European organic dairy farmers’ preference for animal health management within the farm management system

The expertise and knowledge of veterinary advisors on improving animal health management is key towards a better herd health status. However, veterinary advisors are not always aware of the goals and priorities of dairy farmers. To dairy farmers animal health is only one aspect of farm management and resources may be allocated to other more preferred areas. Veterinary advisors may experience this as non-compliant with their advice. To explore the preferences of European Union (EU) organic dairy farmers for improved animal health management relative to other farm management areas an adaptive conjoint analysis (ACA) was performed. A total of 215 farmers participated originating from organic dairy farms in France (n=70), Germany (n=60), Spain (n=28) and Sweden (n=57). The management areas udder health and claw health represented animal health management whereas barn, calf and pasture management represented potential conflicting management areas. Results indicate that EU organic dairy farmers differ in their preferences for improved animal health management within the farming system. In general, improved calf management was the most preferred area and improved claw health management was found to be least preferred, the remaining areas were of intermediate interest. Cluster analyses on claw health measures and udder health measures resulted in respectively seven and nine distinct preference profiles. The results indicate a high degree of variation in farmers’ preference, which cannot be explained by the typical herd characteristics. With the individual preferences revealed by ACA, a veterinary advisor can now find out whether his intended advice is directed at a favourable or unfavourable management area of the farmer. If the latter is the case the veterinarian should first create awareness of the problem to the farmer. Insights in individual farmers preferences will allow veterinary advisors to better understand why farmers were incompliant with their advice and improve their advice by showing, for example, the potential benefits of their advice.     

Graph-based impact analysis as a framework for incorporating practitioner knowledge in dairy herd health management

Production diseases in dairy cows are multifactorial, which means they emerge from complex interactions between many different farm variables. Variables with a large impact on production diseases can be identified for groups of farms using statistical models, but these methods cannot be used to identify highly influential variables in individual farms. This, however, is necessary for herd health planning, because farm conditions and associated health problems vary largely between farms. The aim of this study was to rank variables according to their anticipated effect on production diseases on the farm level by applying a graph-based impact analysis on 192 European organic dairy farms. Direct impacts between 13 pre-defined variables were estimated for each farm during a round-table discussion attended by practitioners, that is farmer, veterinarian and herd advisor. Indirect impacts were elaborated through graph analysis taking into account impact strengths. Across farms, factors supposedly exerting the most influence on production diseases were ‘feeding’, ‘hygiene’ and ‘treatment’ (direct impacts), as well as ‘knowledge and skills’ and ‘herd health monitoring’ (indirect impacts). Factors strongly influenced by production diseases were ‘milk performance’, ‘financial resources’ and ‘labour capacity’ (directly and indirectly). Ranking of variables on the farm level revealed considerable differences between farms in terms of their most influential and most influenced farm factors. Consequently, very different strategies may be required to reduce production diseases in these farms. The method is based on perceptions and estimations and thus prone to errors. From our point of view, however, this weakness is clearly outweighed by the ability to assess and to analyse farm-specific relationships and thus to complement general knowledge with contextual knowledge. Therefore, we conclude that graph-based impact analysis represents a promising decision support tool for herd health planning. The next steps include testing the method using more specific and problem-oriented variables as well as evaluating its effectiveness.     

Evaluation of the impact of a Herd Health and Production Management programme in organic dairy cattle farms: a process evaluation approach

Animal health planning activities are not always providing a satisfactory positive impact on herd health and welfare. Moreover, evaluating the impact of advisory programmes is complex due to multiple interacting elements that influence its outcome. Therefore, measuring solely health outcomes is not sufficient: the whole process of the implementation and use of such programmes should be evaluated. In order to evaluate the impact of an intervention with a Herd Health and Production Management (HHPM) programme a process evaluation framework was designed and used. The intervention involved 20 organic dairy cattle farmers and their advisors, in both France and Sweden. In both countries 20 organic dairy farms were selected as control herds. The evaluation of the HHPM programme was based on: (a) the compliance to the programme; (b) the programme’s functions influencing herd health management practices and stimulating dialogue between farmers and advisors; (c) its effectiveness in terms of improving herd health compared with control farms. Complete compliance to the programme was fulfilled by 21 out of 40 farmers–advisors. Results from a questionnaire showed that the programme functioned as intended (e.g. by allowing early identification of herd health problems), stimulated change in farmers’ herd health management practices and farmer–advisor dialogue. Even though the majority of the users perceived that the programme contributed to herd health improvements, no significant differences in health outcomes were found when compared with control farms 12 months after the start of the intervention. The programme allowed creating an environment promoting the exchange of information between farmers and advisors, necessary to define pertinent advice in a farm-specific situation. Future research should aim at improving methods for the evaluation of the effect of advisory programmes, by identifying early indicators for effective advice and developing methods to evaluate the quality of advisory situations without interfering with them.     

Reduced Medication in Organic Farming with Emphasis on Organic Dairy Production

Medication is an important focus area in organic animal husbandry. The combination of goals relating to improved animal welfare and reduced use of chemicals in general creates a common wish to reduce medication. Based on data from current Danish research projects in organic dairy farming, one specific organic medication pattern or policy cannot be described. The disease treatment pattern is influenced by many factors, e.g. the interaction with colleagues, veterinarians and agricultural advisors. No significant difference could be found with regard to incidence of mastitis treatments or somatic cell counts in 27 organic and 57 conventional herds. A marked tendency to shorter treatment periods in relation to mastitis treatments was described for organic farms in comparison with conventional farms (1.9 days versus 3.2 days (5 organic and 7 conventional herds)). In a study of development of health advisory service in organic herds, the dialogue between farmer, veterinarian and agricultural cattle advisor changed the treatment pattern markedly during a period of 6 months. Among important future challenges for veterinarians in organic farming is pointed at the constructive, open, and critical interaction with the single organic farmer as well as the organic animal husbandry system in general.     

A decision-tree model to detect post-calving diseases based on rumination,activity, milk yield,BW and voluntary visits to the milking robot

Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows’ routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian’s diagnosis served as a binary reference for the model (healthy–sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.     

The role of the veterinarian in bovine fertility management on modern dairy farms

The decline in dairy herd fertility internationally has highlighted the limited impact of traditional veterinary approaches to herd fertility. The role of the veterinarian in fertility management on dairy farms has evolved from addressing individual clinical conditions to analyzing suboptimal herd metrics. However, this paradigm shift has only successfully occurred in some dairy industries and less so in others. Needs analyses indicate that the critical constraints to change are veterinary practice size, client motivation and data quality and availability. In addition, this review identified the inability of veterinarians to demonstrate and to market the cost-benefit of their fertility management services as important impediments to change. In many cases change is not being managed but is imposed by the growth of paraprofessionals. Some veterinarians still see their role as an animal clinician while others have evolved into leaders of the herd fertility management team. The core role of dairy veterinarians remains individual animal examinations but this must be supplemented with systematic herd fertility investigation and veterinarian-led herd fertility management. This new role encompasses leading the change from clinical calls only to a planned approach to herd fertility, demonstrating the cost-benefits of the program, scheduling fertility management consultations, assisting the farmer in setting specific, measurable, attainable, relevant and time-limited (SMART) goals, drawing up standard operating procedures (SOPs), training and auditing staff in fertility management practices, encouraging a team approach, implementing veterinary fertility management and monitoring performance. Veterinarians who fail to engage in this process of change risk being marginalized by others keen to promote their herd fertility services.     

The impact of work organisation on the work life of people on pasture-based dairy farms

The seasonal workload combined with increased dairy herd sizes and a declining workforce have created social sustainability challenges for pasture-based dairy farms. Effective work organisation can build productive capacity that may have a positive impact on this scenario. Our objective was to develop a framework to characterise and examine the effect of work organisation on the working situations of the people involved in a sample of 55 pasture-based dairy farms in Ireland. We conceptualised that effective work organisation on a dairy farm could be considered as a system that is efficient from a labour input perspective, resulting in a profitable farming system with outcomes of good operator well-being, health and safety, and quality of life. A literature review established efficiency & productivity, flexibility and standardisation as our three characteristics of work organisation. Using data from an existing labour time-use study completed from the 1st February to 30th June 2019, we aimed to test the veracity of these work organisation characteristics in the Irish pasture-based dairy system. Two proxy indicators were selected to represent each of the three work organisation characteristics, and each of the 55 farms were categorised into quartiles based on their ranking for these six indicators (1 = most effective quartile to 4 = least effective quartile). The most and least effective quartiles of farms for work organisation showed similar levels of farm labour input and labour efficiency. Farmers in the most effective work organisation quartile were working 51.2 h/week from February to June compared with 70.0 h/week for farmers in the least effective quartile, which was attributed to later start times, earlier finish times, and more time at non-farm activity. Farms achieving effective work organisation had a labour-efficient system with relatively low farmer working hours. Extension of the work organisation concept to other farms could improve their labour situation and aid in alleviating some of the key quality of life challenges faced by dairy farmers.     

Management factors affecting udder health and effects of a one year extension program in organic dairy herds

The first part of this study was a cross-sectional analysis of the impact of 29 management factors on udder health in organic dairy farms in Switzerland. All 77 farms joined the extension program 'pro-Q'. As a measure of udder health the theoretical bulk milk somatic cell count (TBMSCC) calculated by the monthly cow composite somatic cell count over a time period of 1 year was chosen. The basic udder health of the farms was determined by TBMSCC during the year prior to the start of the project (mean for all farms = 176 460 cells/ml). In the multivariable analysis, the five factors 'swiss brown breed', 'alpine summer pasturing', 'calf feeding with milk from mastitis diseased cows', 'hard bedding' and 'no post-milking' remained as significant risk factors on udder health. In the second part of the study, the development of management factors and the udder health situation affected by an extension program after 1 year was investigated. A partial improvement of the management factors on the farms but no overall improvement on udder health and no association between management changes and udder health changes were found. Improvement of udder health was more likely in farms with higher basic TBMSCC than in those farms with less udder health problems at the beginning of the project.     

Risk factors for <Emphasis Type="Italic">Coxiella burnetii</Emphasis> antibodies in bulk tank milk from Danish dairy herds

The aim was to identify risk factors associated with Coxiella burnetii antibody positivity in bulk tank milk (BTM) samples from 100 randomly selected Danish dairy cattle herds. Antibody levels were measured by an enzyme-linked immuno-sorbent assay. Before testing the herds, the farm managers were interviewed about hired labour, biosecurity, housing and herd health during the 12 months prior to the study. Variables considered important for C. burnetii antibody positivity in multivariable logistic regression analysis included the sharing of machines between farms (OR?=?3.6), human contacts (OR?=?4.2), artificial insemination by other people than artificial insemination technicians (OR?=?7.7), routine herd health contract with the veterinarian (OR?=?4.3) and hygiene precautions taken by veterinarians (OR?=?5). In addition, herd size, hired labour, trading of cattle between farms, quarantine and use of calving and disease pens also showed significant association in univariable analysis. This study demonstrates that strict biosecurity is important for the prevention of infections with C. burnetii.     

Contributions to variability of clinical measures for use as indicators of udder health status in a clinical protocol

A cross-sectional observational study with repeated observations was conducted on 16 Danish dairy farms to quantify the influence of observer, parity, time (stage in lactation) and farm on variables routinely selected for inclusion in clinical protocols, thereby to enable a more valid comparison of udder health between different herds. During 12 months, participating herds were visited 5 times by project technicians, who examined 20 cows and scored the selected clinical variables. The estimates of effect on variables were derived from a random regression model procedure. Statistical analyses revealed that, although estimates for occurrence of several the variables, e.g. degree of oedema, varied significantly between observers, the effects on many of these estimates were similar in size. Almost all estimates for occurrences of variables were significantly affected either parity and lactation stage, or by both e.g. udder tissue consistency. Some variables, e.g. mange, had high estimates for the farm component, and others e.g. teat skin quality had a high individual component. Several of the variables, e.g. wounds on warts, had a high residual component indicating that a there still was a major part of the variation in data, which was unexplained. It was concluded that most of the variables were relevant for implementation in herd health management, but that adjustments need to be made to improve reliability.     

Mastitis and related management factors in certified organic dairy herds in Sweden

Background  

Mastitis is one of the major threats to animal health, in organic farming as well as conventional. Preliminary studies of organic dairy herds have indicated better udder health in such herds, as compared to conventional herds. The aim of this paper was to further study mastitis and management related factors in certified organic dairy herds.     

快速准确监测奶牛体细胞数的方法

实验通过荧光染色的方法,运用荧光显微术对3个取样点总计39头奶牛的体细胞在不同时间计数,表明吖啶橙染色是一种快速、准确的监测奶牛体细胞数的方法,同时还表明不同的饲养条件及管理会造成牛群健康状况的显著差异,并依据实验结果对改善牛群的健康状况提出了建议。     

Prevalence and clonal nature of Escherichia coli O157:H7 on dairy farms in Wisconsin.

A survey was conducted between March and October of 1994 to determine the prevalence and identify the sources of serotype O157:H7 isolates of Escherichia coli in Wisconsin dairy herds. A stratified sample of 400 farms was identified, and 70 farms with weaned calves less than 4 months old were included in the study. During the prevalence study, 5 of the 70 farms (herd prevalence, 7.1 +/- 4.5%) and fecal samples from 10 of 560 calves (animal prevalence, 1.8%) tested positive for serotype O157:H7. In a follow-up study, the five O157:H7-positive farms and seven of the O157:H7-negative farms identified in the prevalence study were visited again. An additional 517 fecal samples from cattle of various ages were tested, and a total of 15 animals from four of the five herds that were previously positive and 4 animals from two of seven herds that were previously negative tested positive for E. coli O157:H7. Observations made during the follow-up study suggested that horizontal transmission was an important means of E. coli O157:H7 dissemination on the farms. A total of 302 environmental samples, were examined, and 2 animal drinking water samples from one previously negative farm and 1 animal drinking water sample from a previously positive farm contained E. coli O157:H7. Analyses by the pulsed-field gel electrophoresis technique of contour-clamped homogeneous electric field electrophoresis revealed that isolates from the same farm displayed identical or very similar XbaI restriction endonuclease digestion profiles (REDP), whereas isolates from different farms typically displayed different REDP. However, more than one REDP was usually observed for a given herd over the 8-month sampling period. Analyses of multiple isolates from an animal revealed that some animals harbored O157:H7 strains that had different REDP, although the REDP of isolates obtained from the same fecal sample were very similar. Collectively, 160 bovine isolates obtained from 29 different animals and three water isolates displayed 20 distinct XbaI REDP. Our data revealed that there are several clonal types of serotype O157:H7 isolates in Wisconsin and indicated that there is probably more than one source of this pathogen on the dairy farms studied. However, animal drinking water was identified as one source of E. coli O157:H7 on one farm.     

Managing the transition from purebred to rotational crossbred dairy cattle herds: three technical pathways from a retrospective case-study analysis

The growing interest in rotational crossbreeding in Western countries is due to its potential to improve reproductive and health performances of cows. Although a large amount of research focuses on assessing crossbred cows’ performances, how to manage the transition from purebred to rotational crossbred herds is under-explored. Based on a retrospective analysis of French dairy herd case studies, we aimed to identify and characterise technical pathways to make such a transition. In 2018, we performed semi-directive interviews on 26 commercial dairy farms. Data were collected to describe changes in breeding, replacement and culling management practices from the first crossbred mating with purebred cows to the management of a mainly crossbred herd in 2018. Based on a multivariate analysis, we identified two main guidelines structuring technical pathways to move towards rotational crossbred herds: (i) the depth and scale of change (i.e. farm v. herd) associated with the introduction of rotational crossbreeding in the whole-farm dynamics and (ii) the changes in herd replacement and breeding practices to adapt to the evolution of herd demographics induced by the evolution of the dairy crossbred mating rate over time (high from the beginning v. distributed over time). Hierarchical clustering discriminated three groups of farmers differing in their technical pathway to move towards a rotational crossbred herd. In pathway 1, farmers customised one or several rotational crossbreeding schemes to support whole-farm transition towards an organic or grass-based system. Once the scheme stabilised, they quickly implemented it and had to readjust replacement and culling practices to regulate imbalance in herd demographics induced by the improvement in cow fertility. In pathway 2, farmers also customised one or several rotational crossbreeding schemes to support whole-farm redesign but they implemented it more gradually in the herd, which induced no major imbalance in herd demographics. In pathway 3, farmers predefined a relatively well-known rotational crossbreeding scheme to correct fertility issues of purebred cows without any changes at the farm level. They implemented it quickly from the beginning and had to adapt herd replacement and culling to regulate imbalance in herd demographics induced by the improvement in cow fertility. These first empirical evidences on how dairy farmers manage the transition from a purebred to rotational crossbred herd provide original scientific and operational contributions.     

Welfare effects of a disease eradication programme for dairy goats

The Norwegian dairy goat industry has largely succeeded in controlling caprine arthritis encephalitis (CAE), caseous lymphadenitis (CLA) and paratuberculosis through a voluntary disease eradication programme called Healthier Goats (HG). The aim of this study was to apply an on-farm welfare assessment protocol to assess the effects of HG on goat welfare. A total of 30 dairy goat farms were visited, of which 15 had completed disease eradication and 15 had not yet started. Three trained observers assessed the welfare on 10 farms each. The welfare assessment protocol comprised both resource-based and animal-based welfare measures, including a preliminary version of qualitative behavioural assessments with five prefixed terms. A total of 20 goats in each herd were randomly selected for observations of human–animal interactions and physical health. The latter included registering abnormalities of eyes, nostrils, ears, skin, lymph nodes, joints, udder, claws and body condition score. For individual-level data, robust clustered logistic regression analyses with farm as cluster variable were conducted to assess the association with disease eradication. Wilcoxon rank-sum tests were used for comparisons of herd-level data between the two groups. Goats with swollen joints (indicative of CAE) and enlarged lymph nodes (indicative of CLA) were registered on 53% and 93% of the non-HG farms, respectively, but on none of the HG farms. The only other health variables with significantly lower levels in HG herds were skin lesions (P=0.008) and damaged ears due to torn out ear tags (P<0.001). Goats on HG farms showed less fear of unknown humans (P=0.013), and the qualitative behavioural assessments indicated that the animals in these herds were calmer than in non-HG herds. Significantly more space and lower gas concentrations reflected the upgrading of buildings usually done on HG farms. In conclusion, HG has resulted in some welfare improvements beyond the elimination of infectious diseases. The protocol was considered a useful tool to evaluate the welfare consequences of a disease eradication programme. However, larger sample sizes would increase the reliability of prevalence estimates for less common conditions and increase the power to detect differences between the groups. Despite the obvious link between disease and suffering, this aspect is rarely taken into account in the evaluation of disease control programmes. We therefore propose that welfare assessment protocols should be applied to evaluate the merits of disease control or eradication programmes in terms of animal welfare.     

Role of input self-sufficiency in the economic and environmental sustainability of specialised dairy farms

Increasing input self-sufficiency is often viewed as a target to improve sustainability of dairy farms. However, few studies have specifically analysed input self-sufficiency, by including several technical inputs and without only focussing on animal feeding, in order to explore its impact on farm sustainability. To address this gap, our work has three objectives as follows: (1) identifying the structural characteristics required by specialised dairy farms located in the grassland area to be self-sufficient; (2) analysing the relationships between input self-sufficiency, environmental and economic sustainability; and (3) studying how the farms react to a decrease in milk price according to their self-sufficiency degree. Based on farm accounting databases, we categorised 335 Walloon specialised conventional dairy farms into four classes according to their level of input self-sufficiency. To this end, we used as proxy the indicator of economic autonomy – that is, the ratio between costs of inputs related to animal production, crop production and energy use and the total gross product. Classes were then compared using multiple comparison tests and canonical discriminant analysis. A total of 30 organic farms – among which 63% had a high level of economic autonomy – were considered separately and compared with the most autonomous class. We showed that a high degree of economic autonomy is associated, in conventional farms, with a high proportion of permanent grassland in the agricultural area. The most autonomous farms used less input – especially animal feeding – for a same output level, and therefore combined good environmental and economic performances. Our results also underlined that, in a situation of decrease in milk price, the least autonomous farms had more latitude to decrease their input-related costs without decreasing milk production. Their incomes per work unit were, therefore, less impacted by falling prices, but remained lower than those of more autonomous farms. In such a situation, organic farms kept stable incomes, because of a slighter decrease in organic milk price. Our results pave the way to study the role of increasing input self-sufficiency in the transition of dairy farming systems towards sustainability. Further research is required to study a wide range of systems and agro-ecological contexts, as well as to consider the evolution of farm sustainability in the long term.     

Initial insights on the performances and management of dairy cattle herds combining two breeds with contrasting features

Finding ways of increasing animal production with low external inputs and without compromising reproductive performances is a key issue of livestock systems sustainability. One way is to take advantage of the diversity and interactions among components within livestock systems. Among studies that investigate the influence of differences in animals’ individual abilities in a herd, few focus on combinations of cow breeds with contrasting features in dairy cattle herds. This study aimed to analyse the performances and management of such multi-breed dairy cattle herds. These herds were composed of two types of dairy breeds: ‘specialist’ (Holstein) and ‘generalist’ (e.g. Montbeliarde, Simmental, etc.). Based on recorded milk data in southern French region, we performed ANOVA: (i) to compare the performances of dairy herds according to breed-type composition: multi-breed, single specialist breed or single generalist breed and (ii) to test the difference of milk performances of specialist and generalist breed cows (n = 10 682) per multi-breed dairy herd within a sample of 22 farms. The sampled farmers were also interviewed to characterise herd management through multivariate analysis. Multi-breed dairy herds had a better trade-off among milk yield, milk fat and protein contents, herd reproduction and concentrate-conversion efficiency than single-breed herds. Conversely, they did not offer advantages in terms of milk prices and udder health. Compared to specialist dairy herds, they produce less milk with the same concentrate-conversion efficiency but have better reproductive performances. Compared to generalist dairy herds, they produce more milk with better concentrate-conversion efficiency but have worse reproductive performances. Within herds, specialist and generalist breed cows significantly differed in milk performances, showing their complementarity. The former produced more milk for a longer lactation length while the latter produced milk with higher protein and fat contents and had a slightly longer lactation rank. Our results also focus on the farmers’ management of multi-breed dairy herds underlying herd performances. Three strategies of management were identified and structured along two main axes. The first differentiates farmers according to their animal-selection practices in relation with their objectives of production: adapting animal to produce milk with low-feeding inputs v. focussing on milk yield trait to intensify milk production. The second refers to the purpose farmers give to multi-breed dairy herds: milk v. milk/meat production. These initial insights on the performances and management of multi-breed dairy herds contribute to better understanding the functioning of ruminant livestock systems based on individual variability.     

Development and application of an integrated sustainability index for small-holder dairy farms in Rajasthan,India

In agrarian economy of developing nations like India, smallholder dairy production is an important enterprise and its sustainability is vital for ensuring livelihood and nutritional security to the masses. Studies on methodological aspects of farm sustainability at micro-level are limited, either confined to a particular dimension of sustainability or based on complex data requirement which is not feasible to obtain in the context of smallholder dairy farms. This study has developed a multi-attribute farm level sustainability assessment method encompassing economic, social and ecological dimensions of sustainability and has applied it to assess the sustainability of dairy farming in north-western part of India. Based on data from 120 dairy farms located in rural area of Jaipur district from the state of Rajasthan, the study computed the composite Sustainable Dairy Farming Index (SDFI). The overall substantiality status of the smallholder dairy farms in the study area was not encouraging, implying that it may not be viable for future generation to take up the enterprise. Among the three dimensions of sustainability, the average scores of ecological dimension were highest followed by the economic and social sustainability scores. Some of the core attributes like feed productivity, management of animal genetic potential and gender equality are particularly weak aspects of the dairy production system in India. The direct relationship of economic sustainability with herd size suggests for farmers with very small herds (one to two) animals, increasing the number of dairy animals to about five to six, would be a good strategy to economize on input costs and generate more marketed surplus of milk.     

A generalised additive model to characterise dairy cows’ responses to heat stress

Heat stress is one of the most critical issues jeopardising animal welfare and productivity during the warm season in dairy cattle farms. The global trend of increase in average and peak temperatures is making the problem more and more serious. Many devices have been introduced in livestock farms to monitor and control temperature-humidity index, as well as animal behaviour and production parameters. The consequent availability of collected databases has increasingly enhanced the research aimed to understand the consequences of heat stress in cattle, in relation to genetic, reproductive, productive and behavioural features. Moreover, these investigations laid the foundations for the development, calibration, validation and test of numerical models quantifying the individual responses to heat stress conditions. In this work, a generalised additive model with mixed effects has been developed to analyse the relationship between milk production, animal behaviour and environmental parameters based on data surveyed in 2016 in an Italian dairy farm. Each cow has been characterised in terms of her response to heat conditions, and the results led to define three classes of susceptibility to heat stress within the herd. These attributes have then been related to the various phenotypic parameters collected by the precision livestock farming devices used in the farm. The study provides a model to understand the effects of heat stress conditions on individual animals in relation to the main parameters describing their rearing conditions; moreover, the results contribute to improve the herd management by lending indications to define targeted treatments according to the cow’s characteristics.