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Communities, scientists, policy-makers and industries are requiring farmers to address environmental and wellbeing challenges in their on-farm management, transitioning away from a productivity dominated focus towards a multi-faceted system focus that includes environmental and social values. This paper analyses how Miraka Ltd., an Aotearoa-New Zealand indigenous owned and operated milk company, has taken on the role of institutional entrepreneur to enable and support change towards a multi-faceted system amongst its supply farmers. Observations and interviews were carried out to: (i) identify farmers' changes in practices, beliefs and values over the last ten years; and (ii) identify how Miraka functions as an indigenous entrepreneur in the agricultural sector. Findings show that interviewees were initially guided by business and family-oriented values, beliefs and practices, but in response to the institutional entrepreneurship by Miraka, approximately half of the interviewees changed these values, beliefs and practices, by internalising people and environmental values. The main strategies employed by Miraka were mobilisation of material resources such as incentives and awards, creation of a rationale addressing environmental and social concerns in the dairy sector, and proactive connection with new actors. The research shows an indigenous owned small-medium enterprise can make changes in values, beliefs and practices amongst its supply farmers, but requires a stronger shared base of values to contribute to a wider economic change. The discussion connects these findings to wider literature on diverse economies and indigenous entrepreneurship to identify to what extent an indigenous small-medium enterprise can contribute to a system change. [ABSTRACT FROM AUTHOR]

Previous research shows that feeding and activity behaviours in combination with machine learning algorithms has the potential to predict the onset of bovine respiratory disease (BRD). This study used 229 novel and previously researched feeding, movement, and social behavioural features with machine learning classification algorithms to predict BRD events in pre-weaned calves. Data for 172 group housed calves were collected using automatic milk feeding machines and ultrawideband location sensors. Health assessments were carried out twice weekly using a modified Wisconsin scoring system and calves were classified as sick if they had a Wisconsin score of five or above and/or a rectal temperature of 39.5 °C or higher. A gradient boosting machine classification algorithm produced moderate to high performance: accuracy (0.773), precision (0.776), sensitivity (0.625), specificity (0.872), and F1-score (0.689). The most important 30 features were 40% feeding, 50% movement, and 10% social behavioural features. Movement behaviours, specifically the distance walked per day, were most important for model prediction, whereas feeding and social features aided in the model's prediction minimally. These results highlighting the predictive potential in this area but the need for further improvement before behavioural changes can be used to reliably predict the onset of BRD in pre-weaned calves. [ABSTRACT FROM AUTHOR]

One of the key ways to improve the sustainability of agricultural systems is through diversification, taking advantage of synergies between farm enterprises. Among diversified systems, multispecies livestock farms with at least two animal enterprises have rarely been studied. We explored 95 organic farms from six countries, accounting for the proportion of animal enterprises, sales management, workforce size, and work organization. The study reveals various types of interactions between animal enterprises. Complementarities were observed between ruminant and monogastric enterprises, particularly fertilizer transfer from monogastric manure to grasslands. Milk production was often associated with on-farm processing and short distribution channels, which enhanced farm viability and reduced its dependency on herd productivity. Eleven out of the 95 farms combined above-average production efficiency, on-farm processing, and the majority of sales in short distribution channels. Their labor productivity converged toward 22 livestock units per annual work unit, regardless of the number of workers. Combining farm structure; livestock production efficiency; social elements, such as the workforce; and sales management led us to distinguish four types of farms: (i) small and very autonomous grassland farms with on-farm processing and short distribution channels; (ii) dairy farms associated with a high-density pig or poultry enterprise, whose feed purchase contributes to high rates of cattle feeding self-sufficiency and stocking rate; (iii) large farms with an extensive, grassland beef enterprise associated with either sheep or monogastrics; and (iv) dairy sheep associated with goat or beef cattle on rangelands, with high added-value products enhancing salaries. This study highlights for the first time the diversity of organic multispecies livestock farms and how consistent patterns of interactions among farm structure, livestock management, sales management, and workforce management shape them. The results are a preliminary basis for designing policy interventions aiming to scale up organic farming and value social assets of diversified and small farms. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus is one of the most prevalent pathogens causing bovine mastitis in the world, in part because of its ease of adaptation to various hosts and the environment. This study aimed to determine the prevalence of S. aureus in Colombian dairy farms and its relationship with the causal network of subclinical mastitis. From thirteen dairy farms enrolled, 1288 quarter milk samples (QMS) and 330 teat samples were taken from cows with positive (70.1%) and negative California Mastitis Test (CMT). In addition, 126 samples from the milking parlor environment and 40 from workers (nasal) were collected. On each dairy farm, a survey was conducted, and the milking process was monitored on the day of sampling. S. aureus was identified in 176 samples, i.e., 138 QMS, 20 from teats, 8 from the milking parlor environment, and 10 from workers' nasal swabs. Isolates identified as S. aureus underwent proteomics (clustering of mass spectrum) and molecular (tuf, coa, spa Ig, clfA, and eno genes) analysis. Regarding proteomics results, isolates were distributed into three clusters, each with members from all sources and all farms. Concerning molecular analysis, the virulence-related genes clfA and eno were identified in 41.3% and 37.8% of S. aureus isolates, respectively. We provide evidence on the circulation of S. aureus strains with limited variability among animals, humans, and the environment. The parameters with the lowest compliance in the farms which may be implicated in the transmission of S. aureus are the lack of handwashing and abnormal milk handling. [ABSTRACT FROM AUTHOR]

The global dairy industry is undergoing a period of expansion and consolidation, alongside heightened critique and competition from non-dairy alternatives. This review identifies four key megatrends within the global dairy sector, focusing in on the socioecological challenges associated with each. The megatrends were identified through a literature review of recent publications within the dairy science and social science fields, as well as a review of grey literature from intergovernmental and institutional reports. Key findings include geographical range shifts in production and consumption of dairy milk from the Global North to the Global South; intensification of production agendas that strive for mechanisation, standardisation, and corporatisation of the sector; increasing awareness of the ecological impacts of intensive dairying; and finally, disruptions to the sector driven by plant-based milks and, potentially, synthetic milks. We identify under-researched socioecological challenges associated with each of these trends. Although dairy milk may be homogenous in its final form, the sector remains heterogenous in its impacts across spaces, places, and scales, as increasingly intensive dairying systems fundamentally reshape human–cattle relations. The combined impacts of these trends bring into question the mythologies of milk and the assumed desirability of ever-expanding dairy industries. Our review finds that the future of dairy is not clear nor uncontroversial and that more attention needs to be directed to maximising and broadening the social benefits of the dairy and dairy alternatives, minimising the human and non-human costs, and limiting contributions to global climate change. [ABSTRACT FROM AUTHOR]

Mastitis is one of the major health problems in dairy herds leading to a reduction in the leading to a reduction in the quality of milk and economic losses. The research aimed to present the system, which uses electronic 3D motion detectors to detect the early symptoms of mastitis. The system would allow more effective prevention of this illness. The experiment was carried out on 118 cows (64 Holstein Friesian and 54 Brown Swiss). The animals were kept in free-stall barn with access to pasture. The occurrence of mastitis cases was noticed in veterinary register. Microbiological culture was taken from milk in order to confirm the development of infection. Data from motion detectors were defined as time spent by animals on feed intake, ruminating, physical activity and rest, and were expanded by adding information about feeding group, breed type and lactation number. During analyses, two approaches were used to process the same dataset: artificial neural networks (ANN) and logistic regression. The obtained ANN and the logistic regression models proved to be satisfactory from the perspective of applied criteria of goodness of fit (area under curve—exceed 0.8). Quality parameters (accuracy, sensitivity and specifity) of logistic regression are relatively high (larger than 0.73), whereas the ranks of significance of the studied variables varied across datasets. These proposed models can be useful for automating the detection of mastitis once integrated into the farm's IT system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

India has the largest dairy industry in the world and accounts for a significant share of the global emission of livestock methane ( CH 4 ), a potent greenhouse gas (GHG). While previous works have examined the large-scale livestock CH 4 emissions in India, bottom-up studies are essential to account for the diverse farm conditions and practices across the subcontinent. We developed a Methane Calculator for Indian livestock sector using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology for estimating methane emissions from enteric fermentation and manure management. Using this calculator, we undertook a study of emissions from four dairy farms in the tropical coastal district of Thiruvananthapuram, Kerala, in June 2019. Livestock population and milk production data were collected from the four farms, to compute a mean CH 4 emission of 0.7183 kg CO 2 equivalents/kg of fat and protein corrected milk (kg CO 2 e/kg FPCM), with a notable farm-to-farm variability (63.3%). Having implemented the latest available guidelines outlined by the IPCC, our results are a valuable new addition to the existing body of knowledge in the measurement of dairy farm GHG emissions. We present this as a pilot study, demonstrating a simple method to perform bottom-up investigations of dairy GHG emissions and further formulate policy interventions and mitigation strategies at the farm level. [ABSTRACT FROM AUTHOR]

Purpose: The main objective of this study was to assess the gastrointestinal parasitism in relation with the worm control practices (WCP) in dairy cattle in areas of major importance for dairy/milk production of Cameroon. Methods: Fresh fecal samples were randomly collected from 402 cattle from August to October 2016 in North West Cameroon, and analyze using the McMaster technique. Data on WCP were collected using a questionnaire. Results: A total of 11 parasites species were identified: Trichostrongylus sp. (5.97%); Oesophagostomum sp. (5.47%); Haemonchus sp. (2.48%); Bonostomum sp. (1.74); Cooperia sp. (1.49%). Toxocara sp (0.24%); Ostertagia sp. (0.50%); Nematodirus sp. (0.74%); Trichuris sp. (0.50%); Moniezia sp. (0.50%); Eimeria sp. (0.50%). The mean individual parasite load for helminthes and protozoa ranged from 100 to 400 eggs per gram of feces (epg) and 333–400 oocysts per gram of feces (opg), respectively. Most farmers (95.12%) used conventional drugs (Albendazole, Doramectin, Fenbendazole, Ivermectin.) to deworm animals as compared with traditional phytotherapy (e.g., Carica papaya leaves) (4.88%). The mean epg/opg in animals treated with conventional drugs was significantly higher (p < 0.05) than in those receiving traditional treatment. Animals treated less than four times a year with conventional drugs had the highest (p < 0.05) mean epg/opg compared with animals treated four to six times a year. Conclusion: This study suggests that treating at least four times a year with conventional drugs, and at least two times a year with traditional approaches could help reducing GIP burden in dairy cattle in North West Cameroon. Since the majority of farmers use conventional drugs, it is imperative for them to appropriately use these conventional drugs for a better control of GIP on their farms. [ABSTRACT FROM AUTHOR]