Search Results (59)

The changing climate poses a significant challenge to the dairy industry, particularly in Punjab’s Faisalabad region, a central milk production hub. Rising temperatures and humidity exacerbate heat stress, endangering rural livelihoods. This study quantifies the impacts of these climatic stressors on milk yield, evaluates smallholder farmers’ perceptions of climate risks, and projects future losses to guide adaptive policymaking. By integrating Likert-scale surveys of 450 dairy farmers with advanced panel regression models (including fixed and random effects) and a dynamic panel generalized method of moments (GMM) approach for forecasting, we analyzed eight years of milk production and climate data (2017–2024) under IPCC scenarios (+2 °C, +10% humidity). The results revealed significant declines: a 1 °C temperature increase reduced milk yields by 1.72 L per month (p < 0.01), while a 1% rise in humidity decreased output by 0.59 L per month (p < 0.01). Compounded losses under combined stressors reached 2.25 L per month, with hotter regions (Faisalabad’s semi-arid zone) experiencing the steepest declines. Farmers’ perceptions are closely aligned with empirical trends, identifying heat humidity interactions as the most critical risks. To mitigate these losses, adaptive strategies such as heat-resistant cattle breeds, humidity-responsive cooling systems, and targeted financial support for smallholders are critical. This study connects farmers’ insights with econometric modeling to provide practical strategies to enhance resilience in Punjab’s dairy sector. Full article

Bovine anaplasmosis, caused by Anaplasma marginale, is a major tick-borne disease in tropical and subtropical regions of the world, leading to significant production losses. Prolonged convalescence periods are common and surviving animals often become subclinical carriers. This study aimed to detect and characterise A. marginale in bovines in smallholder dairy farms across diverse climatic zones of Pakistan using molecular methods. In total, 321 blood DNA samples from apparently healthy cattle (n = 174) and buffaloes (n = 147) from six districts in Pakistan were tested for A. marginale using a nested PCR assay, targeting part of the major surface protein B gene (msp1β) as a genetic marker, followed by agarose gel electrophoresis and selective sequencing of amplicons from test-positive samples. Of the 321 DNA samples tested, 135 (42.1%) were test-positive for A. marginale. Prevalence was significantly higher in cattle (64.4%; 112/174) than in buffaloes (15.6%; 23/147), and female bovines (43.5%; 108/248) were more frequently infected than males (37%; 27/73). Phylogenetic analysis of the msp1β sequence data (n = 42) revealed that A. marginale from Pakistan clustered with those from Brazil, Thailand, South Africa, and the USA. This study represents the first comprehensive investigation of A. marginale from bovines from diverse agroecological zones of Pakistan and will further stimulate population genetic studies of A. marginale and investigations into the economic impact of subclinical infections in bovines in smallholder farming systems. Full article

Implementing genomic selection in smallholder dairy systems is challenging due to limited genetic connectedness and diverse management practices. This study aimed to optimize genomic evaluation models for crossbred cattle in South India. Data included 305-day first lactation milk yield (FLMY) records from 17,650 cows (1984–2021), with partial pedigree and genotypes for 1004 bulls and 1568 cows. Non-genetic factors such as geography, season and period of calving, and age at first calving were significant sources of variation. The average milk yield was 2875 ± 123.54 kg. Genetic evaluation models used a female-only reference. Heritability estimates using different approaches were 0.32 ± 0.03 (REML), 0.40 ± 0.03 (ssGREML), and 0.25 ± 0.08 (GREML). Bayesian estimates (Bayes A, B, C, Cπ, and ssBR) ranged from 0.20 ± 0.02 to 0.43 ± 0.04. Genomic-only models showed reduced variance due to the Bulmer effect, as genomic data belonged to recent generations. Breeding value prediction accuracies were 0.60 (PBLUP), 0.45 (GBLUP), and 0.65 (ssGBLUP). Using the LR method, the estimates of bias, dispersion, and ratio of accuracies for ssGBLUP were −39.83, 1.09, and 0.69; for ssBR, they were 71.83, 0.83, and 0.76. ssGBLUP resulted in more accurate and less biased GEBVs than ssBR. We recommend ssGBLUP for genomic evaluation of crossbred cattle for milk production under smallholder systems. Full article

Herd management plays a vital role in boosting the productivity, profitability, and sustainability of dairy cooperatives, particularly in developing countries where smallholder farmers are prevalent and have limited access to modern farming technologies. This research presents a dynamic programming (DP) model aimed at helping dairy cooperatives optimize decisions regarding herd structure, specifically focusing on strategies for culling and replacement to match milk supply with varying market demands. The model considers essential traits of dairy cows, including age, milk production, and reproductive condition, to ascertain the best transitions within the herd over several periods. Findings indicate that implementing the proposed DP model can effectively align milk output with fluctuating demand, decrease the gap between supply and demand, and enhance overall herd productivity. While this study uses Thai dairy cooperatives as a case study, the developed model and its insights are relevant to similar smallholder dairy systems in other developing countries, thereby aiding improved decision-making and promoting sustainable herd management practices worldwide. Full article

This study focused on improving the milk fat percentage for crossbred dairy cows in smallholder systems, using GEBV. The data were collected from 2507 animals between 2016 and 2023 under BAIF’s Enhanced Genetic Gains program in Pune, India. After refining the dataset, 33,845 records from 1896 animals were analyzed. The result showed that 75.54% of farms had either one or two animals. Prior to quality control, the mean milk fat percentage was 3.94%, but it decreased to 3.83% after data pruning, which necessitated removing the outliers. Genetic analysis involved 1478 animals genotyped for 49,911 SNPs after applying a rigorous quality control process, and imputation improved the accuracy of genomic data, boosting allele frequency correlation from 0.594 to 0.882. The study revealed that the additive genetic variance, phenotypic variance, and error variance were calculated as 0.012, 0.118, and 0.106, respectively. The heritability was estimated at 0.10, suggesting cautious use for breeding improvements. The GEBV ranged from 0.096 to 3.10%, which offers breeders a practical tool for selecting high-fat-producing cows. This research provides valuable insights into optimizing milk quality and advancing genetic improvement strategies in smallholder dairy systems. Full article

Inequality, malnutrition, poverty, and environmental degradation are some of the global challenges facing humanity. These are aggravated in the context of climate change (CC), envisioning as a utopia to guarantee food security without risking sustainability. Considering the increase in scientific attention on dairy goat production (DGP), we aimed to carry out an exhaustive analysis regarding the evolution of DGP to determine both its socioeconomic and cultural importance during the period 1970–2022 and its possible scenarios for 2050. Over the last half century (1970–2022), dairy goats (DG; 214.01 million heads) have shown an inventory growth of 182%, and this is estimated to increase by 53.37% over the next 28 years (2023–2050). While DGP increased 196% during 1970–2022, it is projected to increase around 71.29% by 2050. Notably, however, the economic value of DGP almost quadrupled (+375%) during 1991–2022, and the same trend is estimated for 2023–2050. Historically, Asia has excelled in both goat inventory and goat milk production volume. This research highlights the crucial role of both goats and DG in the socioeconomic issues in various regions of the world, as they most often represent the only source of income for millions of smallholder families, particularly in developing countries. In the face of CC challenges, goats in general, and DG in particular, show an exceptional potential to be considered the “animal of the future” due to their refined and sophisticated ethological, adaptive, and physiological plasticity under generally clean, green, and ethical production schemes, mainly in marginal contexts in the arid and semi-arid zones of the world. Full article

This cross-sectional study assessed the prevalence, bacterial distribution, antimicrobial susceptibility, and potential risk factors associated with subclinical mastitis (SCM) in small-holder dairy herds in Gansu Province, Northwest China. Forty small-holder cow farms were randomly selected from eight cities/counties in six districts of Gansu Province, and a total of n = 530 lactating cows were included in this study. SCM prevalence was noted at 38.87% and 9.72% at the cow and quarter levels, respectively, based on the California Mastitis Test (CMT). The prevalence of the recovered bacterial species was noted as follows: S. agalactiae (36.02%), S. aureus (19.43%), coagulase-negative staphylococci (CNS) (16.11%), S. dysgalactiae (12.80%), E. coli (9.00%), and S. uberis (6.64%). All isolated bacteria were 100% multi-drug-resistant (MDR) except S. aureus (87.8% MDR). Antimicrobial susceptibility profiles revealed the increased resistance (>85%) of these pathogens to penicillin, streptomycin, trimethoprim–sulfamethoxazole, vancomycin, and erythromycin. However, these pathogens showed increased susceptibility to ampicillin, amoxicillin–sulbactam, ceftazidime, neomycin, kanamycin, spectinomycin, norfloxacin, ciprofloxacin, and doxycycline. The multivariate regression analysis demonstrated that old age, high parity, late lactation, lesions on teats, previous history of clinical mastitis, higher milk yield, and milking training were found to be potential risk factors (p < 0.001) associated with developing SCM in small-holder dairy cows in Gansu Province, China. These findings highlight the need for routine surveillance, antimicrobial stewardship, and effective preventive strategies to mitigate SCM in small-holder dairy production and their possible impacts, i.e., increased antimicrobial resistance and infection, on public health. Full article

Brucellosis is a zoonosis caused by bacteria of the genus Brucella, which results in economic losses relating to livestock and threatens public health. A cross-sectional study was conducted to determine the molecular prevalence of Brucella species in smallholder dairy cattle in six regions of Tanzania from July 2019 to October 2020. Dairy cattle (n = 2048) were sampled from 1371 farms. DNA extracted from blood and vaginal swabs was tested for Brucella using qPCR targeting the IS711 gene and positives were tested for the alkB marker for B. abortus and BMEI1172 marker for B. melitensis. The molecular prevalence was 3.5% (95% CI: 2.8–4.4) with the highest prevalence 8.1% (95% CI: 4.6–13.0) in Njombe region. B. melitensis was the predominant species detected (66.2%). Further studies are recommended to understand the source of B. melitensis and its implications for veterinary public health. Livestock keepers should be informed of the risks and biosecurity practices to reduce the introduction and control of Brucella. Cattle and small ruminant vaccination programs could be implemented to control brucellosis in high-risk populations in the country. Full article

Poor mastitis control favors intramammary infection (IMI), which always involves CNS. This study aimed to determine the relationships of IL-4, IL-6, and IL-10 in mastitis milk with concurrent infection, bacterial pathogens, SCC, and MDA, an oxidative stress marker. All mastitis quarters from five smallholder dairy farms were sampled aseptically before morning milking and again before afternoon milking for bacteriological identification using MALDI-TOF mass spectrometry. The samples with the concomitant infection between streptococci and CNS and their pairs of another sample from the quarters were selected. In addition, samples were randomly chosen to have a controlled single infection. IL-4, IL-6, and IL-10 were measured with ELISA kits. MDA was measured using HPLC, while SCC was measured using Fossomatic™ FC. The results from a repeated measure analysis showed that IL-4 positively correlated with SCC, while IL-6 showed a negative trend. IL-4 levels were highest in CNS infections and significantly higher than in non-infected or mixed infections (p < 0.05). The IL-6 level of the mixed bacteria was highest and showed a different trend from non-infection, and the quarter was infected with streptococcal bacteria. In conclusion, from a single infection, the streptococci and CNS quarter showed varied immune responses, including trendily higher IL-6 and IL-4. Full article

This study explored smallholder dairy production and cattle welfare in Eastern Uganda using mixed methods evaluation approaches. A focus group of 17 members performed a SWOT analysis of local farms, identifying strengths like available land, forage, and community support but weaknesses including disease, parasites, and lack of technologies. Field assessments of 12 farms using a modified Welfare Quality^® protocol revealed 25% had inadequate body condition; 33% lacked adequate water access; 50% provided comfortable housing; and 42% had animals with health issues. Six recommendations were formulated to address needs via training, veterinary services access, data systems, finance, milk market development, and pasture improvements. Though struggling with resource constraints and animal health, eastern Uganda’s favorable climate and community present opportunities to enhance productivity and welfare with targeted actions like skills development and access to technologies. However, external inputs require alignment with smallholder realities. Findings detail current conditions while highlighting local perspectives to guide appropriate innovations sensitive to economic limitations and values-based motives. Collaborating with producers to incrementally elevate management can improve livelihoods and animal well-being. Full article

The adoption of effective coping strategies is crucial for successful adaptation to the impacts of climate change in the dairy sector. However, little attention has been paid to understanding the perceived constraints and motivations toward such strategies. A survey was conducted among 104 dairy farmers from three semi-arid regions of South India. The aim of the survey was to explore the dairy farmers’ perception of climate risk, how it impacts their dairy farming system, the coping strategies they employ, and the barriers they face when implementing these strategies. The survey also investigated the factors that facilitate the adoption of adaptation measures. The results indicate dairy farmers in the region perceive drought, pests and diseases, and high temperatures as the major risks associated with climate change, which has resulted in decreased dairy income, animal health problems, reduced fertility, and food intake problems for their cattle. In response to climate variability, dairy farmers have adopted various coping strategies. The most important strategies include buying livestock insurance, keeping low debt obligations, and growing drought-tolerant grass varieties. However, most farmers face significant constraints in adopting these and other strategies including a lack of climate forecast data, the high cost of adaptation activities, and weak institutional support. On the other hand, the key enabling factors that support the adoption of these strategies include milk production security, suitable feed growing conditions, and family interest. Most importantly, the study found that certain factors such as age, education, number of earning family members, annual milk production, monthly cattle expenses, and landholdings significantly influenced dairy farmers’ strategies for adapting to climate change. The study recommends that providing timely climate forecasts, implementing improved policies such as vaccination and cattle health services, and establishing strong institutional support systems can help dairy farmers become more resilient to climate change and protect their livelihoods. Full article

Optimising antimicrobial usage (AMU) in livestock is pivotal to counteract the emergence of antimicrobial resistance. We analysed AMU in more than 1000 cattle herds over 11 years (2008–2018) in the Aosta Valley (Italy), a region where 80% of farms house less than 50 cattle. Dairy cows accounted for over 95% of AMU. AMU was estimated using the defined daily dose animal for Italy (DDDAit) per biomass for the whole herd and a treatment incidence 100 (TI₁₀₀) for cows. Average annual herd-level AMU was low, with 3.6 DDDAit/biomass (range: 3.2–4.0) and 1.2 TI₁₀₀ in cows (range: 1.1–1.3). Third and fourth generation cephalosporins, which are critical for human medicine, represented almost 10% of usage, and intramammary antimicrobials accounted for over 60%. We detected significant downward temporal trends in total AMU, as well as a positive relationship with herd size. The magnitude of such effects was small, leaving scant room for further reduction. However, the frequent use of critical antimicrobials and intramammary products should be addressed, following the principles of prudent AMU. Our findings highlight the importance of monitoring AMU even in low-production, smallholding contexts where a low usage is expected, to identify any deficiencies and implement interventions for further AMU optimisation. Full article

A study was designed to identify the genomic regions associated with milk production traits in a dairy cattle population reared by smallholder farmers in the harsh and challenging tropical savanna climate of Bengaluru, India. This study is a first-of-its-kind attempt to identify the selection sweeps for the dairy cattle breeds reared in such an environment. Two hundred forty lactating dairy cows reared by 68 farmers across the rural–urban transiting regions of Bengaluru were selected for this study. A genome-wide association study (GWAS) was performed to identify candidate genes for test-day milk yield, solids-not-fat (SNF), milk lactose, milk density and clinical mastitis. Furthermore, the cross-population extended haplotype homozygosity (XP-EHH) methodology was adopted to scan the dairy cattle breeds (Holstein Friesian, Jersey and Crossbred) in Bengaluru. Two SNPs, rs109340659 and rs41571523, were observed to be significantly associated with test-day milk yield. No significant SNPs were observed for the remaining production traits. The GWAS for milk lactose revealed one SNP (rs41634101) that was very close to the threshold limit, though not significant. The potential candidate genes fibrosin-like 1 (FBRSL) and calcium voltage-gated channel auxiliary subunit gamma 3 (CACN) were identified to be in close proximity to the SNP identified for test-day milk yield. These genes were observed to be associated with milk production traits based on previous reports. Furthermore, the selection signature analysis revealed a number of regions under selection for the breed-group comparisons (Crossbred-HF, Crossbred-J and HF-J). Functional analysis of these annotated genes under selection indicated pathways and mechanisms involving ubiquitination, cell signaling and immune response. These findings point towards the probable selection of dairy cows in Bengaluru for thermotolerance. Full article

A cross-sectional baseline survey was conducted at Kibaha Town Council (KTC), Pwani Region (Tanzania), to assess the awareness and practices of smallholder dairy producers towards antimicrobial use (AMU), a major cause of foodborne antimicrobial resistance (AMR) in livestock production systems. The aim was to improve consumers’ confidence in the consumption of milk and other dairy products. Quantitative data were collected from a total of 30 randomly selected respondents from a sampling frame of households keeping dairy cattle in 3 administrative wards of Tumbi, Picha ya Ndege, and Maili Moja. A structured questionnaire was administered through face-to-face conversations between the interviewer and the interviewees. Six other respondents participated in the Focus Group Discussions (FGDs) for qualitative data collection. The quantitative data were analyzed using the statistical package for social science (SPSS, Version 16) and MS Office Excel 2010 for window packages. There were more male respondents (63.3%) than female respondents, whereas the level of education was primary for 46.7%, secondary for 33.3%, and tertiary level for the remaining 20%. About 76.6% of them were using antimicrobials to treat lactating dairy cows, mainly oxytetracycline (OTC 20%), penicillin, and Peni-Strep. Twice the number of males (53.3%) used antimicrobials compared to females (23.3%). Respondents with tertiary education rarely administered antimicrobials themselves. The common diseases being treated were diarrhea (46.7%), mastitis (43.3%), and respiratory diseases (36.7%). A proportion of milk from sick animals (those treated with antimicrobials) was fed to calves (33.3%), sold to milk collection centers (26.7%) where it goes through normal market channels, 26.7% fed to other animals while little is consumed by the family at home (6.7%). In conclusion, it should be noted that milk producers administer antimicrobials themselves even when the animals are being milked. This situation poses health challenges among milk consumers. We advise dairy producers to avoid unnecessary AMU. Full article

Developing the economic welfare of smallholder dairy farmers is an important strategy for achieving the Sustainable Development Goals (SDGs) in regions such as Pujon District, a major dairy producer in the Malang Regency. Enhancing the economic stability of these farmers contributes to community welfare and promotes aspects of the SDGs such as “Good Health and Well-Being” and “No Poverty”. This study delves into the relationships among five types of capital—human, social, natural, physical, and financial—and their influence on the welfare of dairy farmers in Pujon District. A questionnaire was distributed to 110 respondents in January and February 2022 for the purpose of this research. After the data were collected, Smart-PLS was used to analyze the structural-equation model (SEM). According to the findings, these five types of capital have a significant and positive impact on the welfare of farmers. As a result, these five capitals provide a tangible framework for enhancing and measuring farmer welfare in Pujon District, thus providing a strategic path for optimizing community resources to boost economic welfare and contribute to the Sustainable Development Goals. The study findings provide valuable insights into the strategies that can be adopted to promote sustainable agriculture and enhance the well-being of farmers in Pujon District. Full article