Introduction

In recent years, the dairy industry has witnessed a growing emphasis on biosecurity measures as a means to safeguard animal health, enhance productivity, and mitigate the risks associated with disease outbreaks1,2. The implementation of effective biosecurity protocols has become a critical component in ensuring the sustainability and profitability of dairy farms worldwide3,4. Biosecurity, in the context of animal husbandry, encompasses a range of management practices and preventive measures designed to minimize the introduction and spread of diseases among livestock and therefore reduce the use of drugs as antimicrobials and associated resistances5,6. These measures may include, among others, strict hygiene protocols, controlled access to farms, appropriate vaccination programs, and effective disease surveillance7. Assessing the biosecurity status on dairy farms requires the utilization of various methods and indicators to capture the multifaceted nature of this complex concept3,8. Researchers and industry professionals have developed several approaches to estimate biosecurity levels, each with its strengths and limitations4. One commonly employed method is the use of questionnaires or surveys, which involve collecting data directly from farmers regarding their biosecurity practices9. These questionnaires typically cover a wide range of topics, such as farm management practices, disease prevention measures, biosecurity infrastructure, and employee training. Another approach involves conducting on-farm assessments, where trained evaluators visit dairy farms and directly observe the physical infrastructure, biosecurity protocols, and animal health management practices in place10,11. In addition to surveys and on-farm assessments, some studies utilize quantitative measures, such as disease prevalence or pathogen testing, to estimate the impact of biosecurity practices on animal health outcomes12,13. By analysing disease incidence rates or the presence of specific pathogens, researchers can infer the effectiveness of implemented biosecurity measures in reducing the risk of disease transmission within and between farms14. Irrespective of the assessment method, previous studies mostly considered small numbers of dairy farms which allow only limited realistic and proper insights for drawing practical conclusions (e.g.8,15,16). Furthermore, few studies analyzed the economic impact of applying biosecurity measures (e.g.17) and enhanced animal welfare (e.g.18) in dairy farming.

In 2018, Italy launched a new integrated system called Classyfarm that combines data obtained from field surveys of animal welfare and farm biosecurity, antimicrobial use and resistance considering data from the electronic prescription system for veterinary drugs, herd data (health status, production and feed) as well as slaughterhouse assessments on animal health (e.g. lung scores) and welfare (e.g. tail lesions in pigs) for surveilling the potential risk of livestock farms for public health11,19. Since 2023 the ClassyFarm System is in use for dairy cattle farms. In a previous study, however, Holighaus et al.20 showed that the practicability of the welfare protocol for dairy cows used in the ClassyFarm system for small-scale mountain farms was for some sections (especially biosecurity) limited as topographical and structural constraints hamper farms to fulfill many of the requested criteria. In order to motivate farmers for implementing biosecurity measures and animal welfare criteria in respective farms the present study aims to first investigate the interaction between biosecurity measures and productivity (milk yield, milk quality) and secondly to quantify the economic impact for farms when applying such measures. Hereby, the assessment on biosecurity practices and animal welfare was carried out on 2291 mountain dairy farms to gain realistic and practical insights into the interaction between biosecurity and welfare measures with milk performance (quality and yield) and resulting economic performance.

Results

Descriptive statistics of herd size, biosecurity score, welfare score, production traits and economic indicators for investigated farms are depicted in Table 1. The average number of dairy cows per farm was 14 varying between 7 and 166 animals among investigated farms. According to the welfare protocol for dairy cows used for the ClassyFarm system the average biosecurity score for farms was 19.24 out of 30, while the welfare score averaged 57.73 out of 81 (Table 1). The average milk production was 7269 kg per cow and year with 4.04% fat and 3.38% protein (Table 1). The SCS averaged at 3.61. Finally, the average milk price calculated with respective milk composition (fat, protein, SCC) according to the pricing system of the cooperative Bergmilch South Tyrol was 0.53 eurocent per kg milk (Table 1).

Table 1 Descriptive summary of herd size, biosecurity score, welfare scores, production traits, and economic indicators across 2291 dairy farms.
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Interaction between welfare and biosecurity indices with milking performance and quality

Pearson correlations reported in Table 2 reveal a strong association between fat and protein with both, the animal welfare (0.74 and 0.68, respectively) and the biosecurity score (0.79 and 0.84, respectively). Furthermore, milk price strongly correlated with welfare and biosecurity score of a farm. The latter is explainable by the fact that the main parameter influencing the milk price is fat followed by protein as shown in Table 2. Furthermore, a moderate association was observed for milk production and welfare and biosecurity score (0.56 and 0.37, respectively).

Table 2 Pearson correlations between the average score of total animal welfare score, biosecurity scores, milk price, milk production, SCS, and quality traits across 2291 farms included in the study. (P < 0.05).
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Effect of biosecurity and welfare on farm economy

Tables 3 and 4 depicts Least Square Means of biosecurity and welfare score as well as ECM, related milk price and predicted profitability per cow and year. For both biosecurity and welfare an increase in respective index resulted in an increase of predicted profitability per cow and year. In terms of numbers an increase of one score for biosecurity resulted in an increase in sales of 272.23 € per cow and year (R2 = 0.78) (Fig. 1) and increase of one score for welfare resulted in an increase in sales of 160.29 € per cow and year (R2 = 0.94) (Fig. 2). This information was considered for calculating estimates reported in Table 5 for quantifying the actual increase in farm profitability when improving welfare and biosecurity status. A significant increase in ECM and a significant decrease in SCS was observed with increasing welfare and biosecurity indices resulting in a significant increased milk price in farms corresponding to the highest class of biosecurity and welfare score (Table 5). For instance, farms with a biosecurity index score of 20 to 30 earned, on average, approximately 0.1 euro more per kg sold milk than farms having a biosecurity index below 10 (Table 5). In terms of animal welfare, farms with a higher welfare score (61 to 81 index points) earned 0.17 euro more per kg sold milk than farms having a low welfare score (< 45 index points) (Table 5).

Table 3 Least squares mean (LSM) and confidence limits of the mean (CLM) of the average ECM and SCS and the biosecurity score index, and the profitability per kg/year per cow.
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Table 4 Least squares mean (LSM) and confidence limits of the mean (CLM) of the average ECM and SCS and the total welfare score index, and the profitability per kg/year per cow.
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Figure 1
figure 1

Association between Biosecurity Score and milk sales per cow and year.

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Figure 2
figure 2

Association between Welfare Score and milk sales per cow and year.

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Table 5 Estimate and standard error (SE) of the ECM, SCS, and milk price for the effect of biosecurity, total welfare, and emergency management scores in 2291 dairy farms; SD standard deviation.
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Irrespective of this, our results also evidence a poor to moderate adoption of biosecurity measures in mountain dairy farms as most of investigated farms had no or moderate knowledge about certain biosecurity measures like udder health analysis, control plans for infectious diseases or preventive control of endo and ectoparasites (Table 6). In contrast, adequate animal welfare measures were found in most of the farms in the different sections regarding farm management and staff training (Area A), housing (Area B) and animal-based measures (Area C) (Table 7).

Table 6 Estimate and standard error (SE) of the MP for the effect of biosecurity measures scores with a significant impact on milk production across 2291 dairy farms.
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Table 7 Estimate and standard error (SE) of the MP for the effect of welfare measures scores with a significant impact on milk production across 2291 dairy farms and the economic index.
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Discussion

To the best of the authors’ knowledge, this study represents the first comprehensive investigation into the association between animal welfare, biosecurity (estimated based on the welfare protocol for dairy cows of the ClassyFarm system), milk quality, and milk performance on a large scale, encompassing 2291 dairy farms in mountainous regions. Therefore, observed results offer a detailed and realistic understanding of how biosecurity and welfare measures interact with milk performance (both quality and yield) and subsequently influence economic performance.

Overall, our results reveal a poor to moderate adoption of biosecurity measures (19.24 out of 30, as shown in Table 1) in mountain dairy farms. This deficiency can be partly attributed to structural limitations in farm buildings due to topographic disadvantages in such marginal areas, as highlighted by Holighaus et al.20, and partly to farmers’ lack of awareness, as indicated in our results (see Table 6). This aligns with previous studies by Correia-Gomes et al.21 and Van Steenwinkel et al.22 which reported limited awareness of biosecurity practices and poorer farm infrastructure (such as animal housing) in small-scale farms compared to larger operations. Additionally, farmers often perceive certain biosecurity measures as impractical due to the economic and logistical burdens associated with their implementation in day-to-day operations15,23. Irrespective of this, previous studies such as that by Robertson24 highlight the importance of adopting biosecurity measures to safeguard animal health, which is crucial for reducing the need for antimicrobial substances in the livestock sector. Specifically, the adoption of biosecurity measures and plans is essential for maintaining disease-free farms, regions, and countries, thereby contributing positively to the reduction of antimicrobial resistance in the livestock sector5. Moreover, studies emphasize the importance of appropriate education, as well as farmer’s knowledge and attitudes, in enhancing the adoption of biosecurity measures to minimize disease spread and improve farm productivity14,25,26. In this context, Shortall et al.23 suggest that consulting veterinarians can play a pivotal role in advising farmers on biosecurity practices. Furthermore, the adoption of biosecurity practices has been shown to have a significant impact on the economic outcomes of dairy farms17. Hereby, Osawe et al.17 named good managerial abilities to be crucial for implementing biosecurity measures effectively and thus ensuring good economic viability of the farm. The economic significance of properly adopting biosecurity measures is evident in our results (Tables 3, 5, Fig. 1), providing additional motivation for farmers to improve the current situation. Nevertheless, the peculiarity of small-scale mountain dairy farming needs to be considered by the EU policy to adapt certain biosecurity measures to those specific production conditions as already highlighted in Holighaus et al.20, to ensure the continued existence of those farms. The latter provides several crucial ecosystem services such as the conservation of diverse ecosystems and diverse flora and fauna including rare species that depend on traditional mountain agricultural practices (e.g. transhumance) as well as the maintenance of terraced fields, grazing lands, and mountain meadows help to prevent soil erosion27. Moreover, they will increasingly contribute to global food security as they mostly use human-inedible grassland through ruminant production systems for producing food (e.g.28).

In terms of animal welfare, our results revealed a moderate to good welfare status in the farms assessed (57.73 out of 81, as shown in Table 1). This underscores farmers’ existing awareness of the importance of maintaining high welfare standards for their dairy cows to ensure good herd productivity. Animal welfare, among other factors, is significantly associated with the economic success of a farm as shown in Table 2. Indeed, our results demonstrated an increase in sales with improved animal welfare (Tables 4, 5). This finding aligns with Villettaz Robichaud et al.29, who demonstrated the positive impact of good comfort and welfare on dairy herd productivity. Conversely, Coignard et al.30 found that while higher milk production may occur, it does not necessarily reflect the overall welfare status of a herd, as it can be linked to an increased occurrence of health disorders like metabolic diseases. Therefore, Beck and Gregorini31 emphasized the importance of ensuring livestock well-being by allowing animals to express natural behaviors fully in a domesticated environment, leading to a positive emotional experience and improved welfare and health for dairy cows. Additionally, the smaller scale of mountain dairy farms (Table 1) may positively influence welfare due to potentially better individual animal care and human-animal bonding compared to large dairy enterprises. However, Lindena and Hess32 concluded from their study of 3085 dairy farms in Germany that farm size had only a limited effect on animal welfare, while farmers’ knowledge and skills in farm management played a more significant role. Similarly, Gieseke et al.33 argued that farm size alone cannot serve as an indicator of animal welfare, with housing conditions and management practices having a more substantial impact. Despite encouraging findings regarding animal welfare (Table 1), the prevalent housing system in the mountain area is still tie stalls20,34 for which several studies in the past35 as well as EFSA36 highlighted some deficiencies regarding animal health and welfare, especially when housed on a year-round basis37. Therefore, there remains significant room for improvement in enhancing animal welfare in small-scale mountain dairy farming, especially considering the increasing consumer awareness of animal welfare issues and ethical concerns surrounding animal production. Napolitano et al.38 emphasized the importance of providing consumers with accurate information about animal welfare-friendly production methods through effective labeling and scientifically validated monitoring systems to encourage willingness to pay more for animal-based products. However, farmers face the challenge that higher production costs to ensure better welfare standards are often not offset by higher market prices, as many consumers remain indifferent to animal welfare when purchasing animal-based products39. Nonetheless, maintaining good animal welfare standards is crucial not only for the economic success of farms, as shown in our results (Tables 4, 5, Fig. 2), but also for ensuring social acceptance of livestock production.

Conclusions

The results of the present study provide comprehensive insights into the interaction between animal welfare, biosecurity, milk quality, and milk performance on 2291 dairy farms in mountainous regions. The findings highlight the importance of both biosecurity and animal welfare measures in enhancing productivity and economic performance. Nevertheless, our results reveal a poor to moderate adoption of biosecurity measures in mountain dairy farms, attributed partly to structural limitations of small-scale mountain farms and farmers’ lack of awareness. This aligns with previous research highlighting the need for increased education and support for farmers to effectively implement biosecurity practices. In contrast, the study indicates a moderate to good welfare status in the assessed farms, reflecting farmers’ awareness of the importance of maintaining high welfare standards for dairy cows. Improved animal welfare is shown to have a positive impact on milk sales and productivity, highlighting the economic benefits of prioritizing animal well-being. However, there remains room for improvement, particularly in addressing animal housing deficiencies (e.g. year-round tie stall housing) and general consumer concerns regarding animal welfare in livestock production systems. Overall, the study underscores the need for continued efforts to promote and support the adoption of biosecurity measures while simultaneously enhancing animal welfare standards. However, the peculiarity of mountain livestock farming and its crucial role for the provision of some important ecosystem service needs to be considered by the policymakers when developing regulations regarding biosecurity and animal welfare for ensuring its continued existence. Moving forward, targeted interventions and educational initiatives should be prioritized to empower farmers and promote best practices in biosecurity and animal welfare management. However, the resultant increase in production costs necessitates society's willingness to pay more for animal-based food.

Methods

For the present study, 3469 dairy farms all located in the province of South Tyrol (very northern part of Italy) were visited and assessed in 2022 by specifically trained auditors with the welfare protocol for dairy cows used in the ClassyFarm system. The specific details of the assessment and the protocol as well as farm structure and management are published in Holighaus et al.20. For the assessment only dairy cows were considered. In assessing the biosecurity measures and animal welfare criteria within our study, we adopted a structured approach to quantify their prevalence across different farms. Each question related to biosecurity measures or welfare criteria was assigned a numerical value of 0, 1, or 2, indicating the absence, partial absence, or total presence of the measure or criteria, respectively. By summing the scores assigned to each relevant question, we computed a cumulative score for both biosecurity measures and welfare criteria for each farm included in our study. This method enabled us to quantify the level of biosecurity and welfare and to determine the percentage of farms that exhibited specific measures or criteria. Furthermore, milk samples from farms that permitted us were collected every 5 weeks in the course of the official milk performance control and subsequently analyzed for the classical milk quality traits (milk fat, milk protein) and somatic cell count (SCC) in the laboratories of the South Tyrolean Dairy Association equipped with MilkoScan FT6000 (Foss, Hillerød, Denmark) and Fossomatic FC (Foss, Hillerød, Denmark). Fat-to-protein ratio (FPR) was calculated as FPR = FP/PP. For milk production (MP), fat percentage in milk (FP), protein percentage in milk (PP), FPR, and lactose percentage (LP), values were retained only if they fell within the range of mean ± 3 standard deviations (SD). For SCC, the minimum value was set at 1000 cells/mL, while the maximum value was set at 10,000,000 cells/mL. To achieve a normal distribution, SCC was transformed into somatic cell score (SCS) using the conventional formula proposed by Ref.40. Moreover, the milk pricing system for conventional milk of the cooperative Bergmilch Südtirol was used for formulating the milk price for respective milk quality as most of the South Tyrolean dairy farms are members of this cooperative. The pricing systems considers fat, protein, and somatic cells in milk. The detailed description of the payment system is provided in Supplementary Material 1. Additional payments in the milk pricing system for animal welfare is currently not foreseen in the pricing system. Furthermore, natural changes in the milk price on the market were not considered in the economic evaluation. The final dataset used for the statistical analysis comprised milk and biosecurity data from 2291 dairy farms.

Statistical analysis

The data were analyzed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA), treating each farm as an experimental unit. Normality assumptions were assessed using multiple methods, including the Shapiro–Wilk test, examination of skewness and kurtosis, and visual inspection of normal probability plots. Descriptive statistics, including mean, standard deviation, minimum, maximum, and quartiles, were computed using PROC MEANS efficiently summarizing the dataset’s central tendencies and distribution characteristics. Pearson correlation coefficients were derived via PROC CORR and used to investigate the relationships between Welfare and Biosecurity scores, SCC, Fat, %, Protein, %, Milk production, and Milk Price. Results are presented as the correlation coefficient (Rho). Subsequently, the impact of biosecurity and welfare scores on various economic indicators, such as milk production, and profitability in euros, was examined using PROC REG, enabling the evaluation of linear relationships and the estimation of regression coefficients, standard errors, and P-values. Additionally, the robustness of the results was tested using bootstrapping techniques. Only the biosecurity and welfare indicators having a significant impact on milk production and consequently, economic indices were used for subsequent analysis. An ANOVA test in the GLM procedure of SAS was used to check for comparing biosecurity and animal welfare scores with milk production, milk price, and profitability. Results are presented as least squares mean (LSM) standard error of the mean (SEM). This analysis unveiled significant associations between Biosecurity and Welfare scores and economic performance metrics. Moreover, independent variables related to Biosecurity and Welfare practices were scrutinized using PROC REG, elucidating their impact on economic indicators such as ECM (kg per cow/year), and Milk sales per cow and year (€). These findings underscored the significance of specific practices, including control and prevention of infectious diseases, Submission and examination of pathological/biological material, udder health analyses, preventive control of endo ectoparasites, control and analysis of the used water, number of inspections of the animals, treatment of sick or injured animals, management of feed and daily ration, feed availability, water provision, cleanliness of water points, prevention of hoof disorders, hygiene of milking areas and equipment, management of milking operations and udder hygiene, available space at the feed bunk, functioning and number of water points, facilities for sick animals, temperature, humidity, and ventilation, human avoidance test, body condition score (BCS), cleanliness of the animals, skin alterations, lameness, prevalence of long and deformed claws, evaluation udder health, and number of treatments for clinical mastitis in 1 year.

The equation used in the analysis typically follows the form of a linear regression model:

$$Y=\beta 0+\beta 1X1+\beta 2X2+\cdots +\beta nXn+\varepsilon ,$$

where Y represents the dependent variable. X1, X2,…, Xn represent the independent variables, which are specific measures related to welfare or biosecurity practices. β0, β1, β2,…, βn are the regression coefficients corresponding to each independent variable. ε represents the error term.

A Tukey–Kramer adjustment was used to account for multiple comparisons. The criterion for determination of statistical significance was established at P < 0.05.

Ethics declarations

The experimental and notification procedures were carried out in compliance with Directive 86/609/EEC.