First scientific assessment protocol to assess animal welfare in cattle: a novel study from India

doi:10.21203/rs.3.rs-4825298/v1

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First scientific assessment protocol to assess animal welfare in cattle: a novel study from India

https://doi.org/10.21203/rs.3.rs-4825298/v1

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The increasing importance of animal welfare in Veterinary Medicine highlights the need for a comprehensive scientific assessment protocol for evaluating animal well-being across diverse animal husbandry setups in Haryana, India. In light of this gap, our study has been meticulously crafted to rectify these critical deficiencies and a protocol was developed to assess animal welfare in cattle. Conducted over 1.5 years (March 2022 - August 2023) in various animal husbandry setups of cattle [gaushalas (cattle shelters) having zebu cattle, organized and unorganized farms having exotic/crossbred cattle] across two agro-climatic zones (North Eastern (NE) and South Western (SW) Haryana), the study involved two stages. First, a detailed analysis of existing studies utilizing different biomarkers as indicators of bovine health and welfare, both in our country and abroad, was performed. The second stage involved evaluating selected animal welfare biomarkers in different husbandry setups. Through comprehensive analysis, we identified the necessity of a systematic evaluation protocol comprising twenty welfare indicators, including four physical measures, two behavioral measures and fourteen physiological/immunological measures. For the first time in India, this diverse set of indicators provides a robust foundation for thoroughly and scientifically evaluating and monitoring the health and welfare of cattle across different husbandry setups.

Health sciences/Biomarkers/Predictive markers

Health sciences/Risk factors

Animal welfare

Cattle

Assessment protocol

Principal component analysis

India.

Humans use animals for clothing, food, companionship, recreation, draught power, research and education. To meet population needs, we have altered animal environments and genetics¹. India boasts a substantial livestock population, with around 193.46 million cattle and 109.85 million buffaloes. Haryana state, in particular, stands out for its exceptional buffaloes (4.4 million) and cattle (19.3 million) population, according to the 20th Indian Livestock Census of 2019. Animal welfare has achieved significant global prominence and this is increasingly seen as relevant to improving animal husbandry worldwide². The term "animal welfare" has been used since 1965 and was first defined by Brambell³. The best way to measure animal welfare is through animal-based indicators that reflect their experiences. Modern protocols also assess the animal's feelings and its capacity for positive experiences^4,5. A scientific method for assessing body language would enhance our understanding of farm animals' experiences and improve the accuracy of health and welfare measurements. Thus, there is a growing need for reliable welfare assessment methods⁶. An appropriate and practicable animal welfare assessment protocol is developed only by identifying and selecting suitable welfare measures for each production system and the chosen measures need to be repeatable, relevant and comparable across farms with similar production systems⁷.

Despite efforts to develop animal welfare standards, issues remain controversial, particularly regarding the accuracy and reliability of welfare indicators⁸. An indicator is something that "indicates the state or level of something"⁹. Validity, reliability and feasibility are three principles that a possible indicator of animal welfare must adhere to^10,11. Resource and management-based measures are indirect markers of animal welfare, while animal-based measures, or direct indicators, assess how animals react to resources and management approaches¹². Thus, using a variety of scientifically verified indicators is crucial for accurately assessing animal welfare. These indicators should encompass all aspects of well-being (behavioral, psychological and physiological) and reflect an individual's chronic state¹³. Various indicators such as behavioural measures (general temperament; avoidance distance etc), physical measures (body condition score; lameness score; skin lesions/integument alterations; teat and udder condition; rumen fill score etc), production measures (impaired growth; reduced body weight; impaired production; reduced milk yield etc) and physiological measures (measuring the levels of catecholamines (epinephrine and norepinephrine); cortisol and various species specific acute phase proteins) directly reflect the welfare status of the animal^1,14,15.

In this era of commercialization and intensification of dairy farming, there is a lacuna about the use of animal welfare indicators to assess welfare in the context of large animal husbandry practices in India, particularly in cattle. Farmers can gain from increasing welfare by increasing productivity and profitability, such as through lower animal mortality and better animal health, better product quality, increased disease resistance, decreased medication use, decreased risk of foodborne diseases and zoonoses and the potential to charge consumers more¹⁶. Recognizing the growing importance of animal welfare in the field of Veterinary Medicine, there is a concurrent surge in the demand for dependable methodologies to evaluate animal welfare. A scientific assessment protocol that includes a range of animal welfare indicators to evaluate the health and welfare of animals in various animal husbandry setups in Haryana state or in India is lacking. In response to this need, our study has been strategically designed to develop a scientific assessment protocol to assess animal welfare in Indian cattle to address and bridge these critical gaps in the current understanding of large animal welfare.

Study design

The study is reported in accordance with ARRIVE guidelines and also followed the relevant guidelines, regulations and ethical standards of the Institutional Animal Ethics Committee (IAEC) of Lala Lajpat Rai University of Veterinary and Animal Sciences (LUVAS), Hisar, Haryana, India.

Ethical approval

The study was approved by the IAEC of LUVAS, Hisar, Haryana, India under approval number VCC/IAEC/2022/1624 + 51.

Methodology for searching literature and criteria for inclusion in study

The first stage of work was to comprise a detailed analysis of available studies that have been conducted using different biomarkers as indicators for the evaluation of bovine health and welfare in our country India and abroad. Using different keywords like "animal welfare or cattle welfare or positive welfare indicator or gaushala (cattle shelters) welfare or acute phase proteins", a methodical search for published articles was carried out. Different databases, including Google Scholar, PubMed, CAB Direct, Krishikosh, Web of Science and Research Gate, were utilized to thoroughly collect research articles that were published in both domestic and foreign journals. The publication date was not restricted in any way. From the reference lists of the articles produced by the database search, more articles were also searched manually. The criteria for inclusion and exclusion of studies in selecting welfare indicators have been established. Inclusion criteria were as follows: study conducted anywhere in India or abroad on cattle welfare; study on physical measures of cattle welfare; study on behavioural measures of cattle welfare; study on physiological measures of cattle welfare; study on production measures of cattle welfare; study on animal-based measures of cattle welfare and complete text of the article available. Exclusion criteria in gathering information were: study on Resource-Based measures of cattle welfare; research not addressing cattle welfare; full text of research article unavailable and study on animals other than cattle.

Retrieval of data

After a systematic review and comprehensive analysis of more than 300 publications conducted in our country and abroad, a total of 42 articles were included to determine the set of biomarkers that can act as indicators (number of selected indicators 53 in total) of cattle welfare in different animal husbandry setups in Haryana, India. The experts were also consulted over the chosen welfare indicators along with their trends to determine areas of agreement and disagreement. Local factors affecting animal health and their welfare were also considered during the study. The Welfare Quality® Protocol goal of acceptable behavior, housing, health and good feeding was also kept in mind while deciding the set of indicators¹⁷. These were in accordance with the "Four Principles" to uphold the "Five Freedoms" of animal welfare and the possibility to quantify them in typical circumstances¹⁸.

Welfare indicators used for the assessment of the cattle welfare

Physical measures: Body Condition Score (BCS)^19,20 were determined by using a scale of 1-5 by visual examination: 1 - Very bad condition (emaciated): Spinal crest looks like the teeth of the saw, transverse processes are very prominent > ½ length visible, ischial bones very prominent with a deep V-shaped cavity below the tail; 2 - Skeleton clearly visible: Spinal crest vertebra’s individually recognizable, transverse processes are for ½ - 1/3 visible. Ischial bones prominent, U-shaped cavity below the tail; 3 - Skeleton and covering well balanced: Spinal crest form a sharp edge, transverse processes ¼ visible, ischial bones softly curved, shallow cavity below tail; 4 - Almost everything covered: vertebra’s of spinal crest are flat and cannot be individually defined, transvers processes are softly curved, ischial bones are surrounded by fat, cavity filled with some fat under tail; 5 - Too much fat: Spinal covered with fat, edge of transverse processes barely visible because of fat, ischial bones covered by fat, cavity filled with fat, folds arise. Lameness scoring²¹ was conducted using a numerical rating scale of 1-5 based on visual examination: 1 - Not lame (smooth and fluid movement); 2 - Mildly lame but not observable easily (an imperfect gait but able to freely move with a mildly arched back); 3 - Moderately lame (able to move but not freely, with an arched back); 4 - Lame (with inability to move freely with and asymmetrical gait and abnormal head movement); 5 - Severely lame (severely restricted in movement, requiring considerable encouragement to move and a severely arched back). Claw overgrowth^21,22 was assessed by visual examination on a scale of 0 – 3: 0 - Normal claws; 1 - Mild claw overgrowth; 2 - Moderate claw overgrowth; 3 - Severe claw overgrowth. Hock joint swellings²³ was assessed through visual examination using a scale of 0 to 3: 0 – Normal; 1 - Mild swollen joint; 2 - Medium swollen joint; 3 - Severely swollen joint. Dirtiness of the hind limbs, udder and flanks⁴ were scored (1 - 4) by visual inspection of the cows from both sides (left and right) and from behind: 1 - No dirtiness; 2 - Mildly dirty (small soiled areas of dirtiness with no thick scabs); 3 - Medium dirtiness (large soiled areas but with < 1 cm thick scabs of dung); 4 - Severely dirty (large soiled areas with > 1cm thick dung scabs). Ectoparasitism²⁴ was categorized as follows: 1 - Absence of ectoparasites; 2 - Mild infestation - no lesions (not easily visible by naked eye but on tactile perception in the neck region; 3 - Moderate - mild infestation visually observable ectoparasites or immature forms or eggs in the neck, groin, peri rectal, tail root and switch regions; 4 - Severe - visually observation of mature ectoparasites all over the body especially regions mentioned in score 3. Skin lesions / Integument alterations²⁵ were described by using a 3-point scale: 0 - Normal (no apparent lesions); 1 - Mild hair loss (< 2 cm²); 2 - Moderate (> 2 cm² hair loss and inflamed skin); 3 - Severe (a large > 4 cm² area of hair loss with extensive skin inflammation and breakage). Teat and udder condition¹⁴ was graded on the following scale of 1 – 6: 1 - Normal teats and udder; 2 - Dry udder and teats; 3 - Teat cracks; 4 - Warts on teats and udder; 5 - Acute lesions on the teats and udder; 6 - Chronic lesions on teats and udder. Ocular lesions²⁶, Nasal Discharge²⁶, Hampered respiration²⁶ & Vulvar Discharge²⁶ were assessed by visual examination on scale of 0 – 1: 0 – absent; 1 – present. Rumen Fill Score²⁷ was decided by visually inspecting the animal by standing behind it on its left side and observing the left para lumbar fossa between the last rib, the lumbar transverse processes and the hip bone. Scoring was done in the range of 1-5: 1 - The para lumbar fossa is empty, presenting a rectangular cavity that is more than a hand’s width behind the last rib and a hand’s width under the lumbar transversal processes. 2 - The para lumbar fossa forms a triangular cavity with a width about the size of a hand behind the last rib, but less than this under the lumbar transverse processes. 3 - The para lumbar fossa forms a cavity less than a hand’s width behind the last rib and about a hand’s width vertically downwards from the lumbar transverse processes and then bulges out. 4 - The para lumbar fossa skin covers the area behind the last rib and arches immediately outside below the lumbar transverse processes due to a bloated rumen. 5 - The rumen is distended and almost fills up the para lumbar fossa; the last rib and the lumbar transverse processes are not visible. Faecal consistency²⁷ was scored in the scale of 1 – 5: 1 - thin and watery and not truly recognizable as faeces; 2 - thin custard-like consistency, structurally recognizable as faeces, splashing out wide upon falling on the floor; 3 - thick custard-like consistency, making a plopping sound while falling on the floor and a well-circumscribed pad which spreads out and is about 2 cm thick; 4 - stiff with a heavy plopping sound while falling on the floor and a proper circumscribed pad with visible rings and minimal spreading out; 5 - hard fecal balls like horse faeces.

Behavioural measures: General temperament²⁸ was scored after visual examination of the animal: 0 – Docile; 1 – Aggressive. For the avoidance distance²⁹, animals that were standing at the feeding manger were approached from the front at a rate of one step per second, starting at 2 m from the manger. The distance between the assessor’s hand and the cow’s head was estimated at the moment cow moved away and turned its head. Scoring was done on a scale of 0 to 3: 0 – Touched; 1 - 0 to 50 cm; 2 - 51 to 100 cm; 3 - > 100 cm. Rising behavior^30,31 was categorized using an existing protocol. All animals lying in the shelter were coaxed to get up with use of a minimum amount of force. If the presence of the assessor did not evoke rising, they were given one or two gentle slaps on the back, followed by a break of 5 seconds, then more slaps with slightly more force if required, up to a maximum of 30 seconds. Score was given in the range of 1 to 5: 1 - Normal (smooth and a normal sequence of rising behaviour); 2 - Easy but slightly interfered (smooth movement with slight twisting of the head but with normal sequence of rising process); 3 - Uneasy with effort (sudden movement and difficulty in rising with awkward twisting of the head and neck but following a normal sequential rising process); 4 - Abnormal (uncharacteristic sequence of a rising event); 5 - Refused to get up. Rising restrictions³² as a result of shelter facilities were scored on a scale of 0 to 3: 0 - Unrestricted (cow can rise as if it were in a pasture); 1 - Mild restrictions (cow can modify standing to rise comfortably as it lunges sideways and not forwards); 2 - Cow takes time to rise and hits shed fixtures or fittings while rising; 3 - Dog sitting posture adopted while standing or make multiple attempts before able to rise.

Physiological/Immunological measures: Haematological Parameters^{33,34,35,36,37}: A total of approximately 10 ml blood was collected aseptically using EDTA (Ethylenediamine tetra acetic acid) powder/heparin coated sterile vials from jugular vein of the apparently healthy animals. The automated haematology cell counter (MS4se, Melet Schlosing Lab.) was used to analyze the blood samples for different parameters viz. haemoglobin (Hb); packed cell volume (PCV); total erythrocyte count (TEC); total leucocyte count (TLC); differential leucocyte count (DLC) comprising of neutrophils (N), lymphocytes (L), monocytes (M), eosinophils (E) and basophils (B); platelet count; erythrocytic indices such as mean corpuscular haemoglobin (MCH), mean corpuscular volume (MCV) and mean corpuscular haemoglobin concentration (MCHC). Biochemical Parameters^35,38,39: A paired blood sample was also collected from animals and serum was separated by centrifugation at 3000 rpm for 15 minutes. The biochemical parameters viz. blood glucose, cholesterol, calcium, phosphorus (P), alkaline phosphatase (ALP), total proteins (TP), lactate dehydrogenase (LDH), serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic pyruvic transaminase (SGPT), gamma-glutamyl transferase (GGT), blood urea, serum creatinine, triglycerides, creatine kinase (CK) and magnesium were determined in the serum samples using an automated random access clinical chemistry analyzer (EM Destiny 180/200, Erba Diagnostics Mannheim GmbH). Glucocorticoid, catecholamine and acute phase proteins^40,41,42,43: Serum samples were used to estimate these parameters viz. cortisol, epinephrine, haptoglobin (Hp), serum amyloid A (SAA), fibrinogen (Fbg), C reactive protein (CRP) and albumin. Estimation was done using commercially available ELISA Kits (Bioassay Technology Laboratory, Nanhu Dist, Jiaxing).

Production measures: Average Daily Milk yield^19,20 was calculated on the day of the visit to the farm by averaging the daily milk yield of the animals based on the data that were available.

Sampling Strategy

After the selection of indicators, evaluation was done in different animal husbandry setups (Gaushalas – cattle shelters; organized and unorganized farms) of cattle in Haryana, India in two different agro climatic zones (Northeastern zone and Southwestern zone)⁴⁴ over a period of one and half years i.e., from March, 2022 to August, 2023. Sampling was done randomly from at least two districts (Fig. 1) from each zone, representing different animal husbandry setups. The sample size (total number of animals considered for the study is 200 – 77 from gaushala (cattle shelters); 61 from organized farms and 62 from unorganized farms) was made with meticulous consideration of the total population, estimated at approximately 100,0000 animals, applying a 10% margin of error and a 99% confidence interval for sample size calculation using the Raosoft sample size calculator (http://www.raosoft.com/samplesize.html). A minimum of 30 animals were selected in each setup in each zone by a simple random sampling method. In Northeastern zone, total number of animals considered were 103 (43 from gaushalas (cattle shelters); 30 each from organized and unorganized farms) and in southwestern zone, total number of animals for the study were 97 (34 from gaushalas (cattle shelters); 31 each from organized and 32 from unorganized farms). Inclusion criteria include animals in the 2^nd to 6^th lactation and apparently healthy animals. Calves, bulls, steers and heifers were excluded from the study. The assessment for all the indicators had been done on the day of the visit to the farm or village, in particular animal husbandry setup, beginning at 09:00 hours in the morning.

Statistical analysis

Using statistical software SPSS 22 (SPSS version 22, SPSS Inc. Chicago, Illinois), the data gathered was collated, tabulated and systematically analyzed in accordance with the study's objective, following the steps outlined by Snedecor and Cochran⁴⁵. The statistical parameters listed below were used:

Mean
Standard error
Univariate/Multivariate One-way ANOVA; Duncan's multiple range test was used to compare means at significance levels of 0.01 and 0.05.
Principal Component Analysis (PCA) : PCA (multivariate statistical technique) reduces the amount of data from the interdependent variables to a more manageable group of variables⁴⁶. Using the fewest possible composite variables, PCA seeks to explain the greatest percentage of variance found in the initial collection of variables. In order to make it easier to interpret the results and place a smaller number of strongly correlated variables under each factor, factors were found using orthogonal rotation (varimax method)^47,48. Kaiser's criteria dictated that any factor with an eigen value greater than one was kept⁴⁷. Principal components were found using this strategy. At the 1% level of significance, the validity of the data set was determined using the Bartlett's test of sphericity and the Kaiser-Meyer-Olkin (KMO) test of sample adequacy.

Physical measures

The mean welfare score of BCS (2.89 ± 0.08); rumen fill score (2.80 ± 0.08) and faecal consistency (3.31 ± 0.09) of gaushala (cattle shelter) was found to be significantly lower than the organized and unorganized farms whereas mean welfare score of hock joint swelling (0.44 ± 0.04); dirtiness of the hind limbs, udder and flanks (2.26 ± 0.08); ectoparasitism (2.42 ± 0.07); skin lesions / integument alterations (1.41 ± 0.08) and teat and udder condition (1.81 ± 0.1) of gaushala (cattle shelter) was significantly higher than the other setups (Table 1).

Behavioural and production measures

Table 2showed that when different animal husbandry setups were compared, the mean welfare score of general temperament (0.63 ± 0.05); avoidance distance (1.41 ± 0.09); rising behavior (1.39 ± 0.04) and rising restrictions (0.19 ± 0.03) (p<0.01) were significantly higher in gaushala (cattle shelter) whereas average daily milk yield (5.29 ± 0.6) was significantly lower in gaushala (cattle shelter) as compared to organized and unorganized farms.

Physiological/Immunological measures

Haematobiochemical parameters

The mean value of haemoglobin (9.2 ± 0.20 g/dl); MCH (17.52 ± 0.23 pg); MCHC (31.14 ± 0.27 g/dl); platelet count (194.2 ± 10.32 ×10³/µL); SGPT (30.61 ± 1.43 U/L); ALP (111.24 ± 5.52 U/L); phosphorus (5.39 ± 0.11 mg/dl); calcium (8.95 ± 0.17 mg/dl) and total protein (7.35 ± 0.09 g/dl) of gaushala (cattle shelter) were significantly higher than other animal husbandry setups while mean value of PCV (32.75 ± 0.79 %); TEC (5.81 ± 0.15 ×10⁶/µL); CK (95.3 ± 6.54 U/L) and triglycerides (22.17 ± 1.7 mg/dl) were higher in unorganized farm (Table 3 & 4). No significant variation was seen in the levels of eosinophils; monocytes; MCV; LDH; SGOT and cholesterol when different setups were compared.

Glucocorticoid, catecholamine and acute phase proteins parameters

Fig. 2 displayed that in gaushala (cattle shelter), the mean levels of haptoglobin (243.77 ± 3.64 µg/ml); serum amyloid A (11.47 ± 0.16 µg/ml) and epinephrine (183.63 ± 12.71 ng/ml) were significantly higher than the organized and unorganized farms whereas the mean levels of C reactive protein (17.26 ± 0.38 ng/ml); albumin (2 ± 0.04 g/dl) and cortisol (27.43 ± 1.31 ng/ml) were significantly higher than the other 2 setups (p<0.01).

Principal Component Analysis (PCA)

A total of 27 welfare indicators with significant verdicts, including 6 indicators from physical measures; 2 from behavioural measures; 18 from physiological/immunological measures and 1 from production measures, were selected for principal component analysis. A score of 0.666 was achieved for the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO-MSA) (Table 5). The KMO-MSA less than 0.5 was not acceptable and in order to move forward with a successful factor analysis, the KMO-MSA must be more than 0.5⁴⁹. The percentage of variance in various welfare indicators resulting from the underlying components has been revealed by the estimate of sampling adequacy of KMO⁵⁰. Bartlett's test of sphericity was used to examine the overall significance of the correlation matrix for the welfare indicators. The results showed that the correlation was significant (p<0.01), as shown in table 5, which was sufficient to confirm the validity of the factor analysis of the data. Ten principal components (PCs) were identified from a total of 27 welfare indicators that were included in PCA by using the Kaiser Rule criterion⁵¹, as shown in table 6. The number of components was then determined by maintaining only those PCs with an eigen value greater than one. Additionally, a scree plot can be used to show the different components and determine how many should be included in the analysis; typically, components with eigen values up to the point of "bent of elbow" are considered (Fig. 3-4). A cumulative proportion of variance of 73.28 percent could be explained by the PCs that were found. 16.7 percent of the total variation was explained by the first PC, 27.855 percent by the first two PCs, 36.465 percent by the first three PCs, 44.165 percent by the first four PCs and 51.638 percent by the first five PCs. In other words, more than 50 percent of the total variance in 27 considered welfare indicators can be condensed into five new variables (PCs) (Table 6).

Ten PCs with factor loadings for variables that were produced using PCA are displayed in table 7. The total variance of each variable that was maintained in the factors is displayed in the communality column. Variables with high communality and high factor loadings were taken into consideration for the PC interpretation⁵². For the first PC, the most important variables were two physical measures (ectoparasitism, skin lesions / integument alterations); two behavioural measures (general temperament, avoidance distance) and two physiological/immunological measures (alkaline phosphatase, serum amyloid A) (Table 7). For the second PC, the most important variables were one physical measure (body condition score) and eight physiological/immunological measures (haemoglobin, packed cell volume, phosphorus, glucose, calcium, total protein, cholesterol and albumin) (Table 7). For the third PC, the most important variables were one physical measure (dirtiness of the hind limbs, udder and flanks) and four physiological/immunological measures (haptoglobin, fibrinogen, cortisol and C reactive protein) (Table 7). So, the comprehensive analysis (PCA) of various animal husbandry setups underscores the necessity to assess the health and welfare of animals through a systematic evaluation/scientific assessment protocol of 20 welfare indicators.

Recognizing the escalating significance of animal welfare within Veterinary Medicine since 1990, there has been a parallel rise in the need for reliable methodologies to assess the welfare of large animals. However, a standardized scientific protocol encompassing a diverse array of animal welfare indicators to evaluate the well-being of animals across various husbandry setups in Haryana state or India is currently absent.

The present study stated that organized farms tend to have higher BCS, rumen fill score and faecal consistency compared to gaushalas and unorganized farms. This could suggest better nutrition, management practices or regular deworming protocols in the organized farming setup. Similar findings were also reported by other authors^14,53. Another study which also reported similar findings that the BCS score is highest in large organized dairy farms²⁰. Shelter cows' slightly below-average BCS indicated certain nutritional deficiencies, which may have resulted from their reliance on substandard straw⁵⁴. It was also seen in the present study that the gaushala has a significantly higher level of ectoparasitism, dirtiness of the hind limbs, udder and flank and skin lesions / integument alterations than other setups, indicating that the use of both endo and ectoparasiticidal drugs is not practiced regularly in most cattle shelters and in contrast to this, there is a good and proper management system in other setups. One more study also reported that in shelters, cows' flanks, udder and rear limbs had mild to medium levels of dirtiness¹⁴. According to Chavhan et al. (2013), the prevalence of ectoparasites in cows kept in Indian shelters ranged from 77.2% to 84.8%, while Sharma et al. (2019) observed a 46.3% prevalence in cattle shelters^14,55. Tick infestation has been reported to be 45% common in gaushalas and unorganized dairy farms, but just 4% in the organized sector⁵⁶. In relation to teat and other conditions, gaushala has received a higher overall significant score than both unorganized and organized farms. The score variation falls between 1 and 2, which denotes a normal to dry udder and teats. Several workers have reported similar outcomes^14,53. Most of the cows in the gaushalas had dry teats and udders because they were not high milk yielders. To date, some rare cattle welfare methodologies have evaluated this parameter.

Current study depicted that animal in organized farm was more docile than gaushalas. This may be due to regular visitors visit in gaushala in spite of the proper and regular handling of the animals as well as regular induction of new animals in the herd. An animal's general temperament can be characterized as their reaction to social or environmental cues⁵⁷. There was a significant substantial fluctuation in the mean welfare score of avoidance distance and gaushalas mean score was significantly higher and it was in the range of 0 – 2. The majority of cows in all setups showed no fear of humans, indicating that the human-animal bond was positive in most shelters. These results demonstrated competent stockpersonship. The avoidance distance values found in this investigation were similar to those found in European dairy cattle and some Indian studies^14,24,53,58. Some workers reported that Bos taurus breeds were reported in certain investigations to be more docile than Bos indicus breeds therefore it is now well acknowledged that cow temperament has a genetic basis⁵⁹. Average milk yield of organized farm was considerably higher when different husbandry setups were compared. The results of this investigation align with those of other investigations^19,20,60. The relationship between milk production and animal welfare is complex; some experts in the field of animal welfare do not believe that milk yield is a useful metric for assessing the welfare of dairy cattle on-farm. On the other hand, increased productivity brought about by genetic selection or other management techniques may put dairy cattle in situation where high production is a sign of poor welfare⁴.

Haematological results showed that when various setups were compared, the level of haemoglobin and PCV in Gaushala was significantly higher than in organized and unorganized farms. The mean TEC level of an organized farm was much lower than that of an unorganized farm and gaushalas. Similar findings were published by a number of investigators^61,62. Significant reduction in platelet count (thrombocytopenia) detected in present study in organized and unorganized farm (mainly exotic breed) was in accordance with study of various authors^63,64. When the mean value of LDH was examined, no discernible variation was seen. Despite this, the LDH values in each setup were more than normal. The fact that ectoparasitism were there in most of the studied animals, could account for this higher value. Level of CK was significantly low in gaushalas as compared to other husbandry setups when compared. Researchers also observed higher level of CK and LDH value in anaplasmosis, theileriosis and babesiosis⁶⁵. These enzymes are markers of a higher degree of cellular damage and the inflammatory tissues' altered metabolism is reflected in their increased activity, which is a result of their increased release from the damaged cells⁶⁶. In the present study, low CK value in gaushalas may reflect better adoptability with minimal cytokine cascade in animals. ALP level of gaushala was significantly higher as compared to organized and unorganized farm. The findings were in agreement with those reported by Debbarma et al. (2020)⁶⁷. The level of calcium and total protein was significantly higher in gaushalas followed by unorganized and organized farm which was also reported by various researchers^62,67.

The mean value of haptoglobin and SAA as observed in the current study was significantly higher in gaushala followed by organized and unorganized farm. Numerous investigations have demonstrated the importance of haptoglobin and SAA as a clinically valuable metric for assessing the incidence and intensity of inflammatory reactions in cows suffering from endocarditis, pneumonia, enteritis, peritonitis, endometritis, haemoprotozoan infection and other experimental or natural infectious diseases^68,69,70. As seen in the present study, gaushalas had the higher mean value of ectoparasitism score, so, this could potentially be the reason for higher value of haptoglobin and SAA. Level of C reactive protein and cortisol as observed was lower in gaushala as compared to other setups. It is believed that CRP's plays role in the body innate immune system. Numerous investigations have demonstrated that the serum concentration of CRP rises in the early phases of infection and this increase occurs prior to the observation of a high rectal temperature and it has a correlation with herd health status⁷¹. A correlation was also found between milk output and the serum CRP level. The level of serum CRP rises with increased milk production. Several studies proposed that the levels of APPs in the blood plasma of dairy cows may be significantly influenced not only by inflammations but also by physiological variables including pregnancy, delivery and/or lactation stage^43,72. Considering to our research, presence of ectoparasitism and increased milk output stress may be the causes of higher CRP levels in both organized and unorganized farms. Stress is thought to be the most crucial element to regulate for the welfare of animals. The adrenal glands naturally create the hormone cortisol, which is released under stressful circumstances. Various workers reported that there is a positive correlation between blood cortisol concentration and stress level, which can also be found in cattle milk⁷³. Some studies reported increase in cortisol level in haemoprotozoan infection⁷⁴. In our study, gaushala exhibited a notably low level of cortisol despite having high mean value of ectoparasitism (a physical measure). As per one researcher, health issues rise due to high milk yield and leads to stress, that may be possible reason for high level of cortisol in organized and unorganized farm in addition of presence of ectoparasitism⁷⁵. Gaushala's average epinephrine level was noticeably greater than other setups. Various studies showed that compared to calm cattle, more agitated or temperamental cattle, have higher basal concentrations of adrenaline⁷⁶. Dopamine, norepinephrine and adrenaline - the three catecholamines - are crucial neurotransmitters of the sympathetic nervous system. The animals in gaushalas included in our study had significantly higher general temperament scores than those in the other two settings; this could be the cause of the greater levels of adrenaline in gaushalas.

One multivariate statistical method that deals with reducing a set of observable variables is PCA. PCA aims to use the fewest possible composite variables to explain the greatest percentage of variance that was initially present in the original set of variables⁴⁹. In the current study, KMO-MSA score of 0.666 was achieved. In contrast, various authors reported lower estimates of sample adequacy as 0.550 and 0.594, respectively, when PCA was applied to 20 welfare indicators in Dairy Cattle Welfare Score to examine the welfare and productivity of dairy cattle^19,20.

As observed in the present study, ten principal components (PCs) were identified from a total of 27 welfare indicators which showed cumulative proportion of variance of 73.28 percent with 20 welfare indicators fall in the first three components which include body condition score; ectoparasitism; skin lesions / integument alterations; dirtiness of the hind limbs, udder and flanks; general temperament; avoidance distance; haemoglobin; packed cell volume; phosphorus; glucose; calcium; total protein; cholesterol; alkaline phosphatase; Haptoglobin; serum amyloid A; fibrinogen; cortisol; albumin and C reactive protein as the important variables for scientific assessment of any animal husbandry setup in Haryana, India. Mahla (2018) extracted seven principal components out of 20 welfare indicators that were included in PCA to study the welfare of dairy cattle which showed 70.85 percent cumulative proportion of variance with storage space, feed availability, average productivity, feeding practice, body condition score and reproductive efficiency as the important variables for first PC²⁰. Kumar (2016) extracted six principal components which explained 83.34% of variation. However, there is a dearth of research on using principal component analysis to evaluate the welfare of dairy cows¹⁹.

The comprehensive analysis (PCA) of various animal husbandry setups underscores the necessity to assess the health and welfare of animals through a systematic evaluation/scientific assessment protocol of 20 welfare indicators which include four physical measures (body condition score, ectoparasitism, skin lesions / integument alterations and dirtiness of the hind limbs, udder and flanks); two behavioural measures (general temperament, avoidance distance) and fourteen physiological/immunological measures (haemoglobin, packed cell volume, phosphorus, glucose, calcium, total protein, cholesterol, alkaline phosphatase, Haptoglobin, serum amyloid A, fibrinogen, cortisol, albumin and C reactive protein). The inclusion of these diverse indicators provides a robust foundation for thorough and scientifically evaluating and monitoring the health and welfare of animals across different husbandry setups. Most preferable first six welfare indicators are ectoparasitism, skin lesions / integument alterations, general temperament, avoidance distance, alkaline phosphatase and serum amyloid A; second most preferable nine welfare indicators are body condition score, haemoglobin, packed cell volume, phosphorus, glucose, calcium, total protein, cholesterol and albumin and third most preferable five welfare indicators are dirtiness of the hind limbs, udder and flanks, haptoglobin, fibrinogen, cortisol and C reactive protein.

Data availability

The main data supporting the findings of this study are available within the article, its extended data figures, tables and supplementary information files (containing some of the study raw data). The datasets generated and analyzed during this study are not publicly available due to its novel nature as the first scientific assessment protocol for evaluating animal welfare in cattle in India. However, they can be obtained from the corresponding author upon reasonable request.

Acknowledgments

The authors express their sincere sense of gratitude to Worthy Vice Chancellor, LUVAS and Professor & Head, Department of Veterinary Medicine for providing research facilities and financial support.

Authors Contributions

Study commencement and design – AK, NS, TK, BRM & MS; Collection of 362 data – AK, P, BRM & SP; Data Analysis – AK, AM, MS & SG; Interpretation of data – AK, NS, TK, AM & AY; Manuscript preparation – AK, NS, TK & P.

Competing interest declaration

The authors confirm that they have no competing financial interests or personal relationships that could have influenced the work reported in this paper.

Additional information

Correspondence and requests for materials should be addressed to Ankit Kumar.

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Table 1: Mean welfare score of physical measures in different animal husbandry set ups in Haryana, India.

	Gaushala	Organized Farm	Unorganized Farm
Body Condition Score (BCS)**	2.89 ± 0.08^a	3.39 ± 0.09^b	3.29 ± 0.09^b
Lameness Score	1.13 ± 0.04	1.19 ± 0.05	1.11 ± 0.05
Claw Overgrowth	0.33 ± 0.06	0.34 ± 0.07	0.52 ± 0.07
Hock Joint Swellings**	0.44 ± 0.04^c	0.04 ± 0.05^a	0.19 ± 0.05^b
Dirtiness of the Hind limbs, Udder and Flanks**	2.26 ± 0.08^b	1.98 ± 0.09^a	1.77 ± 0.09^a
Ectoparasitism**	2.42 ± 0.07^b	1.44 ± 0.08 ^a	1.65 ± 0.08^a
Skin Lesions / Integument alterations**	1.41 ± 0.08^b	0.32 ± 0.09^a	0.57 ± 0.09^a
Teat and Udder Condition**	1.81 ± 0.1^b	1.37 ± 0.12^a	1.44 ± 0.12^a
Ocular Lesions*	0.02 ± 0.03^a	0.14 ± 0.03^b	0.14 ± 0.03^b
Nasal Discharge**	0.39 ± 0.05^b	0.13 ± 0.05^a	0.29 ± 0.05^b
Hampered Respiration	0 ± 0	0 ± 0	0.03 ± 0.01
Vulvar Discharge	0 ± 0	0 ± 0	0.03 ± 0.01
Rumen Fill Score**	2.80 ± 0.08^a	3.19 ± 0.09^b	3.14 ± 0.09^b
Faecal Consistency*	3.31 ± 0.09^a	3.63 ± 0.1^b	3.59 ± 0.1^ab

*p<0.05, Highly Significant at 5%; **p<0.01, Highly Significant at 1%

Table 2: Mean welfare score of behavioural and production measures in different animal husbandry set ups in Haryana, India.

	Gaushala	Organized Farm	Unorganized Farm
General Temperament**	0.63 ± 0.05^c	0.21 ± 0.06^a	0.41 ± 0.06^b
Avoidance Distance (AD)**	1.41 ± 0.09^b	0.93 ± 0.1^a	1.21 ± 0.1^b
Rising Behavior**	1.39 ± 0.04^b	1 ± 0.04^a	1.01 ± 0.04^a
Rising Restrictions**	0.19 ± 0.03^b	0 + 0^a	0.03 ± 0.03^a
Average Daily Milk Yield**	5.29 ± 0.6^a	18.23 ± 0.67^c	11.48 ± 0.6^b

*p<0.05, Highly Significant at 5%; **p<0.01, Highly Significant at 1%

Table 3: Mean value of haematological parameters in different animal husbandry set ups in Haryana, India.

	Gaushala	Organized Farm	Unorganized Farm
Hb (g/dl)**	9.2 ± 0.20^b	8.08 ± 0.22^a	9.18 ± 0.22^b
PCV (%)**	30.15 ± 0.70^a	29.06 ± 0.79^a	32.75 ± 0.79^b
TEC (×10⁶/µL)**	5.41 ± 0.14^ab	5.07 ± 0.15^a	5.81 ± 0.15^b
TLC (×10³/µL)**	8.13 ± 0.43^b	6.48 ± 0.48^a	6.53 ± 0.48^a
N (%)**	39.37 ± 1.56^a	49.18 ± 1.75^b	50.65 ± 1.75^b
L (%)**	57.46 ± 1.53^b	47.52 ± 1.72^a	45.75 ± 1.72^a
E (%)	1.35 ± 0.12	1.31 ± 0.14	1.70 ± 0.14
M (%)	1.8 ± 0.2	1.95 ± 0.23	1.86 ± 0.23
MCH (pg)**	17.52 ± 0.23^b	16.04 ± 0.26^a	16.73 ± 0.26^a
MCV (fl)	56.61 ± 0.8	58.76 ± 0.9	58.77 ± 0.9
MCHC (g/dl)**	31.14 ± 0.27^c	27.38 ± 0.3^a	28.34 ± 0.3^b
Platelet Count (×10³/µL) *	194.2 ± 10.32^b	177.5 ± 11.5^ab	151.7 ± 11.5^a

*p<0.05, Highly Significant at 5%; **p<0.01, Highly Significant at 1%

Hb: Haemoglobin, PCV: Packed Cell Volume, TEC: Total Erythrocyte Count, TLC: Total Leukocyte Count, N: Neutrophils, L: Lymphocytes, E: Eosinophils, M: Monocytes, MCH: Mean Corpuscular Haemoglobin, MCV: Mean Corpuscular Volume, MCHC: Mean Corpuscular Haemoglobin Concentration

Table 4: Mean value of biochemical parameters in different animal husbandry set ups in Haryana, India

	Gaushala	Organized Farm	Unorganized Farm
LDH (U/L)	769.4 ± 17.1	728.8 ± 19.3	769.4 ± 19.3
SGPT (U/L)**	30.61 ± 1.43^b	24.38 ± 1.61^a	26.75 ± 1.61^ab
SGOT (U/L)	68.27 ± 2.14	65.09 ± 2.41	61.7 ± 2.41
ALP (U/L)**	111.24 ± 5.52^c	52.14 ± 6.2^a	85.54 ± 6.2^b
GGT (U/L)**	17.17 ± 1.16^a	23.6 ± 1.3^b	19.61 ± 1.3^a
CK (U/L)**	39.62 ± 6.05^a	93.7 ± 6.8^b	95.3 ± 6.54^b
P (mg/dl)*	5.39 ± 0.11^a	5.06 ± 0.12^b	5.23 ± 0.1^a
Blood Urea (mg/dl)**	17.86 ± 0.99^a	20.69 ± 1.12^ab	23.52 ± 1.1^b
Serum Creatinine (mg/dl)**	1.53 ± 0.15^b	0.69 ± 0.1^a	1.07 ± 0.17^ab
Blood Glucose (mg/dl)	51.09 ± 1.6	49.3 ± 1.79	48.37 ± 1.7
Triglycerides (mg/dl)**	19.9 ± 1.61^b	13.25 ± 1.81^a	22.17 ± 1.7^b
Calcium (mg/dl)**	8.95 ± 0.17^b	7.45 ± 0.14^a	7.86 ± 0.19^a
TP (g/dl)**	7.35 ± 0.09^a	7.31 ± 0.1^a	6.7 ± 0.17^b
Mg (mg/dl)**	2.06 ± 0.1^c	1.46 ± 0.11^b	1.02 ± 0.1^a
Cholesterol (mg/dl)	133.81 ± 6.38	143.18 ± 7.17	138.27 ± 7.1

*p<0.05, Highly Significant at 5%; **p<0.01, Highly Significant at 1%

Table 5: KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.666
Bartlett's Test of Sphericity	Approx. Chi-Square	2335.674
	df	351
	Sig.	.000

Table 6: Principal component analysis results and total variance explained by various components

Component	Initial Eigen values			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings
Component	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	4.509	16.700	16.700	4.509	16.700	16.700	2.949	10.921	10.921
2	3.012	11.154	27.855	3.012	11.154	27.855	2.304	8.534	19.454
3	2.325	8.611	36.465	2.325	8.611	36.465	2.302	8.527	27.981
4	2.079	7.699	44.165	2.079	7.699	44.165	2.170	8.035	36.016
5	2.018	7.473	51.638	2.018	7.473	51.638	2.074	7.683	43.699
6	1.350	4.999	56.636	1.350	4.999	56.636	2.043	7.567	51.266
7	1.177	4.359	60.996	1.177	4.359	60.996	1.868	6.918	58.185
8	1.159	4.291	65.287	1.159	4.291	65.287	1.555	5.759	63.944
9	1.112	4.118	69.405	1.112	4.118	69.405	1.313	4.861	68.806
10	1.046	3.875	73.280	1.046	3.875	73.280	1.208	4.474	73.280
11	.908	3.362	76.642
12	.774	2.868	79.510
13	.696	2.578	82.088
14	.613	2.272	84.361
15	.585	2.166	86.526
16	.533	1.974	88.500
17	.505	1.871	90.372
18	.423	1.568	91.940
19	.404	1.496	93.436
20	.345	1.279	94.715
21	.330	1.221	95.936
22	.250	.927	96.863
23	.244	.903	97.766
24	.227	.842	98.608
25	.213	.789	99.397
26	.118	.438	99.835
27	.045	.165	100.000

Table 7: Ten PCs with factor loadings for variables were created using PCA (27 indicators)

Indicators	Principal Components										Comm unality
Indicators	1	2	3	4	5	6	7	8	9	10	Comm unality
Body condition score	-.480	.390	-.112	-.161	-.021	-.053	.117	-.284	-.409	.253	.749
Lameness score	-.044	.043	.084	.094	.295	-.216	-.152	.085	.086	.766	.778
Dirtiness of the hind limbs, udder and flanks	.324	-.275	.413	.228	.152	.024	.070	.088	.203	.154	.504
Ectoparasitism	.654	-.218	.236	.213	.313	-.079	.015	-.105	-.038	.068	.698
Skin lesions / Integument alterations	.627	-.197	.429	.018	.176	.087	.030	-.032	-.001	.179	.689
Rumen Fill Score	-.451	.331	.106	-.250	-.052	.036	.420	-.224	-.340	.228	.784
General temperament	.589	.087	-.179	-.235	-.062	-.491	.322	.249	-.043	-.012	.854
Avoidance distance	.487	.105	-.012	-.386	-.048	-.497	.341	.288	.021	-.070	.851
Milk yield (L/day)	-.731	.118	.040	.201	.000	-.100	.209	-.025	.161	-.005	.670
Hb	.199	.478	.040	-.654	.363	.274	-.171	.043	.082	.016	.943
PCV	-.032	.410	.083	-.691	.391	.258	-.169	.142	.164	-.011	.948
TLC	.218	.063	-.224	.223	.441	.347	.358	-.201	.151	-.098	.667
SGOT	.042	.100	-.049	.372	.222	.300	.076	.583	-.308	-.085	.740
ALP	.521	.193	-.049	.053	.325	.083	.003	-.034	-.246	-.150	.510
CK	-.476	.178	.093	.304	.459	-.104	.111	.259	.030	.009	.662
P	.180	.588	.042	.131	.005	.102	.453	-.012	.129	-.106	.640
Glucose	.107	.477	-.144	.037	-.486	.077	-.234	.356	.069	.109	.701
Ca	.497	.635	.077	.266	.171	-.058	-.087	-.157	-.159	.010	.817
Alb	-.157	.629	.094	.067	-.061	-.291	-.115	-.058	.449	-.046	.742
TP	.156	.454	-.171	.395	-.266	.248	.100	.181	.084	.330	.706
Cholesterol	-.024	.564	.157	.322	-.274	-.002	-.158	-.046	-.028	-.224	.600
Cortisol	-.057	.180	.779	.077	.020	-.153	.015	-.084	.012	-.136	.699
Epinephrine	.319	-.020	-.250	.002	-.139	.179	.235	-.283	.490	.096	.601
Hp	-.063	-.220	.436	-.243	-.444	.397	.273	.213	.036	.107	.789
SAA	.689	-.045	.121	-.125	-.511	.182	.028	-.089	-.124	.092	.834
CRP	-.719	-.237	.266	-.131	.116	.065	.203	.223	.149	-.046	.794
Fbg	-.034	.197	.861	.007	-.134	-.003	-.046	-.070	-.060	-.063	.814

No competing interests reported.

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First scientific assessment protocol to assess animal welfare in cattle: a novel study from India

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