A New, Practical Animal Welfare Assessment for Dairy Farmers

Animal-based welfare indicators for dairy cows and their validity and practicality: a systematic review of the existing literature

Animal welfare is of increasing importance, with consumers preferring animal products made with ethical practices due to growing awareness. This shift highlights the need for reliable methods to evaluate welfare. This systematic review aims to assess the validity of current animal-based welfare indicators for dairy cows to aid farmers and agricultural professionals in evaluating and improving welfare amidst the lack of a clear legislative definition. The literature search spanned five databases: CAB Direct, PubMed, Scopus, Google Scholar and Livivo, covering publications in English and German from 2011 to 2021. Specific search terms were employed, and abstracts were screened for relevance. Publications were categorized based on exclusion criteria, with a final verification process conducted by three independent scientists. Research highlights correlations between welfare measures, farm characteristics and innovative indicators like hair cortisol concentration. Farming systems and housing methods significantly affect welfare, with pasture-based systems generally resulting in reduced lameness and improved behavior. Proper housing design and management practices are important, as they influence indicators like lameness and cleanliness. Heart rate variability and heart rate monitoring provide insights into dairy cow stress levels during milking and other stressors, making them valuable for welfare assessment. Biomarker research emphasizes the need to balance productivity and health in breeding strategies, as high milk production alone does not indicate good welfare. Behavioral studies and the human-animal relationship are key to understanding welfare. Precision Livestock Farming offers real-time assessment capabilities, although validation is needed. Stress physiology is complex, and while cortisol measurement methods are promising, further research is necessary. Assessment tools like the Animal Needs Index and routine herd data analysis are valuable for identifying welfare concerns. Key findings highlight the WQ® protocol's effectiveness and versatility, the challenge of its time demands, and the DCF protocol's promise for more practical and efficient welfare assessments. Commercial animal welfare audits should prioritize easily observable indicators and herd records due to logistical constraints in measuring biomarkers or heart rate variability. This focus on easily accessible indicators, such as body condition score, lameness, claw health, cleanliness, and somatic cell count allows effective welfare assessments, enabling prompt action to enhance wellbeing.

Exploring uses for an algorithmically generated Animal Welfare Indicator for welfare assessment of dairy herds

On-farm welfare assessment is time-consuming and costly. Assessing welfare using routinely collected herd data has been proposed as a more economical alternative. The online Animal Welfare Indicator (AWI), developed by a Norwegian dairy cooperative, applies an algorithm to routinely collected health, production, and management data to "indicate" aspects of animal welfare at herd level. The overall AWI score is based on 10 AWI subindicator scores, representative of elements of animal welfare such as claw health, udder health, and mortality. Our cross-sectional study explored 2 ways in which the AWI may enable more efficient welfare assessment of Norwegian dairy herds. First, we investigated using the AWI to reduce the duration of on-farm assessments by replacing on-farm measures. Second, we examined reducing the number of on-farm welfare assessments by using the AWI to predict which herds have poorer welfare with respect to specific on-farm measures. Using Spearman rank analyses, we investigated if the AWI scores for 157 herds were associated with 24 on-farm welfare variables measured contemporaneously by Welfare Quality assessment. The mortality AWI subindicator score and the percentage mortality in the previous 12 mo were moderately correlated, as were the udder health AWI subindicator score and the percentage high somatic cell count (SCC) in the previous 3 recordings. Only negligible or weak correlations were found between the other AWI scores and the on-farm assessment variables. We built Generalized Linear Models using AWI scores as independent variables to predict herds with poorer welfare. Herds were classified as having poorer welfare based on their results in specific on-farm welfare measures. We evaluated the models' predictive ability and accuracy. Moderately accurate models were built for predicting poorer herds with respect to high SCC, mortality, and moderate or severe lameness. The other models were less accurate. The AWI scores were generally unsuitable as replacements of on-farm welfare measures. The AWI subindicators for udder health and mortality could replace the on-farm welfare measures related to those 2 topics, but there was some overlap in the data used to calculate them. Despite a lack of independence, the use of those 2 AWI subindicators may marginally reduce the duration of on-farm assessments. A prediction model based on AWI scores showed potential for identifying herds with poorer welfare in terms of moderate or severe lameness, facilitating more efficient use of resources for on-farm lameness assessment. As a consequence of the data used in the AWI, it was only reflective of health-related welfare outcomes.

Development of a benchmarking tool to assess the welfare of dairy cattle on small-scale farms

Public concern about the welfare of farm animals and the livestock industry's awareness of the need to improve animal welfare have led to the implementation of new tools designed to meet this objective. Especially in the case of small-scale farms in marginalized areas, the lack of available data specifically for assessing welfare led to the present study. Its aim was to use animal- and resource-based indicators that are representative of small-scale farms, to establish an index and develop a benchmarking tool that can be used to dynamically evaluate the welfare of cattle on farms with different husbandry systems and provide farmers, veterinarians, extension officers, and stakeholders with reliable information that can be used as a decision support tool. For this reason, 1,891 cows from 204 herds housed in freestall (n = 111) and tiestall (n = 93) husbandry systems in South Tyrol (Northern Italy) were evaluated. The results showed that 17.6% of herds (36 farms) had an average score below 60 (out of 100), which means that immediate intervention should be adopted to improve welfare. South Tyrolean dairy farms performed well in terms of lameness, skin alterations, avoidance behavior, number and space of lying areas, and dystocia occurrence scores, whereas water supply, cow cleanliness status, claw conformation, and getting-up behavior offered significant potential for improvement. Significant differences were observed between housing systems scoring less than 60 out of 100 points in 9.9% (n = 11) and 26.9%, (n = 25), of the herds kept in freestalls and tiestalls, respectively. A slight difference was found when comparing the percentage of herds with high scores, which corresponded to 30.6% (n = 34) of herds housed in freestalls and 22.6% (n = 21) of herds housed in tiestall housing systems. In addition, it was shown that animals reared on farms with tiestalls more often had problems with body condition, cleanliness, and skin alterations. All individual welfare indicators in the top 25% of herds had scores above 80, indicating that this may be an attainable target for freestall and tiestall herds, respectively, to promote good dairy cow welfare. The overall aim must be to adopt measures to increase the scores on all farms closer to this level.

Obtaining an animal welfare status in Norwegian dairy herds-A mountain to climb

Introduction

Knowing the national status of animal welfare, one can identify welfare problems and set a benchmark against which improvements can be compared. Such a status is potentially invaluable for tangible, sustained animal welfare improvement. The objective of this cross-sectional study was to report the status of animal welfare in Norwegian loose-housed dairy herds as assessed using the Welfare Quality^® Assessment Protocol. Additionally, we investigated if the welfare status varied on a regional basis.

Methods

In total, 155 herds in eight of Norway's eleven counties were assessed by six trained Welfare Quality^® assessors. This article presents the herd prevalences of common welfare issues in dairy production in Norway, as well as integrated welfare scores. To determine whether welfare status varied regionally in Norway, generalized linear modeling was used to estimate the mean welfare score for five regions in the four Welfare Quality^® principles: A. Good feeding, B. Good housing, C. Good health, and D. Appropriate behavior. These estimated mean welfare scores and their 95% confidence intervals were subsequently assessed for significant variation.

Results

Encouraging findings included the low mean herd prevalence of 'very lean' cows (3.0%) and the high proportion of cows (59.8%) which could be touched during avoidance distance testing, indicating a positive relationship between stockpeople and their cattle. Challenges affecting the welfare of Norwegian dairy cows were also identified. Of particular concern were issues related to the cows' environment such as prolonged times needed to complete lying down movements and integument alterations. No herd was completely free of changes to the integument and, on average, 77.9% of each herd were affected either mildly or severely. Animal welfare did not appear to vary much between the five regions assessed. Our investigation revealed significant regional variation between two regions (Trøndelag and Vestlandet North) in only the Welfare Quality^® principle Good housing (p < 0.01).

Discussion

The almost complete absence of regional variation demonstrates that animal welfare status generally varies most at herd level. In conclusion, both welfare challenges and encouraging findings were identified in loose-housed Norwegian dairy herds. To improve animal welfare, herd-specific interventions are most likely to be effective in these herds.

The relationship between common data-based indicators and the welfare of Swiss dairy herds

The assessment of dairy cow welfare has become increasingly important in recent years. Welfare assessments that use animal-based indicators, which are considered the most direct indicators, are time consuming and therefore not feasible for assessments on a large number of farms. One approach to reducing this effort is the use of data-based indicators (DBIs) calculated from routine herd data. The aim of this study was to explore the relationship between common DBIs and the welfare of 35 dairy herds to evaluate the feasibility of a data-based welfare prediction method. For this purpose, the WelfareQuality® (WQ) protocol was used to assess the welfare of dairy cows on 35 Swiss farms, for each of which 10 commonly used DBIs were calculated from herd data. Spearman's rank correlations were used to investigate the relationship between DBIs and WQ criteria and measurements. The study found only a few statistically weak associations between DBIs and animal welfare, with no associations for measurements or criteria of resting comfort and appropriate behavior. Thus, the multidimensional welfare definition is insufficiently covered, and the present publication does not support the approach of a purely data-based prediction of dairy welfare status at the farm level. Instead, the regular calculation of DBIs that are indicative of isolated animal welfare problems or metrics of animal health could allow monitoring of these specific areas of animal welfare.

Practical Application of the Five Domains Animal Welfare Framework for Supply Food Animal Chain Managers

The author has worked as a consultant with global commercial supply managers for over 20 years. The focus of this commentary will be practical application of The Five Domains Model in commercial systems. Commercial buyers of meat need simple easy-to-use guidelines. They have to use auditors that can be trained in a workshop that lasts for only a few days. Auditing of slaughter plants by major buyers has resulted in great improvements. Supply chain managers need clear guidance on conditions that would result in a failed audit. Animal based outcome measures that can be easily assessed should be emphasized in commercial systems. Some examples of these key animal welfare indicators are: percentage of animals stunned effectively with a single application of the stunner, percentage of lame animals, foot pad lesions on poultry, and body condition scoring. A farm that supplies a buyer must also comply with housing specifications. The farm either has the specified housing or does not have it. It will be removed from the approved supplier list if housing does not comply. These types of easy to assess indicators can be easily evaluated within the four domains of nutrition, environment, health and behavioral interactions. The Five Domains Framework can also be used in a program for continuous improvement of animal welfare.

New Approaches for risk assessment and management of bovine protothecosis

Protothecosis is a potential zoonosis related to bovine mastitis. In several countries, a higher incidence of protothecal bovine mastitis that is being recorded and the resistance of Prototheca species to various factors (chlorine, high temperatures, antimicrobial and antiseptic treatments, pH variations), make it difficult to control its spread among farms. The authors aim to describe the infection caused by microalgae, focusing on the problems within cattle farms and proposing new approaches to farm management, based on Regulation (EU) No 2016/429 on transmissible animal diseases. This new flexible approach, based on risk analysis, is a further tool in protecting against Prototheca species. The list of transmissible animal diseases under Regulation (EU) No 2016/429 includes those caused by microorganisms resistant to antimicrobials, which can have important implications for human and animal health, feed and food safety. This approach would involve a series of changes to the rules used for Official Controls (Regulation (EU) No 2017/625) moving from the concept of the food chain to that of the agri-food chain.

Data-Based Variables Used as Indicators of Dairy Cow Welfare at Farm Level: A Review

Simple Summary

In recent years, the interest in the use of data from routine herd records in the monitoring of dairy welfare at farm level has increased. This review compiles 13 papers to outline the current potential of data-based variables for animal welfare monitoring. All the identified studies showed associations between data-based variables and farm-level dairy cow welfare and therefore provide a first indication of the possible use and suitability of data-based variables for welfare monitoring. However, we found that the definitions of animal welfare, its assessment on the farm, and the data-based variables varied considerably. Consequently, the current state of research does not allow a conclusive assessment of the potential of data-based variables for animal welfare monitoring. Therefore, future research is needed to clarify the potential of data-based variables. Harmonisation of the data-based variables and the use of valid measurements that reflect the multidimensionality of welfare could contribute to increased comparability between the studies.

Abstract

During the last years, the interest in data-based variables (DBVs) as easy-to-obtain, cost-effective animal welfare indicators has continued to grow. This interest has led to publications focusing on the relationship between DBVs and animal welfare. This review compiles 13 papers identified through a systematic literature search to provide an overview of the current state of research on the relationship between DBVs and dairy cow welfare at farm level. The selected papers were examined regarding their definition of animal welfare and classified according to this definition into three categories: (a) papers evaluating DBVs as predictors of animal welfare violations, (b) papers investigating the relationship between DBVs and animal-based measurements, and (c) papers investigating the relationship of DBVs to scores of welfare assessments like the Welfare Quality protocol or to overall welfare scores at farm level. In addition, associations between DBVs and indicators of animal welfare were extracted, grouped by the type of DBV, and examined for replications that may confirm the associations. All the identified studies demonstrated associations between DBVs and animal welfare. Overall, the first indications of a possible suitability of DBVs for predicting herds with animal welfare violations as well as good or poor animal welfare status were given. The evaluation of relationships between DBVs and animal-based measurements (ABMs) found mortality-based DBVs to be frequently associated with ABMs. However, owing to varying definitions of animal welfare, the use of different variants of DBVs, and different methods used to assess DBVs, the studies could only be compared to a limited extent. Future research would benefit from a harmonisation of DBVs and the use of valid measurements that reflect the multidimensionality of welfare. Data sources rarely investigated so far may have the potential to provide additional DBVs that can contribute to the monitoring of cow welfare at farm level.

The Relationship between Animal Welfare and Antimicrobial Use in Italian Dairy Farms

Information regarding the relationship between animal welfare (AW) and antimicrobial use (AMU) in dairy cows is limited. The current study aimed to investigate this relationship on Italian farms and to identify potential targets of AMU reduction. The study was performed at 79 Italian dairy farms housing over 15,000 cows during 2019. AW was scored with an on-farm protocol assessing farm management and staff training, housing systems, and animal-based measures. AMU was estimated using a defined daily dose per kg of animal biomass (DDDAit/biomass) for Italy. The median AW score was 73% (range: 56.6-86.8%). The median AMU was 4.8 DDDAit/biomass (range: 0-11.8). No relationship between the total AMU and AW was found. Management and staff training were positively associated with the use of the European Medicines Agency's category B antimicrobials, which are critical for human medicine, and with intramammary products for dry cow therapy. In those farms, antimicrobial stewardship should aim to reduce the category B antimicrobials and selective dry cow therapy. Our results underline the importance of implementing both an integrated monitoring system (AW, AMU, etc.) and antimicrobial stewardship tailored to the specific needs of each dairy farm.

Precision Technologies to Address Dairy Cattle Welfare: Focus on Lameness, Mastitis and Body Condition

Simple Summary

The welfare of farm animals is a growing concern in the EU and across the world. In milk production, there is a strong need to assess the welfare of dairy cows. One of the most sound assessment initiatives has been practiced using protocols developed by the Welfare Quality project. These protocols mainly support the assessment of cow welfare with animal-based indicators. However, evaluating these indicators is time-consuming and expensive, so using precision livestock farming (PLF) solutions is a way forward and is becoming a reality in the dairy industry. This review presents advances in PLF solutions, particularly in the last five years, and for assessing the animal-based indicators of lameness, mastitis, and body condition in dairy cattle farming.

Abstract

Specific animal-based indicators that can be used to predict animal welfare have been the core of protocols for assessing the welfare of farm animals, such as those produced by the Welfare Quality project. At the same time, the contribution of technological tools for the accurate and real-time assessment of farm animal welfare is also evident. The solutions based on technological tools fit into the precision livestock farming (PLF) concept, which has improved productivity, economic sustainability, and animal welfare in dairy farms. PLF has been adopted recently; nevertheless, the need for technological support on farms is getting more and more attention and has translated into significant scientific contributions in various fields of the dairy industry, but with an emphasis on the health and welfare of the cows. This review aims to present the recent advances of PLF in dairy cow welfare, particularly in the assessment of lameness, mastitis, and body condition, which are among the most relevant animal-based indications for the welfare of cows. Finally, a discussion is presented on the possibility of integrating the information obtained by PLF into a welfare assessment framework.

A Results-Oriented Approach for the Animal Welfare Measure of the European Union's Rural Development Programme

Farm animal welfare is a major concern to the European Union's citizens, addressed in the Rural Development Programmes by a specific animal welfare support measure. Previous evaluation results reveal that the implemented action-oriented measures fail when it comes to improving animal health, an important dimension of animal welfare. Results-oriented measures could compensate for this deficiency, but little is known about their design. In order to improve the effectiveness of current animal welfare measures for dairy cows, we analysed the elements of such a measure in an interdisciplinary, application-oriented research project involving agricultural economists and livestock scientists. We have used a mixed methods approach including a written Delphi survey, group-discussions and on-farm data-collection to select suitable indicators, develop an approach for the identification of threshold values and to design a support measure. Results suggest that, in animal welfare support measures, action- as well as results-oriented elements are necessary to address all dimensions of animal welfare.