Animal welfare is an essential component of sustainable dairy farming but still in India it is in nascent phase and standard protocol for assessment of welfare of all livestock species specially farms animals not developed yet. The main aim of this study to evaluate the welfare status of dairy cattle using ten output-based indicators across small, medium, and large dairy farms in Haryana. The indicators included body condition score, cow comfort index, cow cleanliness score, lameness score, human–animal relationship, mastitis incidence, hock injury score, abnormal behaviors, average productivity, and reproductive efficiency which is already explored in India. The data for measurement of those indicators for different types of farms were done as per scale suggested by DAWA Scale developed in India by NDRI Karnal. Data were collected through field observations and farmer interviews. Statistical analysis showed significant variation in welfare scores among farm sizes, with large farms generally exhibiting better comfort and body condition, while medium farms had higher mastitis incidence and behavioral abnormalities. Principal Component Analysis (PCA) was employed to interpret multidimensional welfare data. PC1, accounting for the majority of variance, represented comfort and health-related parameters, while PC2 was associated with behavioral stress and human interaction. The bi-plot clearly clustered farms based on their welfare characteristics, demonstrating the value of PCA in identifying risk patterns. This study highlights the importance of integrating animal or output-based indicators into national welfare monitoring systems and provides a replicable, data-driven framework for evaluating dairy cattle welfare in India.
Kumar et al. (Fri,) studied this question.
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