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Mealworms are one of the most economically important insects in large-scale production for human and animal nutrition. Densoviruses are highly pathogenic for invertebrates and exhibit an extraordinary level of diversity which rivals that of their hosts. Molecular, clinical, histological, and electron microscopic characterization of novel densovirus infections is of utmost economic and ecological importance. Here, we describe an outbreak of densovirus with high mortality in a commercial mealworm (Tenebrio molitor) farm. Clinical signs included inability to prehend food, asymmetric locomotion evolving to nonambulation, dehydration, dark discoloration, and death. Upon gross examination, infected mealworms displayed underdevelopment, dark discoloration, larvae body curvature, and organ/tissue softness. Histologically, there was massive epithelial cell death, and cytomegaly and karyomegaly with intranuclear inclusion (InI) bodies in the epidermis, pharynx, esophagus, rectum, tracheae, and tracheoles. Ultrastructurally, these InIs represented a densovirus replication and assembly complex composed of virus particles ranging from 23.79 to 26.99 nm in diameter, as detected on transmission electron microscopy. Whole-genome sequencing identified a 5579-nucleotide-long densovirus containing 5 open reading frames. A phylogenetic analysis of the mealworm densovirus showed it to be closely related to several bird- and bat-associated densoviruses, sharing 97% to 98% identity. Meanwhile, the nucleotide similarity to a mosquito, cockroach, and cricket densovirus was 55%, 52%, and 41%, respectively. As this is the first described whole-genome characterization of a mealworm densovirus, we propose the name Tenebrio molitor densovirus (TmDNV). In contrast to polytropic densoviruses, this TmDNV is epitheliotropic, primarily affecting cuticle-producing cells.

The livestock industry is undergoing significant transformation with the integration of intelligent technologies aimed at enhancing productivity, welfare, and sustainability. This review explores the latest advancements in intelligent systemization (IS), including real-time monitoring, machine learning (ML), and the Internet of Things (IoT), and their impacts on livestock farming. The aim of this study is to provide a comprehensive overview of how these technologies can address industry challenges by improving animal health, optimizing resource use, and promoting sustainable practices. The methods involve an extensive review of the current literature and case studies on intelligent monitoring, data analytics, automation in feeding and climate control, and renewable energy integration. The results indicate that IS enhances livestock well-being through real-time health monitoring and early disease detection, optimizes feeding efficiency, and reduces operational costs through automation. Furthermore, these technologies contribute to environmental sustainability by minimizing waste and reducing the ecological footprint of livestock farming. This study highlights the transformative potential of intelligent technologies in creating a more efficient, humane, and sustainable livestock industry.

The livestock industry is undergoing significant transformation with the integration of intelligent technologies aimed at enhancing productivity, welfare, and sustainability. This review explores the latest advancements in intelligent systemization (IS), including real-time monitoring, machine learning (ML), and the Internet of Things (IoT), and their impacts on livestock farming. The aim of this study is to provide a comprehensive overview of how these technologies can address industry challenges by improving animal health, optimizing resource use, and promoting sustainable practices. The methods involve an extensive review of the current literature and case studies on intelligent monitoring, data analytics, automation in feeding and climate control, and renewable energy integration. The results indicate that IS enhances livestock well-being through real-time health monitoring and early disease detection, optimizes feeding efficiency, and reduces operational costs through automation. Furthermore, these technologies contribute to environmental sustainability by minimizing waste and reducing the ecological footprint of livestock farming. This study highlights the transformative potential of intelligent technologies in creating a more efficient, humane, and sustainable livestock industry. [ABSTRACT FROM AUTHOR]

BackgroundCalf morbidity and mortality are major constraints in Ethiopian cattle production that severely limit available replacement stock. Calf morbidity and mortality reports in Ethiopia mostly focus on market-oriented dairy production systems. A cross-sectional study was undertaken in central Ethiopia with the objectives of estimating the magnitude of calf morbidity and mortality across three production systems and contributing risk factors.MethodsA cross-sectional study was conducted at pastoral, mixed-crop livestock, and dairy farms in central Ethiopia from February 2019 to June 2019 to collect 1-year retrospective and cross-sectional data on calf morbidity and mortality from smallholder farmers using a structured questionnaire.ResultsA total of 293 smallholder farmers were involved in the study. Among the households interviewed, 83% of respondents encountered feed shortages in the year prior to this study. The overall annual calf morbidity prevalence and mortality rate were 6.49% (95% CI: 4.87-8.44) and 10% (95% CI: 8.28-11.93), respectively. Morbidity was higher in Dalocha and Sululta districts in mixed crop-livestock and peri-urban production systems, respectively. Logistic regression analysis of potential risk factors indicated that calf morbidity was associated with the calf and dam body condition score (BCS). Calves with BCS of 3 (medium) were less likely to be morbid (odds ratio [OR]: 0.20 [95% CI: 0.07-0.56]) than calves with BCS of 1 (emaciated), and calves born from dams with a body condition score of 2 (thin) were also at lower risk (OR: 0.25 [95% CI: 0.07-0.95]) than calves born from emaciated dams. The odds of calf mortality in Awash Fentale district were higher (OR: 6.19 [95% CI: 2.09-18.32]) compared to Sululta district.ConclusionsThe study results revealed that the production system and management affect the magnitude of calf morbidity and mortality. We recommend improving water and feed access and resources for livestock owners to reduce calf morbidity and mortality.

The goals of this study were to evaluate factors affecting recovery and antimicrobial resistance (AMR) in intrauterine E. coli in post-partum dairy cows with and without metritis from commercial California dairy farms. Using a cross-sectional study design, a total of 307 cows were sampled from 25 farms throughout California, from which a total of 162 intrauterine E. coli isolates were recovered. During farm visits, cows within 21 days post-partum were categorized in one of three clinical presentation groups before enrollment: metritis (MET, n = 86), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; cows with purulent discharge (PUS, n = 106), defined as a non-fetid purulent or mucopurulent vaginal discharge; and control cows, (CTL, n = 115) defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge. Cows diagnosed as MET had significantly higher odds for recovery of E. coli compared to cows diagnosed as CTL (OR = 2.16, 95% CI: 1.17-3.96), with no significant difference observed between PUS and CTL, and PUS and MET. An increase in days in milk (DIM) at the time of sampling was significantly associated with a decrease in the odds ratio for E. coli recovery from intrauterine swabs (OR = 0.94, 95% CI: 0.89-0.98). All intrauterine E. coli were resistant to ampicillin (AMP), with an AMR prevalence of 30.2% and 33.9% observed for chlortetracycline and oxytetracycline, respectively. Only 8.6% of isolates were resistant to ceftiofur (CEFT), one of the most common drugs used to treat cows on farms sampled. No significant difference in the prevalence of AMR was observed among clinical groups at the individual cow level. At the farm level, a significantly higher odds for isolating intrauterine E. coli resistant to chlortetracycline (OR: 2.6; 95% CI: 3.7-58.0) or oxytetracycline (OR: 1.9; 95% CI: 1.4-33.8) was observed at farms that used an intrauterine infusion of oxytetracycline as a treatment for metritis when compared to those farms that did not use this practice. Findings from this study indicate the need for further research supporting a broader understanding of farm practices driving AMR in cows with metritis, as well as data to increase the accuracy of breakpoints for AMR classification of intrauterine E. coli from cattle.

Precision livestock farming has become an important research focus with the rising demand of meat production in the swine industry. Currently, the farming practice is widely conducted by the technology of computer vision (CV), which automates monitoring pig activity solely based on video recordings. Automation is fulfilled by deriving imagery features that can guide CV systems to recognize animals' body contours, positions, and behavioral categories. Nevertheless, the performance of the CV systems is sensitive to the quality of imagery features. When the CV system is deployed in a variable environment, its performance may decrease as the features are not generalized enough under different illumination conditions. Moreover, most CV systems are established by supervised learning, in which intensive effort in labeling ground truths for the training process is required. Hence, a semi-supervised pipeline, VTag, is developed in this study. The pipeline focuses on long-term tracking of pig activity without requesting any pre-labeled video but a few human supervisions to build a CV system. The pipeline can be rapidly deployed as only one top-view RGB camera is needed for the tracking task. Additionally, the pipeline was released as a software tool with a friendly graphical interface available to general users. Among the presented datasets, the average tracking error was 17.99 cm. Besides, with the prediction results, the pig moving distance per unit time can be estimated for activity studies. Finally, as the motion is monitored, a heat map showing spatial hot spots visited by the pigs can be useful guidance for farming management. The presented pipeline saves massive laborious work in preparing training dataset. The rapid deployment of the tracking system paves the way for pig behavior monitoring.

Porcine reproductive and respiratory syndrome (PRRS) is an extremely contagious disease that causes great damage to the U.S. pork industry. PRRS is not subject to official control in the U.S., but most producers adopt control strategies, including vaccination. However, the PRRS virus mutates frequently, facilitating its ability to infect even vaccinated animals. In this paper we analyze how increased vaccination on sow farms reduces PRRS losses and when vaccination is profitable. We develop a SIR model to simulate the spread of an outbreak between and within swine farms located in a region of Minnesota. Then, we estimate economic losses due to PRRS and calculate the benefits of vaccination. We find that increased vaccination of sow farms increases the private profitability of vaccination, and also transmits positive externalities to farms that do not vaccinate. Although vaccination reduces industry losses, a low to moderate vaccine efficacy implies that large PRRS losses remain, even on vaccinated farms. Our approach provides useful insight into the dynamics of an endemic animal disease and the benefits of different vaccination regimens.

Large and densely sampled sensor datasets can contain a range of complex stochastic structures that are difficult to accommodate in conventional linear models. This can confound attempts to build a more complete picture of an animal's behavior by aggregating information across multiple asynchronous sensor platforms. The Livestock Informatics Toolkit (LIT) has been developed in R to better facilitate knowledge discovery of complex behavioral patterns across Precision Livestock Farming (PLF) data streams using novel unsupervised machine learning and information theoretic approaches. The utility of this analytical pipeline is demonstrated using data from a 6-month feed trial conducted on a closed herd of 185 mix-parity organic dairy cows. Insights into the tradeoffs between behaviors in time budgets acquired from ear tag accelerometer records were improved by augmenting conventional hierarchical clustering techniques with a novel simulation-based approach designed to mimic the complex error structures of sensor data. These simulations were then repurposed to compress the information in this data stream into robust empirically-determined encodings using a novel pruning algorithm. Nonparametric and semiparametric tests using mutual and pointwise information subsequently revealed complex nonlinear associations between encodings of overall time budgets and the order that cows entered the parlor to be milked.

The mealybug, Planococcus ficus (Signoret), is a primary vineyard pest in California and other grape-growing regions throughout the World. Mating disruption programs are commercially available to manage Pl. ficus, but widespread adoption has been limited, in part, by high costs compared with insecticide programs. To improve mating disruption economic effectiveness, different deployment technologies (passive, aerosol, and microencapsulated formulations) were individually examined. Adult male Pl. ficus captures in pheromone traps and categorical ratings of vine infestation or crop damage suggest that all deployment strategies lowered mealybug densities or damage. Using passive dispensers, deployment rates of 310 and 465 per ha lowered Pl. ficus crop damage similar to 615 per ha, a rate commonly used in commercial operations; reduced rates would lower product and deployment costs. Meso dispensers, containing more a.i., deployed at 35 per ha did not have a treatment impact, but a microencapsulated formulation and aerosol canisters lowered male flight captures and/or crop damage. Male mealybug flight activity was greatest from 0500-1100 hr, which coincided with temperatures >16° and

Coxiella burnetii is a highly transmissible intracellular bacterium with a low infective dose that causes Q fever (coxiellosis), a notifiable zoonotic disease distributed worldwide. Livestock are the main source of C. burnetii transmission to humans, which occurs mostly through the aerogenous route. Although C. burnetii is a major abortifacient in small ruminants, it is less frequently diagnosed in aborting cattle. We report a case of C. burnetii abortion in a lactating Holstein cow from a dairy farm producing and selling artisanal cheese directly to consumers in Uruguay, and review the literature on coxiellosis as a bovine abortifacient in South America and as a milk-borne disease. The aborted cow had severe necrotizing placentitis with abundant intratrophoblastic and intralesional C. burnetii confirmed by immunohistochemistry and PCR. After primo-infection in cattle, C. burnetii remains latent in the lymph nodes and mammary glands, with milk being a significant and persistent excretion route. Viable C. burnetii has been found in unpasteurized milk and cheeses after several months of maturing. The risk of coxiellosis after the consumption of unpasteurized dairy products, including cheese, is not negligible. This report raises awareness on bovine coxiellosis as a potential food safety problem in on-farm raw cheese manufacturing and sales. The scant publications on abortive coxiellosis in cattle in South America suggest that the condition has probably gone underreported in all countries of this subcontinent except for Uruguay. Therefore, we also discuss the diagnostic criteria for laboratory-based confirmation of C. burnetii abortion in ruminants as a guideline for veterinary diagnosticians.

Rearing habitat for juvenile Chinook Salmon (Oncorhynchus tshawytscha) in California, the southernmost portion of their range, has drastically declined throughout the past century. Recently, through cooperative agreements with diverse stakeholders, winter-flooded agricultural rice fields in California's Central Valley have emerged as ecologically functioning floodplain rearing habitat for juvenile Chinook Salmon. From 2013 to 2016, we conducted a series of experiments examining methods to enhance habitat benefits for fall-run Chinook Salmon reared on winter-flooded rice fields in the Yolo Bypass, a modified floodplain managed for flood control, agriculture, and wildlife habitat in the Sacramento River Valley of California. Investigations included studying the effect of 1) post-harvest field substrate; 2) depth refugia; 3) duration of field drainage; and 4) duration of rearing occupancy on in-situ diet, growth and survival of juvenile salmon. Post-harvest substrate treatment had only a small effect on the lower trophic food web and an insignificant effect on growth rates or survival of rearing hatchery-origin, fall-run Chinook Salmon. Similarly, depth refugia, created by trenches dug to various depths, also had an insignificant effect on survival. Rapid field drainage yielded significantly higher survival compared to drainage methods drawn out over longer periods. A mortality of approximately one third was observed in the first week after fish were released in the floodplain. This initial mortality event was followed by high, stable survival rates for the remainder of the 6-week duration of floodplain rearing study. Across years, in-field survival ranged 7.4-61.6% and increased over the course of the experiments. Despite coinciding with the most extreme drought in California's recorded history, which elevated water temperatures and reduced the regional extent of adjacent flooded habitats which concentrated avian predators, the adaptive research framework enabled incremental improvements in design to increase survival. Zooplankton (fish food) in the winter-flooded rice fields were 53-150x more abundant than those sampled concurrently in the adjacent Sacramento River channel. Correspondingly, observed somatic growth rates of juvenile hatchery-sourced fall-run Chinook Salmon stocked in rice fields were two to five times greater than concurrently and previously observed growth rates in the adjacent Sacramento River. The abundance of food resources and exceptionally high growth rates observed during these experiments illustrate the potential benefits of using existing agricultural infrastructure to approximate the floodplain wetland physical conditions and hydrologic patterns (shallow, long-duration inundation of cool floodplain habitats in mid-winter) under which Chinook Salmon evolved and to which they are adapted.

Diversifying agricultural landscapes may mitigate biodiversity declines and improve pest management. Yet landscapes are rarely managed to suppress pests, in part because researchers seldom measure key variables related to pest outbreaks and insecticides that drive management decisions. We used a 13-year government database to analyse landscape effects on European grapevine moth (Lobesia botrana) outbreaks and insecticides across c. 400 Spanish vineyards. At harvest, we found pest outbreaks increased four-fold in simplified, vineyard-dominated landscapes compared to complex landscapes in which vineyards are surrounded by semi-natural habitats. Similarly, insecticide applications doubled in vineyard-dominated landscapes but declined in vineyards surrounded by shrubland. Importantly, pest population stochasticity would have masked these large effects if numbers of study sites and years were reduced to typical levels in landscape pest-control studies. Our results suggest increasing landscape complexity may mitigate pest populations and insecticide applications. Habitat conservation represents an economically and environmentally sound approach for achieving sustainable grape production.

Modern day large-scale, high-density farming environments are inherently susceptible to viral outbreaks, inadvertently creating conditions that favor increased pathogen transmission and potential zoonotic spread. Metagenomic sequencing has proven to be a useful tool for characterizing the microbial burden in both people, livestock, and environmental samples. International efforts have been successful at characterizing pathogens in commercial farming environments, especially swine farms, however it is unclear whether the full extent of microbial agents have been adequately captured or is representative of farms elsewhere. To augment international efforts we performed metagenomic next-generation sequencing on nine swine slurry and three environmental samples from a United States of America (U.S.A.) farm operation, characterized the microbial composition of slurry, and identified novel viruses. We assembled a remarkable total of 1792 viral genomes, of which 554 were novel/divergent. We assembled 1637 Picobirnavirus genome segments, of which 538 are novel. In addition, we discovered 10 new viruses belonging to a novel taxon: porcine Statoviruses; which have only been previously reported in human, macaques, mouse, and cows. We assembled 3 divergent Posaviruses and 3 swine Picornaviruses. In addition to viruses described, we found other eukaryotic genera such as Entamoeba and Blastocystis, and bacterial genera such as Listeria, Treponema, Peptoclostridium and Bordetella in the slurry. Of these, two species Entamoeba histolytica and Listeria monocytogenes known to cause human disease were detected. Further, antimicrobial resistance genes such as tetracycline and MLS (macrolide, lincosamide, streptogramin) were also identified. Metagenomic surveillance in swine fecal slurry has great potential for novel and antimicrobial resistant pathogen detection.

The nutrition transition towards western diets in developing countries occurs at multiple levels, impacting health and society and also the environment. In Mexico, the shift in food consumption and production patterns, particularly in relation to animal source foods (ASF), has changed land use. We studied the consumption and production of ASF and change in agricultural land use in Mexico during the second half of the twentieth century and until 2013; using domestic and international data sources, our findings show an increasing proportion of farmed area devoted to the production of feed crops domestically, and also an increasing demand of farmed feed beyond national borders. We discuss how the intensification of livestock production is associated to major environmental threats and suggest that opportunities are available for sustainable and healthy food options.

Food production including dairy has been associated with environmental impacts and resource use that has been steadily improving when adjusted per unit of product. The objective of this study was to conduct a cradle-to-farm gate environmental impact analysis and resource inventory of the California dairy production system to estimate the change in greenhouse gas emissions and water and land use over the 50-yr period between 1964 and 2014. Using a life cycle assessment according to international standards and the Food and Agriculture Organization of the United Nations guidelines, we analyzed contributions from dairy production in California to global environmental change. Production of 1 kg of energy- and protein-corrected milk (ECM) in California emitted 1.12 to 1.16 kg of CO2 equivalents (CO2e) in 2014 compared with 2.11 kg of CO2e in 1964, a reduction of 45.0 to 46.9% over the last 50 yr, depending on the model used. Greater reductions in enteric methane intensity (i.e., methane production per kilogram of ECM) were observed (reduction of 54.1 to 55.7%) compared with manure GHG (reduction of 8.73 to 11.9%) in 2014 compared with 1964. This was mainly because manure management in the state relies on lagoons for storage, which has a greater methane conversion factor than solid manure storage. Water use intensity was reduced by 88.1 to 89.9%, with water reductions of 88.7 to 90.5% in crop production, 55.3 to 59.2% in housing and milking, and 52.4 to 54% in free water intake. Improved crop genetics and management have contributed to large efficiencies in water utilization. Land requirements for crop production were reduced by 89.4 to 89.7% in 2014 compared with 1964. This was mainly due to dramatic increases in crop yields in the last 50 yr. The increases in milk production per cow through genetic improvements and better nutrition and animal care have contributed to reductions in greenhouse gas emissions and land and water usage when calculated per unit of production (intensity) basis.

Although a number of welfare assessment methods have been developed for poultry, none have been evaluated for use in commercial duck farms. The primary objective of the study was to evaluate the inter-rater reliability and relative accuracy of 4 duck welfare assessment strategies. Over 2 experiments, 12 flocks of commercial meat ducks (5,850 to 6,300 ducks/flock) aged 30 to 34 D were evaluated. During experiment 1, six flocks were evaluated using 2 welfare assessment methods: transect walks (TW) and catch-and-inspect (CAI). During TW, 2 observers walked predetermined transects along the length of the house and recorded the number of ducks per transect that were featherless, were dirty, were lethargic, had bloody feathers, had infected eyes, and/or had plugged nostrils or were found dead. During CAI, a total of 150 ducks per flock were corralled and individually evaluated. The same welfare indicators were assessed using both methods. During experiment 2, six flocks were initially evaluated using CAI, TW, and a distance evaluation (DE; a total of 50 ducks per flock evaluated from a walking distance) and then reassessed within 24 h during the loadout (LO) process. Data were analyzed in SAS (version 9.4) to determine the observer and method effects on the incidence of welfare indicators. Interobserver reliability was high (P > 0.05) across methods for most welfare indicators. The assessment method affected the measured outcome variables in both experiments (P < 0.05). CAI resulted in higher estimated incidences of most welfare indicators than TW (experiment 1 and 2) and LO (experiment 2). DE yielded intermediate results compared with other methods (experiment 2). Results obtained using TW and LO were most similar, the only difference being the number of dead birds observed using each method (P < 0.0001). The average time required for CAI, TW, DE, and LO was 2.40 ± 0.004, 1.12 ± 0.02, 1.54 ± 0.001, 3.56 ± 0.006 h, respectively. Bootstrapping analyses showed that the observed welfare indicator prevalence estimates were affected by the number of transects (TW) and number of birds (CAI) sampled.

Current California agricultural practices strive to comanage food safety and habitat conservation on farmland. However, the ecology of foodborne pathogens in wild bird populations, especially those avian species residing in proximity to fresh produce production fields, is not fully understood. In this repeated cross-sectional study, avifauna within agricultural lands in California were sampled over 1 year. Feces, oral swabs, and foot/feather swabs were cultured for zoonotic Salmonella spp., Escherichia coli O157:H7, and non-O157 Shiga toxin-producing E. coli (STEC) and characterized by serotyping and pulsed-field gel electrophoresis. Of 60 avian species sampled, 8 species (13.3%, bird groups of sparrows, icterids, geese, wrens, and kinglets) were positive for at least one of these foodborne pathogens. At the individual bird level, the detection of foodborne pathogens was infrequent in feces (n = 583; 0.5% Salmonella, 0.34% E. coli O157:H7, and 0.5% non-O157 STEC) and in feet/feathers (n = 401; 0.5% non-O157 STEC), and it was absent from oral swabs (n = 353). Several subtypes of public health importance were identified, including Salmonella enterica serotype Newport, E. coli O157:H7, and STEC serogroups O103 and O26. In late summer and autumn, the same STEC subtype was episodically found in several individuals of the same and different avian species, suggesting a common source of contamination in the environment. Sympatric free-range cattle shared subtypes of STEC O26 and O163 with wild geese. A limited rate of positive detection in wild birds provides insights into broad risk profile for contamination considerations but cannot preclude or predict risk on an individual farm.IMPORTANCE The shedding dynamics of foodborne pathogens by wild birds on farmland are not well characterized. This yearlong study sampled wild birds for foodborne pathogens within agricultural lands in northern California. There was a low prevalence of Salmonella spp., Escherichia coli O157:H7, and non-O157 Shiga-toxin producing E. coli (prevalence, 0.34% to 0.50%) identified in bird populations in this study. However, pathogens of public health importance (such as Salmonella Newport, E. coli O157:H7, and STEC O103 and O26) were identified in fecal samples, and two birds carried STEC on their feet or feathers. Identical pathogen strains were shared episodically among birds and between wild geese and free-range cattle. This result suggests a common source of contamination in the environment and potential transmission between species. These findings can be used to assess the risk posed by bird intrusions in produce fields and enhance policy decisions toward the comanagement of food safety and farmland habitat conservation.

Carbon (C) footprint of dairy production, expressed in kg C dioxide (CO2) equivalents (CO2e) (kg energy-corrected milk (ECM))-1, encompasses emissions from feed production, diet management and total product output. The proportion of pasture on diets may affect all these factors, mainly in subtropical climate zones, where cows may access tropical and temperate pastures during warm and cold seasons, respectively. The aim of the study was to assess the C footprint of a dairy system with annual tropical and temperate pastures in a subtropical region. The system boundary included all processes up to the animal farm gate. Feed requirement during the entire life of each cow was based on data recorded from Holstein × Jersey cow herds producing an average of 7,000 kg ECM lactation-1. The milk production response as consequence of feed strategies (scenarios) was based on results from two experiments (warm and cold seasons) using lactating cows from the same herd. Three scenarios were evaluated: total mixed ration (TMR) ad libitum intake, 75, and 50% of ad libitum TMR intake with access to grazing either a tropical or temperate pasture during lactation periods. Considering IPCC and international literature values to estimate emissions from urine/dung, feed production and electricity, the C footprint was similar between scenarios, averaging 1.06 kg CO2e (kg ECM)-1. Considering factors from studies conducted in subtropical conditions and actual inputs for on-farm feed production, the C footprint decreased 0.04 kg CO2e (kg ECM)-1 in scenarios including pastures compared to ad libitum TMR. Regardless of factors considered, emissions from feed production decreased as the proportion of pasture went up. In conclusion, decreasing TMR intake and including pastures in dairy cow diets in subtropical conditions have the potential to maintain or reduce the C footprint to a small extent.

This study quantified the association of rodent fruit damage and the microbiological quality of irrigation water on the risk of microbiological contamination of strawberries collected from 18 U-pick farms across five different districts in the Guangzhou metropolitan region of southern China. Fifty-four composite strawberries samples, with or without evidence of rodent or avian foraging damage (i.e., bitten), along with 16 irrigation water samples, were collected during the spring of 2014 and winter of 2015 from our cohort of 18 farms. Composite strawberry samples and irrigation water were analyzed for total coliforms, E. coli, Salmonella, E. coli O157, Giardia, and Cryptosporidium. Total coliforms and E. coli were detected in 100% and ~90% of irrigation water samples, respectively. In contrast, Cryptosporidium was detected in only two water samples, while Salmonella, E. coli O157, and Giardia were not detected in any water samples. Strawberries with signs of being bitten by wildlife had significantly higher concentrations of total coliforms and E. coli, compared to strawberries with no physical evidence of rodent damage (p < 0.001). Similarly, Cryptosporidium was detected in 7/18 (39%) of bitten, 4/18 (22%) of edge, and 5/18 (28%) of central strawberry samples, respectively. Concentration of E. coli on strawberries (p < 0.001), air temperature (p = 0.025), and presence of Cryptosporidium in irrigation water (p < 0.001) were all associated with the risk of Cryptosporidium contamination on strawberries. Salmonella and Giardia were detected in

The objective of this cross-sectional study was to determine how management practices on California dairies may be associated with bovine respiratory disease (BRD) in preweaned calves. A convenience sample of 100 dairies throughout California, providing a study population of 4,636 calves, were visited between May 2014 and April 2016. During each farm visit, in-person interviews with the herd manager or calf caretaker were conducted to collect information about herd demographics, maternity pen, colostrum and calf management, herd vaccinations, and dust abatement. A random sample of preweaned calves was identified and evaluated for the presence of BRD using a standardized tool. A survey-adjusted generalized linear mixed model with a logit link function was fitted with calf as the unit of analysis and dairy as the random effect. Mean study herd size (±SE) was 1,718 (±189.9) cows. Survey-adjusted estimates of breed types in the sample were 81.6% (±0.6) Holstein, 13.1% (±0.4) Jersey, and 5.3% (±0.5) crossbred or other purebred breeds, and calf sex proportions were 73.8% (±1.0) female and 26.2% (±1.0) male. Overall survey-adjusted BRD prevalence in the study herds was 6.91% (±0.69). Housing factors positively associated with BRD were metal hutches compared with wood hutches [odds ratio (OR) = 11.19; 95% confidence interval (CI) = 2.80-44.78], calf-to-calf contact in calves >75 d of age (OR = 9.95, 95% CI = 1.50-65.86), feeding Holstein calves 5.68 L of milk or replacer per day to Jersey calves (OR = 0.04; 95% CI = 0.01-0.28) were negatively associated with BRD. Our study identified management practices on California dairies with variability and that may contribute to differences in BRD prevalence, which will be incorporated into a risk-assessment tool to control and prevent BRD in preweaned dairy calves.

Reported estimates of CH4 emissions from ruminants and manure management are up to 2 times higher in atmospheric top-down calculations than in bottom-up (BU) inventories. We explored this discrepancy by estimating CH4 emissions of 2 dairy facilities in California with US Environmental Protection Agency (US EPA) methodology, which is used for BU inventories, and 3 independent measurement techniques: (1) open-path measurements with inverse dispersion modeling (hereafter open-path), (2) vehicle measurements with tracer flux ratio method, and (3) aircraft measurements with the closed-path method. All 3 techniques were used to estimate whole-facility CH4 emissions during 3 to 6 d per farm in the summer of 2016. In addition, open-path was used to estimate whole-facility CH4 emissions over 13 to 14 d per farm in the winter of 2017. Our objectives were to (1) compare whole-facility CH4 measurements utilizing the different measurement techniques, (2) compare whole-facility CH4 measurements to US EPA inventory methodology estimates, and (3) compare CH4 emissions between 2 dairies. Whole-facility CH4 estimates were similar among measurement techniques. No seasonality was detected for CH4 emissions from animal housing, but CH4 emissions from liquid manure storage were 3 to 6 times greater during the summer than during the winter measurement periods. The findings confirm previous studies showing that whole-facility CH4 emissions need to be measured throughout the year to estimate and evaluate annual inventories. Open-path measurements for liquid manure storage emissions were similar to monthly US EPA estimates during the summer, but not during the winter measurement periods. However, the numerical difference was relatively small considering yearly emission estimates. Manure CH4 emissions contributed 69 to 79% and 26 to 47% of whole-facility CH4 emissions during the summer and winter measurement periods, respectively. Methane yields from animal housing were similar between farms (on average 20.9 g of CH4/kg of dry matter intake), but CH4 emissions normalized by volatile solids (VS) loading from liquid manure storage (g of CH4 per day/kg of VS produced by all cattle per day) at 1 dairy were 1.7 and 3.5 times greater than at the other during the summer (234 vs. 137 g of CH4/kg of VS) and winter measurement periods (78 vs. 22 g of CH4/kg of VS), respectively. We attributed much of this difference to the proportion of manure stored in liquid (anaerobic) form, and suggest that manure management practices that reduce the amount of manure solids stored in liquid form could significantly reduce dairy CH4 emissions.

Reducing food production pressures on the environment while feeding an ever-growing human population is one of the grand challenges facing humanity. The magnitude of environmental impacts from food production, largely around land use, has motivated evaluation of the environmental and health benefits of shifting diets, typically away from meat toward other sources, including seafood. However, total global catch of wild seafood has remained relatively unchanged for the last two decades, suggesting increased demand for seafood will mostly have to rely on aquaculture (i.e., aquatic farming). Increasingly, cultivated aquatic species depend on feed inputs from agricultural sources, raising concerns around further straining crops and land use for feed. However, the relative impact and potential of aquaculture remains unclear. Here we simulate how different forms of aquaculture contribute and compare with feed and land use of terrestrial meat production and how spatial patterns might change by midcentury if diets move toward more cultured seafood and less meat. Using country-level aquatic and terrestrial data, we show that aquaculture requires less feed crops and land, even if over one-third of protein production comes from aquaculture by 2050. However, feed and land-sparing benefits are spatially heterogeneous, driven by differing patterns of production, trade, and feed composition. Ultimately, our study highlights the future potential and uncertainties of considering aquaculture in the portfolio of sustainability solutions around one of the largest anthropogenic impacts on the planet.

Reducing food production pressures on the environment while feeding an ever-growing human population is one of the grand challenges facing humanity. The magnitude of environmental impacts from food production, largely around land use, has motivated evaluation of the environmental and health benefits of shifting diets, typically away from meat toward other sources, including seafood. However, total global catch of wild seafood has remained relatively unchanged for the last two decades, suggesting increased demand for seafood will mostly have to rely on aquaculture (i.e., aquatic farming). Increasingly, cultivated aquatic species depend on feed inputs from agricultural sources, raising concerns around further straining crops and land use for feed. However, the relative impact and potential of aquaculture remains unclear. Here we simulate how different forms of aquaculture contribute and compare with feed and land use of terrestrial meat production and how spatial patterns might change by midcentury if diets move toward more cultured seafood and less meat. Using country-level aquatic and terrestrial data, we show that aquaculture requires less feed crops and land, even if over one-third of protein production comes from aquaculture by 2050. However, feed and land-sparing benefits are spatially heterogeneous, driven by differing patterns of production, trade, and feed composition. Ultimately, our study highlights the future potential and uncertainties of considering aquaculture in the portfolio of sustainability solutions around one of the largest anthropogenic impacts on the planet.

Paratuberculosis, also known as Johne's disease (JD), is a chronic contagious disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP). The disease is incurable, fatal and causes economic losses estimated to exceed 200 million dollars to the U.S. dairy industry annually. Several preventive and control measures have been recommended; however, only a few of these measures have been validated empirically. Using a nested compartmental (NC) modeling approach, the main objective of this research was to identify the best combination of control and preventive measures that minimizes the prevalence and incidence of JD and the risk of MAP occurrence in a dairy herd. The NC model employs both MAP transmission estimates and data on pen movement of cattle on a dairy to quantify the effectiveness of control and preventive measures. To obtain reasonable ranges of parameter values for between-pen movements, the NC model was fitted to the movement data of four typical California dairy farms. Using the estimated ranges of the movement parameters and those of JD from previous research, the basic reproduction number was calculated to measure the risk of MAP occurrence in each pen environment as well as the entire dairy. Although the interventions evaluated by the NC model were shown to reduce the infection, no single measure alone was capable of eradicating the infection. The numerical simulations suggest that a combination of test and cull with more frequent manure removal is the most effective method in reducing incidence, prevalence and the risk of MAP occurrence. Other control measures such as limiting calf-adult cow contacts, raising calves in a disease-free herd or colostrum management were less effective.

This study was conducted to investigate first the bacterial contamination by Enterobacteriaceae, fecal coliforms and the prevalence of Salmonella spp. and second to identify the main associated risk factors in Algerian farms, slaughterhouses and butcheries during a two-years period. Thus, a cross-sectional study was performed using a simple random sampling method to target 20 farms, 10 slaughterhouses and 5 butcheries. A structured questionnaire was further used to assess hygienic status of the farms and slaughterhouses. A total of 265 samples were collected from wall, floor, litter, food, water and animals' samples composed mainly of meat, neck skin and liver. Samples from walls and floors, from different sites were analyzed to evaluate the overall contamination and the hygiene of sites for Total viable bacteria, Enterobacteriaceae counts and Fecal coliforms counts. Furthermore, E.coli and salmonella spp. were identified in all samples. The overall contamination by sampling sites expressed as log10 CFU/g (mean ± SD) for Total Aerobic Microbial Count, Enterobacteriaceae count and fecal coliforms counts were around 4.71 ± 1.1, 4.73 ± 1.3 and 4.68 ± 1.2 respectively. The findings evidenced that the prevalence of E.coli and Salmonella spp. were 63.40% and 18.49% respectively. The highest rate of E.coli contamination was for poultry farms (70%), beef farms (64%) and butcheries (74.54%) followed by poultry meat slaughterhouses (60%) and sheep farms (48%) while beef slaughterhouses have the lowest rate of contamination (33.84%). For salmonella spp. the contamination was found to be mainly in poultry meat slaughterhouses (31.11%), butcheries (25.45%), followed by poultry farms (22%), beef farms (20%) and sheep farms (12%) while beef slaughterhouses have the lowest rate of contamination (4.61%). This study evidenced multifactor effects of microbial contamination in farms such as animal density, litter hygiene and scraping, manure storage, water and pest control, contact with other animals and decontamination process. Overall, this trial indicated a high rate of microbial contamination for which further studies are needed to determine all the potential risk factors in order to evaluate the corrective effects.

BackgroundPorcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight.ResultsThe model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124).ConclusionThe result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

Policy makers and farmers need to know the status of farmland biodiversity in order to meet conservation goals and evaluate management options. Based on a review of 11 monitoring programs in Europe and North America and on related literature, we identify the design choices or attributes of a program that balance monitoring costs and usefulness for stakeholders. A useful program monitors habitats, vascular plants, and possibly faunal groups (ecosystem service providers, charismatic species) using a stratified random sample of the agricultural landscape, including marginal and intensive regions. The size of landscape samples varies with the grain of the agricultural landscape; for example, samples are smaller in Europe and larger in North America. Raw data are collected in a rolling survey, which distributes sampling over several years. Sufficient practical experience is now available to implement broad monitoring schemes on both continents. Technological developments in remote sensing, metagenomics, and social media may offer new opportunities for affordable farmland biodiversity monitoring and help to lower the overall costs of monitoring programs.

Background: Since 2011, influenza A viruses circulating in US swine exhibited at county fairs are associated with >460 zoonotic infections, presenting an ongoing pandemic risk. Swine "jackpot shows" that occur before county fairs each summer intermix large numbers of exhibition swine from diverse geographic locations. We investigated the role of jackpot shows in influenza zoonoses.Methods: We collected snout wipe or nasal swab samples from 17 009 pigs attending 350 national, state, and local swine exhibitions across 8 states during 2016-2018.Results: Influenza was detected in 13.9% of swine sampled at jackpot shows, and 76.3% of jackpot shows had at least 1 pig test positive. Jackpot shows had 4.3-fold higher odds of detecting at least 1 influenza-positive pig compared to county fairs. When influenza was detected at a county fair, almost half of pigs tested positive, clarifying why zoonotic infections occur primarily at county fairs.Conclusions: The earlier timing of jackpot shows and long-distance travel for repeated showing of individual pigs provide a pathway for the introduction of influenza into county fairs. Mitigation strategies aimed at curtailing influenza at jackpot shows are likely to have downstream effects on disease transmission at county fairs and zoonoses. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate first the bacterial contamination by Enterobacteriaceae, fecal coliforms and the prevalence of Salmonella spp. and second to identify the main associated risk factors in Algerian farms, slaughterhouses and butcheries during a two-years period. Thus, a cross-sectional study was performed using a simple random sampling method to target 20 farms, 10 slaughterhouses and 5 butcheries. A structured questionnaire was further used to assess hygienic status of the farms and slaughterhouses. A total of 265 samples were collected from wall, floor, litter, food, water and animals' samples composed mainly of meat, neck skin and liver. Samples from walls and floors, from different sites were analyzed to evaluate the overall contamination and the hygiene of sites for Total viable bacteria, Enterobacteriaceae counts and Fecal coliforms counts. Furthermore, E.coli and salmonella spp. were identified in all samples. The overall contamination by sampling sites expressed as log10 CFU/g (mean ± SD) for Total Aerobic Microbial Count, Enterobacteriaceae count and fecal coliforms counts were around 4.71 ± 1.1, 4.73 ± 1.3 and 4.68 ± 1.2 respectively. The findings evidenced that the prevalence of E.coli and Salmonella spp. were 63.40% and 18.49% respectively. The highest rate of E.coli contamination was for poultry farms (70%), beef farms (64%) and butcheries (74.54%) followed by poultry meat slaughterhouses (60%) and sheep farms (48%) while beef slaughterhouses have the lowest rate of contamination (33.84%). For salmonella spp. the contamination was found to be mainly in poultry meat slaughterhouses (31.11%), butcheries (25.45%), followed by poultry farms (22%), beef farms (20%) and sheep farms (12%) while beef slaughterhouses have the lowest rate of contamination (4.61%). This study evidenced multifactor effects of microbial contamination in farms such as animal density, litter hygiene and scraping, manure storage, water and pest control, contact with other animals and decontamination process. Overall, this trial indicated a high rate of microbial contamination for which further studies are needed to determine all the potential risk factors in order to evaluate the corrective effects. [ABSTRACT FROM AUTHOR]

Background: Farming is the most dangerous occupation in high-income countries worldwide. However, there is a lack of descriptive literature in this area. Injuries on farms are increasing, at a time when the cohort of trauma patients generally has become older and more medically complex. Farmers continue to work late in life when other industry workers would be retired. This study describes major trauma occurring on farms in the Republic of Ireland, the demographics of patients and treatments they received.Methods: Data was gathered from the National Office of Clinical Audit Major Trauma Audit (MTA) 2014 to 2016. Patients were included and excluded based on Trauma Audit and Research Network(TARN) inclusion criteria.Results: There were 430 patients included in this study. The median age was 54.5 years (range 1-93). There were 6.3%(n=27) paediatric patients, and 27%(n=116) over 65-year olds. Patients had predominantly low Charlson Comorbidity Index scores (median 0). Patients >65 years had more comorbidities (p<0.001). The median ISS was 9(IQR 9-17). The most common mechanism of injury was blow from animal (n=126,29%) followed by low fall (n=115,27%). Summer was the most common season of injury (n=128,30%) and most patients presented to a hospital between 8am-12am(n=412,96%). There were 11 patients (2.6%) who died after arrival to hospital - most commonly due to head injury (n=5,45%). The median length of stay was six days; older patients stayed longer than younger patients (6 vs 12 days,p<0.001). The most common body area injured was limbs (n=139,32%), followed by chest (n=89,21%), spine (n=67,16%) and head injuries (n=64,15%). There were 84 patients (19.5%) who underwent operative intervention, and 77(18%) required intensive care unit (ICU) admission. Farm trauma patients were more likely to arrive by helicopter than other MTA patients.Conclusions: A substantial proportion of trauma on Irish farms involves older men who have co-morbidities and complexity of medical need. Farm trauma occurs in rural and remote locations with longer journey times to trauma centres and trauma units-this has implications for trauma care education and mode of EMS transport. Older patients who suffer trauma on farms require longer hospital stays and may not return to independent living. [ABSTRACT FROM AUTHOR]

Many animals suffer terribly under intensive farming that existence is simply of no benefit to them. Animals have a moral right not to be raised when their other rights will inevitably be violated. This paper applied the rights theory to the question of farm animals and argues that animals have a moral right not to be killed and not to be made to suffer by agricultural practices, but have no moral right not to be used in farming at all. This paper argues that there is nothing inherently wrong with modifying animals for human ends, however, not all modifications are permissible. For example, modifying animals to be kill and modifying them to suffer is wrong. Those modifications that lead to animals possessing worthwhile lives but with insufficient opportunities for well-being are also impermissible. This paper implies a call to end to intensive farming methods which are not animal friendly, and an end to raising animals for just their meat. [ABSTRACT FROM AUTHOR]

Free‐range poultry farms have a high risk of introduction of avian influenza viruses (AIV), and it is presumed that wild (water) birds are the source of introduction. There is very scarce quantitative data on wild fauna visiting free‐range poultry farms. We quantified visits of wild fauna to a free‐range area of a layer farm, situated in an AIV hot‐spot area, assessed by video‐camera monitoring. A total of 5,016 hr (209 days) of video recordings, covering all 12 months of a year, were analysed. A total of 16 families of wild birds and five families of mammals visited the free‐range area of the layer farm. Wild birds, except for the dabbling ducks, visited the free‐range area almost exclusively in the period between sunrise and the moment the chickens entered the free‐range area. Known carriers of AIV visited the outdoor facility regularly: species of gulls almost daily in the period January–August; dabbling ducks only in the night in the period November–May, with a distinct peak in the period December–February. Only a small fraction of visits of wild fauna had overlap with the presence of chickens at the same time in the free‐range area. No direct contact between chickens and wild birds was observed. It is hypothesized that AIV transmission to poultry on free‐range poultry farms will predominantly take place via indirect contact: taking up AIV by chickens via wild‐bird‐faeces‐contaminated water or soil in the free‐range area. The free‐range poultry farmer has several possibilities to potentially lower the attractiveness of the free‐range area for wild (bird) fauna: daily inspection of the free‐range area and removal of carcasses and eggs; prevention of forming of water pools in the free‐range facility. Furthermore, there are ways to scare‐off wild birds, for example use of laser equipment or trained dogs. [ABSTRACT FROM AUTHOR]