and structural conditions, as well as the reduction in stocking densities and improvements in the water systems.

Environmental factors and management practices associated with beef cattle carcass quality in the mid-west of Brazil.

The "Precoce MS" program, established by the Brazilian government in Mato Grosso do Sul in 2017, aims to encourage beef producers to harvest animals at younger ages to enhance carcass quality. About 40% of the beef produced in the state now comes from this program, which offers tax refunds ranging from 49% to 67% based on carcass classification and production system. Despite the program success, with participants delivering younger animals (with a maximum of 4 incisors), there remains significant variability in carcass quality. This paper investigates management practices and environmental factors affecting farm performance regarding carcass quality. Data from all animals harvested between the beginning of 2017 and the end of 2018 were analyzed, totaling 1,107 million animals from 1,470 farms. Farm performance was assessed based on the percentage of animals achieving grades "AAA" and "AA." Each batch of harvested cattle from each farm was categorized into two groups: high farm performance (HFP, with more than 50% of animals classified as "AAA" or "AA") and low farm performance (LFP, with less than 50% classified as such). A predictive logistic model was developed to forecast farm performance (FP) using 14 continuous and 15 discrete pre-selected variables. The most effective model, obtained through backward stepwise variable selection, had an R 2 of 0.18, accuracy of 71.5%, and AUC of 0.715. Key predictors included animal category, production system type, carcass weight, individual identification, traceability system, presence of a feed plant, location, and the Normalized Difference Vegetation Index (NDVI) from the 12-mo average before harvest. Developing predictive models of carcass quality by integrating data from commercial farms with other sources of information (animal, production system, and environment) can improve our understanding of production systems, optimize resource allocation, and advance sustainable animal production. Additionally, they offer valuable insights for designing and implementing better sectorial, social, and environmental policies by public administrations, not only in Brazil but also in other tropical and subtropical regions worldwide.

Risk assessment and origin of metals in chicken meat and its organs from a commercial poultry farm in Akwa Ibom state, Nigeria.

Contamination of chicken with metals is on the increase, despite its known attendant health risks to human consumers. The study aimed to evaluate the concentration of some metals in various organs of chicken, their sources, and the health risks they pose to human consumers. Samples of liver, meat, gizzard, borehole water, soil, diets, and droppings were investigated for the presence of some metals (Cr, Co, Mn, Zn, Al, As, Cd, Ni, and Hg), and their sources using principal component analysis (PCA). In addition, health risk assessment was manually computed using estimated daily intake (EDI), target hazard quotient (THQ), hazard index (HI), and carcinogenic risk (CR) parameters. Cr, Mn, Co, and Zn accumulated more in the liver, while Cd and Ni were only observed in the gizzard. The starter diet recorded higher levels of all the metals compared to the grower and finisher diets except for As. All the metals were detected in the poultry surrounding soil and the drinking water of the birds except for Hg. Furthermore, PCA implicated the soil, water, and diets of the birds as the sources of these metals. The THQ, HI, and CR due to the dietary intake of the gizzard indicate a risk of cancer in children and adults. There is a need to ensure that the identified sources of these metals (soil, water, and diets) are routinely monitored to ensure compliance with safety guidelines.

A review of appropriate mechanisation systems for sustainable traditional grain production by smallholder farmers in sub-Saharan Africa with particular reference to Zimbabwe.

Climate change and variability is affecting the production of maize, a staple food in Zimbabwe, leading to the advocacy for production of traditional grains (sorghum, pearl millet and finger millet) as complementary crops for food and nutrition security; mainly because of their drought tolerance. Adoption of traditional grains as a climate change adaptation strategy is, however, limited by lack of appropriate field mechanisation technologies, inter alia. The specific objective of this review was to examine the field mechanisation technologies being used in different farming systems across the globe for their appropriateness in smallholder traditional grain production systems in developing countries, using Zimbabwe as an example, and focusing on the prevailing technical, socio-economic and environmental factors which influence sustainable adoption. The review was conducted by searching ScienceDirect, Researchgate, JSTOR, Springer, AGORA and Google Scholar databases for mechanisation strategies, policies, machinery and equipment used in cereal production systems across the globe. The review revealed that the mechanisation of traditional grain production operations is lagging behind that of other cereals and that there is need to work on developing appropriate mechanisation systems for smallholder farmers in developing countries. Various farm power options were analysed and the use of two-wheel tractors under service-provision was identified as the most suitable option. Conservation agriculture-based direct seeders and use of mowers or bio-pesticides are the best-suited technologies for crop establishment and weed control, respectively. In terms of harvesting, no available equipment can be recommended for smallholder use as yet. Further research is required to optimize the practical application of mowers and bio-pesticides as well as develop scale-based direct seeders and harvesting equipment. Policy issues were identified and recommendations for improvement made. The findings of the current study can be adapted by other sub-Sahara Africa countries where farming systems, priorities and challenges are similar to that of Zimbabwe.

Spatial patterns of influenza A virus spread across compartments in commercial swine farms in the United States.

AbstractMultiple genetic variants of H1 and H3 influenza A viruses (IAVs) circulate concurrently in US swine farms. Understanding the spatial transmission patterns of IAVs among these farms is crucial for developing effective control strategies and mitigating the emergence of novel IAVs. In this study, we analyzed 1,909 IAV genomic sequences from 785 US swine farms, representing 33 farming systems across 12 states, primarily in the Midwest from 2004 to 2023. Bayesian phylogeographic analyses were performed to identify the dispersal patterns of both H1 and H3 virus genetic lineages and to elucidate their spatial migration patterns within and between different systems. Our results showed that both intra-system and inter-system migrations occurred between the swine farms, with intra-system migrations being more frequent. However, migration rates for H1 and H3 IAVs were similar between intra-system and inter-system migration events. Spatial migration patterns aligned with expected pig movement across different compartments of swine farming systems. Sow-Farms were identified as key sources of viruses, with bi-directional migration observed between these farms and other parts of the system, including Wean-to-Finish and Gilt-Development-Units. High intra-system migration was detected across farms in the same region, while spread to geographically distant intra- and inter- system farms was less frequently. These findings suggest that prioritizing resources towards systems frequently confronting influenza problems and targeting pivotal source farms, such as sow farms, could be an effective strategy for controlling influenza in US commercial swine operations.