Context Dairy farming occurs across a wide range of production systems globally, but all share a common requirement, namely, their development and sustainability depend on meeting fundamental animal wellbeing needs, such as shelter, nutrition, and comfort, within varied social, cultural, economic, and regulatory contexts.Aim A conceptual typology for global dairy farm systems is proposed, designed to enable evaluation across any system from an animal wellbeing perspective.Methods The typology is structured around eight primary system components that influence the adult dairy cows' physiological and psychological wellbeing, including living environment, diet, genetic selection for resilience, contact with people, degree of behavioural autonomy, group size, milking interval and cow-calf interaction. These components are organised into an attribute hierarchy, visually represented in a matrix that progresses from lower to higher levels of human intervention, and a shift in welfare risks from physiological to psychological domains. The typology was applied to representative dairy systems in New Zealand, the United States, Ireland, and China.Key results Despite limitations in cross-jurisdictional data availability, it successfully highlighted key similarities and differences in wellbeing-related system attributes. Further refinement, particularly in measuring components such as the degree of human contact, could enhance its precision and applicability. The framework was also tested against future scenarios, demonstrating its potential to identify farm system attributes that align with varying and changing welfare expectations.Conclusions This exercise supports the broader utility of the typology in system-level assessments, including those not explicitly focused on animal welfare, while ensuring that wellbeing remains a central consideration.Implications Overall, the attribute hierarchy provides a cow-centric and operationally flexible tool for characterising and evaluating global dairy farm systems.
Productivity growth is essential for securing the long-term profitability and competitiveness of pasture-based dairy systems, particularly amid volatile input and output prices and increasing environmental constraints. This paper measures productivity growth using a total factor productivity index (TFPI) tailored to the seasonal, pasture-based nature of New Zealand dairy farming. We apply a proper-index approach to enable meaningful comparisons across time and farms. The TFPI is decomposed into key components: technological progress, scale and input-mix efficiency, technical efficiency, production environment and statistical noise. To account for climate-related variability, we integrate pasture growth indices as proxies for pasture availability supporting milksolids (fat + protein) production. Between 2012/2013 and 2023/2024, productivity growth plateaued, with the TFPI declining by 1.33% (-0.09% per annum). While technological progress increased by 6.9%, this was offset by declines in scale-and-mix efficiency (-4.2%), technical efficiency (-0.63%) and production environment favourability (-1.68%). Moreover, technological progress has stagnated since 2015/2016, suggesting that recent innovations have not translated into measurable productivity gains. These findings underscore the need for a multifaceted response to reverse productivity decline and secure competitiveness: accelerating innovation, strengthening technology adoption and building environmental resilience.
Heat stress (HS) negatively affects the health, reproduction, and milk production of dairy cows, indicating a major challenge to animal welfare and farm profitability. Although environmental and physiological indicators are commonly used to monitor HS, cellular biomarkers such as heat shock protein 70 (HSP70) offer a promising approach for detecting HS at the molecular level. This research aimed to evaluate and compare HSP70 levels in the milk, blood, and saliva of lactating dairy cows across seasons, assess their environmental responsiveness using the temperature-humidity index (THI) as the standard environmental indicator of HS under temperate Australian conditions, and investigate the potential of milk HSP70 as a noninvasive biomarker of HS at the cellular level. Twenty multiparous Holstein Friesian cows were monitored across 4 seasons (summer, autumn, winter, and spring) over 1 yr, and HSP70 concentrations were measured using a competitive ELISA system. Weather data, including THI, as well as milk yield and composition traits, were also recorded. Results showed significant seasonal variation in HSP70 levels, with the highest concentrations observed in summer across all sample types. Blood exhibited the highest (416.45 ng/mL) HSP70 concentrations overall, followed by saliva (304.89 ng/mL) and milk (279.02 ng/mL). Milk HSP70 showed the highest variability (CV = 53.76%), indicating that additional factors beyond HS may influence its expression, whereas blood and saliva appeared to be more consistent. The associations between HSP70 concentrations in biological fluids were initially evaluated using Pearson correlation analysis. To account for repeated measurements in cows and identify key predictors, linear mixed-effects models with cow identification as a random effect were then fitted. Moderate positive correlations were found between the concentration of milk HSP70 and both blood (r = 0.58) and saliva HSP70 (r = 0.53), indicating that milk HSP70 may reflect systemic stress responses in dairy cows. Multivariable linear mixed models identified average THI as a significant predictor of HSP70 concentrations across fluids. In the milk HSP70 model, DIM was also a significant predictor, and milk yield was not. Overall, this study provides preliminary evidence that milk HSP70 may have potential as a noninvasive indicator of HS in dairy cows. These findings also contribute to a better understanding of HS physiology and may inform future approaches for herd-level monitoring and management under climate change.
Virtual fencing (VF) is a livestock management technology that uses global positioning systems-enabled collars and audio or electrical cues to geo-fence and herd animals. Virtual fencing is now in use on farms in several countries; however, there have been limited studies on the use of VF on commercial dairy farms and assessing the implications for how farm systems are managed. The aim of this study was to explore farmer experiences with VF use on pasture-based dairy farms in New Zealand. A qualitative research approach was used, with 60- to 90-min semistructured interviews conducted with 20 New Zealand dairy farmers (participants). Interviews were transcribed and analyzed using inductive open coding through Atlas.ti Web software (version 7.4.0-2024-04-04). Innovation appeal, improved job satisfaction, and reduced labor demands were dominant drivers for adoption. Adaptation of animals and people to the new system occurred within a few days or weeks following implementation of VF; however, more time was required for farm system adaptations, such as laneway modifications, additional water troughs, and removal of some permanent fencing. Post-adoption benefits, as perceived by participants, related to time savings, greater control of grazing and crop management, and herd management improvements. Although it was difficult for participants to place a financial return on their VF investment, almost all expressed an ongoing commitment to using the technology, indicating the presence of strong nonfinancial benefits. Findings from this research highlight the transformational potential of VF in grazed dairy systems, while underscoring the need for user-friendly interfaces, robust support systems, and strategies to support the early learning process and mitigate cognitive load.
Pasture-based dairy systems offer a sustainable and cost-effective approach to milk production, particularly in temperate regions. This review synthesizes current knowledge on the nutritional profile of pastures and the nutritional management of grazing dairy cows, emphasizing the unique challenges and opportunities associated with using nonpasture feeds (i.e., grains, coproducts, or conserved forages: commonly referred to as supplements) to fill pasture deficits or increase milk production. Well-managed fresh pasture is a high-quality feed capable of supporting moderate milk production; it supplies an excellent profile of metabolizable AA and highly and rapidly digestible fiber. Its nutritional profile fluctuates, however, with regrowth stage and season, making precise diet management impractical. Our current understanding suggests that supplementary feeding (1) should first be employed to address deficits in ME during periods of low pasture growth; (2) at >30% of DMI can lead to nutrient imbalances, particularly in MP and AA; and (3) can reduce pasture utilization and farm profitability. There is no evidence to support individualized feeding strategies. Further research is required to understand the situations in which supplementary fat or crude protein and AA will increase milk production and to help better parameterize models for use with pasture-based systems.
