Indian Journal of Animal Research

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Indian Journal of Animal Research, volume 56 issue 1 (january 2022) : 109-115

Morphological Standard of Murrah Buffalo of India based on Multivariate Analysis of the Phenotypic Traits

Dinesh Kumar Yadav1,*, Ramesh Kumar Vijh1
1ICAR-National Bureau of Animal Genetic Resources, Karnal-132 001, Haryana, India.
Cite article:- Yadav Kumar Dinesh, Vijh Kumar Ramesh (2022). Morphological Standard of Murrah Buffalo of India based on Multivariate Analysis of the Phenotypic Traits . Indian Journal of Animal Research. 56(1): 109-115. doi: 10.18805/IJAR.B-4313.
Background: Morphometric measurements are important for the characterization of farm animal breeds and have become very useful in determining their morphological standards. Identification of animals based on breed standards are important for breed improvement and conservation programmes. Murrah, India’s world famous buffalo breed, is the highest milk producer and improver breed. Prevalence of Murrah grades in the vicinity of breeding tract of the Murrah warrants their differentiation. The objective of this study was to define the morphological standard of the Murrah buffalo and differentiate it from the Murrah grades. 

Methods: Fourteen body biometric traits of 258 she buffaloes were recorded from the core and peripheral breeding tract of the breed. In order to separate the animals into two groups, data were subjected to cluster analysis. Principal component analysis (PCA) and discriminant analysis were used respectively to describe the body conformation and identify the combination of independent traits that distinguished Murrah from grade Murrah.

Result: Our study showed significant differences between the traits of Murrah and grade Murrah (p<0.05). The grade Murrah she buffaloes were smaller than the Murrah counterparts. PCA results showed that five factors explained 67.4% of total variance of studied morphometric traits in Murrah she buffaloes, whereas in Grade Murrah six components explained 72.7% of the total variance. The stepwise discriminant function derived with eight body biometric traits was able to discriminate Murrah and grade Murrah she buffaloes effectively. A total of 93.5% original grouped animals were classified correctly. The present work determines the morphometric standard of the Murrah buffalo through characterization and identification of latent factors of morphometric traits. Subsequent use of this information in marketing, breeding, management and conservation purposes can give significant productivity gains. 
Multivariate analysis studies the interrelationships among more than two variables. It provides a suite of tools for describing and quantifying the relationship between multiple measured variables (Morrison, 1976; Johnson and Wichern, 2007). The main objective of multivariate analysis is simplification making interpretation easier. Cluster, discriminant and principal component analysis, the multivariate analysis techniques, have been widely used in breed characterization and genetic diversity studies (Legaz et al., 2011; Yakubu et al., 2011; Yunusa, 2013; Yadav et al., 2013, 2017). Cluster analysis finds similar groups of individuals, or organize the individuals into groups based on their similarity. Discriminant analysis is used in situations where the clusters are known a priori, aiming to classify an observation or several observations, into already known groups (Hardel and Simar, 2007). Principal components, a data reduction technique, according to Johnson and Wichern (2007), are linear combinations of the original variables and are estimated in such a way that the first principal component explains the largest percentage of the total phenotypic variance. Characterization through the use of classical multivariate methods such as principal component analysis and discriminant function analysis, in analyzing morphological traits to assess the variations between and within breeds, play major role in the maintenance of AnGR diversity.
Buffaloes in the Indian sub-continent are an integral part of traditional agriculture and hold the greatest promise and potential for food production (Cockrill, 1994). India is the goldmine of farm livestock resources. The world’s 57 percent buffalo population contributing 68 per cent of world buffalo milk production with its 16 registered breeds describe the spectrum of buffalo portfolio the country holds. Among the 16 well-defined breeds, based on their phenotypic characteristics, production performances and geographical distribution (, a world famous Murrah breed occupies prominent position being the highest milk producer and improver breed in India as well as abroad. The breed has spread over all parts of the country and is being bred either in pure form or is being used for grading up and substitution of local breeds (George et al., 1988; Sukla et al., 2006). The core home tract of Murrah is Haryana state. The native tract lies between 28o 15' and 30o North latitude and 75o 45' and 70o 80' East longitude (Sadana et al., 2006). The breed is aptly regarded as the ‘Black Gold’ or ‘Holstein-Friesian’ of the buffalo world in view of its global demand, higher milk production capacity, adaptation to different environmental conditions and feed conversion quality (Kumar et al., 2019).

Morphological characterization entails the description and documentation of the physical traits of a breed (Rege, 1992). It is the basis for differentiation of populations and/or breeds and provide support for breeding and conservation. Identification of true to breed Murrah animals is very important as the typical Murrah animals fetch a distinctively higher price in the market. Traditionally, the developmental agencies and farmers characterise Murrah on the basis of several morphometric characteristics (Nivsarkar et al., 2000; Sadana et al., 2006; As the Murrah breed is being used for grading up of non-descript buffaloes, sometimes distinguishing Murrah from Murrah grades, becomes cumbersome, especially when their morphometric standards are lacking. This study characterizes the morphometric traits of Murrah buffalo from the core breeding tract and compares it with the surrounding graded Murrah using multivariate analysis of the traits. The findings would lend objectivity in decision making for marketing, genetic and breeding purposes of Murrah buffalo.
Sampling and study area
Purposive sampling was done from core breeding tract having typical Murrah animals (Hisar, Bhiwani, Rohtak and Jhajjar districts of Haryana) and peripheral breeding tract having Murrah type or grade Murrah animals (Panipat, Karnal, Kurukshetra, Yamunanagar and Kaithal districts of Haryana). Data on Murrah bulls were recorded from semen stations of Haryana Livestock Development Board at Hisar, Gurugram and Jagadhari. The study was carried out at Indian Council of Agricultural Research-National Bureau of Animal Genetic Resources (ICAR-NBAGR), Karnal (Haryana), India during 2009-2013.
Morphometric traits
The measured morphometric traits were body length (BL), the distance from the point of the shoulder joint to the point of the pin bone; wither height (WH), the distance from the highest point of withers to the ground; chest girth (CG), the circumference of the chest just behind the elbow joint; paunch girth (PG), the circumference at paunch region just anterior to the hip joint; distance between hip bones (HBD); distance between pin bones (PBD); ear length (EL), distance from the point of attachment of ear to the tip of the ear; tail length (TL), distance from the root of tail droop to the tip of the tail excluding switch; tail whiteness (TW), whiteness of the tail from the distal end; horn length (HoL), external length of the horn; horn diameter (HoD), girth of the horn at base; horn curliness (HoC), chord distance between centre and base of the horn; head length (HL), distance between the tip of the skull to the tip of the nose and head width (HW), the distance between the left temple and the right temple.
Statistical analysis
Measurements (cm) of 258 she buffaloes and 93 Murrah bulls on 14 morphometric traits were taken with a measuring tape by same person to avoid inter-individual variations. For this data, we were interested in exploring whether the buffaloes from the core breeding tract and peripheral tract formed two distinct groups. Hierarchical cluster analysis using Ward distance metrics was performed to obtain two homogenous groups while discriminant function analysis was performed to ascertain the accuracy of the clustering. SAS and JMP Pro10 software of SAS were used in the analysis. Descriptive statistics for the morphometric traits of two groups were obtained. Means separation was done using Tukey’s HSD (p<0.05). Stepwise discriminant procedure was applied using PROC STEPDISC (SAS 9.3) to determine which morphological traits have more discriminant power than others. The relative importance of the morphometric variables in discriminating the Murrah from grade Murrah was assessed using the level of significance (p<0.05) and partial R2 values ≥0.01. The CANDISC procedure was used for calculating the Mahalanobis distances (Mahalanobis, 1936) of the morphological traits. The DISCRIM procedure was used to assign each individual animal to its group that included the eight morphometric traits. PCA with Varimax Kaiser Normalization method was used to describe the relationship between a large number of measured traits and a small number of unobserved factors. Kaiser criterion extracted the number of principal components (PCs). A variable was considered to be associated to a specific PC if the absolute value of its loading was ≥0.40. 
Table 1 shows mean (cm), standard errors and coefficient of variation of the morphometric characteristics of the Murrah and grade Murrah she buffaloes and Murrah bulls. Coefficient of variation of the traits in Murrah she buffalo ranged from 3% (HL) to 86.3% (TW).  A significant difference in the studied variables in Murrah and grade Murrah she buffaloes was observed (p<0.05), except for the TW and HW. Mean values of the studied traits were higher in Murrah than Grade Murrah. Similarly, a significant difference in the studied variables in Murrah she buffaloes and Murrah bulls was observed (p<0.05), except for the TW and CG. Horns in males were thicker than females as horn diameter was 29% higher in males. Also, horns were more tightly curved in males than females. Mean values of BL, CG, WH and TL of Murrah reported by Dhillod et al., (2017) are in agreement to the values of our study. Nivsarkar et al., (2000) reported lower mean values of WH and CG of Murrah as compared to our study. Mean values of WH and BL of Murrah in our study were similar to those reported by Rezende (2017). Mean values of WH, EL and PBD of Murrah were similar to Banni buffalo (Mishra et al., 2009); mean values of CG, HBD and TL of Murrah were higher than Banni buffalo whereas average values of HL, HW and BL were smaller. BL and WH of grade Murrah were similar to Bhadawari buffalo (Pundir et al., 1996). Similarly, the mean values of CG, PG, HL, HW, EL, HBD, PBD and TL of grade Murrah were similar to Gojri buffalo (Vohra et al., 2015). Our study as well as other reports indicate that a wide range of variation exists for different morphometric traits, however, extent of variation was specific to a trait.

Table 1: Mean±SE, CV and sexual dimorphism in Murrah she buffalo, Grade Murrah she buffalo and Murrah bulls.

The phenotypic correlations among various morphometric traits of Murrah and Grade Murrah she buffaloes are presented in Table 2, while those of Murrah bulls are given in Table 3. Most of the correlations between the assessed variables in Murrah she buffalo were significant and ranged from 0.16 to 0.68 except tail and horn combinations with other traits. Correlations above 0.50 were obtained for CG, PG, BL and WH (Table 2), related to animal size. Similar pattern of correlation between the assessed traits in Murrah bulls was observed, however, significant correlation values were slightly higher and ranged from 0.21 to 0.73 (Table 3). Some of the traits (ear, tail and horn) exhibited negative correlations with the other traits which were mostly non-significant. Correlation matrix indicates the degree of relationship between the two variables. Our results indicated that in Murrah she buffalo the trait CG was positively associated with PG (0.68), WH (0.50), EL (0.19) and HW (0.21). Murrah bulls showed higher positive correlations of BL with WH (0.73) followed by CG with PG (0.71), BL (0.41) and WH (0.41). Vohra et al., (2015) showed in Gojri buffalo that WH had significantly higher correlation with BL (0.72), HL (0.50) and CG (0.50). Significantly positive associations observed among different traits suggests that indirect measure of a trait can be estimated through the estimations of other correlated trait.

Table 2: Correlation between morphometric traits of Murrah she buffalo and Grade Murrah she buffalo.


Table 3: Correlation between morphometric traits of Murrah bulls.

Five PCs explained 67.4% of total variance of studied morphometric traits (Table 4) in Murrah she buffaloes, whereas in Grade Murrah six PCs explained 72.7% of the total variance (Table 5). The communalities found in Murrah she buffaloes ranged from 0.350 to 0.826. The communalities explain how much a particular trait contributes to explain the number of factors being considered (Morrison, 1976). The HoD trait showed lowest commonality, indicating that it contributed little towards explaining the total accumulated variation in the factors. In Murrah bulls, 4 PCs contributed to 62% of total variance of the studied traits, while the communalities varied from 0.352 to 0.793 (Table 6). In Murrah she buffaloes (Table 4), the first principal component contributed 18.6% of total variation and was represented by high loadings for PBD, CG and PG. The second component explained 18% of the total variance with high loading of HBD, BL, WH, EL and HL. These two components explained the general body conformation. The third component explained 12.7% of variance and showed high component loadings for horn characteristics (HoL, HoD and HoC). The fourth component explained 9.9% of the variance and showed high component loadings for tail characteristics (TL and TW). The fifth component explained 8.2% of variance and showed high component loading for HW. The traits that loaded highly onto first two PCs in Murrah loaded highly together onto PC1 in grade Murrah. The pattern of loading of traits in rest of the components in grade Murrah was different from Murrah (Table 4, 5). In Murrah bulls (Table 6), the first component explained 26% of the total variance with high loadings of seven traits (HBD, PBD, CG, PG, BL, WH and HW) explaining general body conformation of the bulls. Shahin et al., (1993) found three PCs explaining 88% of the variability while studying 13 body measurements in Egyptian buffalo bulls. Tolenkhomba et al., (2013) evaluating 18 biometric traits of bulls of local cattle of Manipur, India, reported that 69.77% of total variation was explained by six factors. Vohra et al., (2015), studying Gojri buffalo in India (based on 13 morphometric measurements), found four factors that explained 70.86% of the total variation. Yakubu et al., (2009) and Casanova et al., (2012) reported similar results in cattle. Murrah animals have distinguishable traits of horn, tail, body and forehead conformations and this knowledge is traditionally practiced by the local farmers to judge this breed. The factor loadings confirms this pattern. Our study also elucidates the structure of morphometric traits which were most useful for identification of Murrah animals. These factors could also be exploited in breeding and selection programmes to acquire highly coordinated animal bodies using fewer measurements (Yakubu et al., 2009).

Table 4: Eigen values, percentage of total variance, rotated factor loadings and communalities of morphometric traits of Murrah she buffalo.


Table 5: Eigen values, percentage of total variance, rotated factor loadings and communalities of morphometric traits of Grade Murrah she buffalo.


Table 6: Eigen values, percentage of total variance, rotated factor loadings and communalities of morphometric traits of Murrah bulls.

Table 7 shows the results of stepwise discriminant analysis. Based on F-values and Wilk’s lambda, eight traits were significant. These variables in the data set were found to have potential discriminatory power. CG had more discriminant power than the others traits followed by HL as indicated by their higher R2 and F-values. In the canonical discriminant analysis, the canonical variable (CAN1) generated was significant (p<0.0001) (Table 8). Mahalanobis distance between two buffalo groups and per cent (%) of individual classified into source group are given in Table 9. The Mahalanobis distance between Murrah and grade Murrah she buffaloes was 6.92 and was highly significant (p<0.0001). This was substantiated by the classification result. In Murrah, 92% animals were correctly assigned while the corresponding figure in grade Murrah was 97%. A very high percentage of the correct assignment of the animals in their respective classes suggests that the Murrah breed is clearly distinguishable based on its morphological characteristics. Similar results of discriminant analysis using ten morphological traits were reported by Yakubu et al., (2010) in the study of morphometric differentiation of two Nigerian cattle breeds. The authors reported that 96.55% of Sokoto Gudali cattle were classified into their source genetic group, while 85.48% Bunaji counterparts were correctly assigned into their source population. The eight morphological variables (CG, HL, PG, HoC, HBD,TL, HoD, TW) obtained in the present study are more important and informative and could be used to assign the animals into Murrah and grade Murrah populations, thereby reducing the errors of selection in future breeding and selection programmes.

Table 7: Stepwise selection summary of traits for differentiating Murrah and Graded Murrah she buffaloes.


Table 8: Pooled within class standardized canonical coefficients or the canonical discriminant function, the canonical correlation and the eigenvalue based on clustering.


Table 9: Mahalanobis distance between two buffalo groups and per cent (%) of individual classified into source group.

The study was aimed at clustering buffaloes, selected from core and peripheral breeding tract of Murrah buffalo breed of India, into Murrah and grade Murrah groups. Cluster analysis was successful in differentiating the two groups on the basis of morphological traits. The derived discriminant function provided maximum separation among the two groups with an overall classification rate of 93.4%. The study can therefore conclude that Murrah and grade Murrah buffaloes can be clearly separated based on the biometric traits with minimum rate of misclassification. The most discriminating trait was the CG. PCA was useful for identifying a set of 5 and 6 latent constructs to characterize the Murrah and grade Murrah buffalo respectively. The identified factors elucidate the socially perceived norms on identification of Murrah buffaloes in sale/purchase of animals. According to discriminant analysis CG, HL, PG, HoC, HBD, TL, HoD and TW characteristics were the most important for breed standard of Murrah. These results giving an overall information of morphometric traits of Murrah buffaloes and differentiating it from grade Murrah may well lead to exhaustive analysis of this breed in defining its morphometric standard which may serve as an objective criterion in identification of a Murrah buffalo. Characterization and identification of latent factors of morphometric traits and subsequent use of this information in marketing, breeding, management and conservation purposes may offer substantial gains in productivity.
The authors are thankful to the Director, ICAR-National Bureau of Animal Genetic Resources, Karnal for providing the necessary facilities. The financial assistance of Indian Council of Agricultural Research, New Delhi is also gratefully acknowledged. Technical support by Subhash Chander, Technical Officer is acknowledged. We are thankful to Director General and Deputy Directors, Department of Animal Husbandry and Dairying, Haryana for their support. The farmers who spared their valuable time and animals for the study are thankfully acknowledged.

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