This study was carried out for prediction of body weights in Nellore brown sheep by using statistical methods. The sheep were divided into four age groups based on the number of permanent teeth emerged out. Data on body weights and body measurements were collected from 897 Nellore brown sheep from five divisions of Kadapa district in Andhra Pradesh. Body weights and body measurements were significantly affected by the divisions. The male lambs were significantly heavier than females at all stages of growth. Body weight was found to be phenotypically highly positively correlated with height at withers (WH), chest girth (CG), paunch girth (PG), hip width (HW) and body length (BL). Simple regression and multiple regression analysis to predict body weight was carried out at all age groups. It is concluded that body weight could be predicted by statistical methods using several body measurements in Nellore brown sheep.
Kadapa district of Andhra Pradesh possess 15.04 lakhs of sheep population (Socio Economic Survey, 2014-15) which is characterized by tropical wet and dry climate and high temperatures throughout the year. In these climatic conditions majority of the farmers are engaged in animal husbandry, as crop production is not economical. Sheep and goats constitute a good source of family income and livelihood for smallholder farmers (Salem-Ben and Smith 2008; Shittu et al., 2008). Sheep are well adapted to critical climatic conditions even in inadequate water and fodder availability conditions. During the periods of unpredictable food shortage, sheep have proven very useful to human beings in the supply of meat and meat products (Gatenby, 2002; Iyayi et al.,2004). Besides short generation time (gestation period) and high growth rate, sheep are generally known to have high production efficiency. Biometric measurements provide an important evidence for the growth of the farm animal. Live weight plays an important role in determining several characteristics of the farm animals especially the ones having economical importance. Birth weight, early growth rate, feed conversion ratio as well as feeding requirements could be predicted by knowing the live weight at different stages and ages (Eker and Yavuz, 1960). Estimating the live weight using body measurements is practical, faster, easier and cheaper in the rural areas where the sources are insufficient for measuring direct weight (Nsoso et al., 2003). Hence the present study was aimed at predicting the body weights using various biometrical measurements and to examine the relationship between body weight and body measurements which is important in determining their market value.
Materials and Methods
A multistage cluster sampling was employed to select the animals from different shepherds in different divisions of Kadapa district of Andhra Pradesh in the year 2016. The district was divided into five divisions namely Kadapa, Jammalamadugu, Rajampeta, Rayachoti and Pulivendula for administration purpose. Out of 51 mandals available in the district, 15 mandals (29.4%) were selected randomly. From each division three mandals, from each mandal three villages and from each village three farmers were selected randomly. The data on body weights and body measurements were recorded on 897 Nellore brown sheep belonging to 5 divisions.
Linear body measurements were taken by a measuring tape and body weight was recorded using a spring balance, while the animals were motionless. Since the particulars of date of birth of the animals were not available in the field conditions, the eruption of permanent incisor teeth was taken as an indication of the age. The animals having 2, 4, 6 and 8 permanent incisor teeth were regarded as 1, 2, 3 and 4 years old, respectively (Banerjee, 1998). The body measurements were recorded as described by Narasimham et al. (2003) viz., height at withers as the distance from the base of hoof of foreleg to the highest point of withers, chest girth as circumference around the chest behind the elbow joint, paunch girth as body circumference in front of the sacrum, hip width as distance from the tuberosity prominence of ilium bone of one side to the other across the rump and body length as distance from the point of shoulder to the point of tuber ischii. The data on various body measurements were grouped according to the division and sex and were subjected to least-squares analysis (Harvey, 1987) to study the influence of division and the effect of sex on biometrical measurements using the following statistical model-
Yijk = μ + Di + Sj + ejjk
Yijk = the measurement on kth animal belonging to jth sex and ith division.
μ = overall mean
Di = effect of ith division (i = 1 to 5. i.e., 1. Kadapa; 2.Jammalamadugu; 3.Rajampeta; 4.Rayachoti; 5.Pulivendula)
Effect of jth sex (j=1 for male and 2 for female)
ejjl = random error
SPSS-20 program designed for windows was used for the statistical analysis. Relationship among body measurements were calculated by Pearson’s correlations and regression equations were established.
Results and Discussion
The least squares means along with standard errors related to body weights and body measurements at different ages according to their permanent teeth number are presented in Table1.
Table 1: Least squares means of body weights (kg) and biometric measurements (cms) of Nellore brown sheep
|Sample Size (n)|
|Jammalamadugu||152||30.35±0.59a||35.85±0.52 NS||34.25±0.61 NS||35.67±0.60a|
|Rajampeta||211||30.38±0.58a||36.01±0.51 NS||35.58±0.56 NS||36.75±0.59b|
|Rayachoti||143||30.72±0.61a||34.93±0.56 NS||34.32±0.64 NS||34.73±0.65a|
|Pulivendula||167||29.67±0.65b||35.79±0.57 NS||35.59±0.62 NS||36.05±0.64b|
|Height at Withers|
|Overall||76.81±0.31||82.63±0.39 NS||82.61±0.32 NS||83.74±0.25|
|Kadapa||224||77.72±0.65a||83.39±0.57 NS||82.44±0.67 NS||83.75±0.69ab|
|Jammalamadugu||152||76.94±0.77a||82.63±0.68 NS||83.00±0.79 NS||85.06±0.79a|
|Rajampeta||211||76.41±0.77a||82.77±0.68 NS||82.94±0.75 NS||83.22±0.79b|
|Rayachoti||143||77.16±0.68a||81.79±0.63 NS||81.34±0.71 NS||82.47±0.72b|
|Pulivendula||167||75.82±0.85b||82.56±0.75 NS||83.31±0.82 NS||84.18±0.84a|
|Kadapa||224||66.95±0.60ab||72.34±0.54 NS||70.94±0.64ab||72.66±0.64 NS|
|Jammalamadugu||152||65.35±0.83b||71.95±0.73 NS||69.88±0.85b||73.54±0.84 NS|
|Rajampeta||211||66.79±0.71ab||71.11±0.63 NS||71.85±0.69a||73.56±0.73 NS|
|Rayachoti||143||68.29±0.70a||71.81±0.65 NS||71.62±0.73ab||72.63±0.74 NS|
|Pulivendula||167||65.8±0.75b||70.66±0.66 NS||70.95±0.72ab||72.59±0.59 NS|
Means with different superscripts differ significantly between divisions (P≤0.05)
Division had significant effect on body weight at 2-teeth and 8-teeth age, height at withers at 2, 4, 8-teeth age , chest girth at 2, 6, 8-teeth age, paunch girth at 2, 8-teeth age and body length at 2, 6-teeth age whereas hip width was influenced at all ages studied. This revealed that the variation in environmental conditions, feeding and management of the sheep in the divisions under this study differed significantly. The highest body weights were noticed in the sheep belonging to Kadapa and Rajampeta divisions at different ages indicating that the better grazing and management practices were adapted by the farmers in these divisions. The overall mean height at withers, chest girth, paunch girth, hip width and body length of the animals at 8-teeth age were higher compared with measurements at 2-teeth age. This is an indication of increased skeletal and muscular growth of the animals with increase in age. The mean body measurements obtained in the present study were similar to those reported by Rani et al., 2014.
Least squares means of body weights (kg) and biometric measurements (cms) sex wise are shown in Table 2. Sex had significant effect on body weight and body measurements at all ages. In general, the mean value of body weight is significantly higher in males (43.59±0.36 at 4T) as compared to females (33.79±0.16 at 8T). Similar significant differences between sexes were reported by Jalajakshi et al., 2017. The overall mean height at withers in males was 84.12±0.99 and in females 75.58±0.11. The chest girth in males was recorded as 85.01±1.12 and 75.05±0.13 in females where as the paunch girth was 86.40±1.36 and 80.60±0.14 respectively. The overall hip width was 22.27±0.29 and 20.19±0.04, whereas the overall body length was 78.17±0.98 and 69.63±0.13 in males and females, respectively.
Table 2: Least squares means of body weights (kg) and biometric measurements (cms) of male and female Nellore brown sheep at different ages
|Age||Body weight||Height at withers||Heart girth||Paunch girth||Hip width||Body length|
|Height at withers||1||0.737**||0.637**||0.642**||0.833**|
|Height at withers||1||0.825**||0.745**||0.751**||0.900**|
|6 Teeth||Body weight||1||0.757**||0.564**||0.607**||0.470**||0.657**|
|Height at withers||1||0.697**||0.622**||0.470**||0.817**|
|8 Teeth||Body weight||1||0.611**||0.387*||0.539**||0.508**||0.455**|
|Height at withers||1||0.558**||0.458**||0.411**||0.682**|
(* P≤0.05; **: P≤0.01)
The phenotypic correlations between the body weights and body measurements at various ages are presented in Table 3 which revealed that all the estimates were positive, high and statistically significant. This was in agreement with the findings of Sreenivasu et al., 2003 in Deccani ewes. The correlation coefficients between the live weight and body measurements viz., withers height, chest girth, paunch girth, hip width, body length were ranged as 0.785, 0.671, 0.695, 0.709, 0.735 for the animals of 2-teeth age group, whereas the same parameters ranged as 0.870, 0.806, 0.777, 0.779, 0.833 for 4-teeth age group. At 6-teeth age group, the values were 0.757, 0.564, 0.607, 0.470, 0.657 and at 8-teeth age group, the values were 0.611, 0.387, 0.539, 0.508, 0.455 respectively. Of all the measurements the magnitude of correlation is highest between body weight and height at withers at all age groups which means that body weight could be estimated accurately using the height at withers parameter. The significant association between body weights and body measurements in the present study indicated that these traits were influenced by the same set of genes and selection for higher body measurements would automatically result in higher body weights and also other body measurements in the same direction as correlated response to selection.
Table 3: Correlation coefficients between the body weights and measurements of Nellore brown sheep
|Sample Size (n)||Overall||2T||4T||6T||8T|
|Male||97||42.01±0.81||38.35±0.83a||43.59±0.36 a||43.58±0.86 a||42.50±2.99 a|
|Female||800||33.28±0.08||29.96±0.16b||32.89±0.16 b||34.49±0.16 b||35.79±0.16 b|
|Height at Withers|
|Male||97||84.68±0.99||81.31±1.02 a||85.59±0.44 a||85.85±1.06 a||86.00±3.67 a|
|Female||800||75.58±0.11||71.51±0.23 b||75.23±0.23 b||76.7±0.23 b||78.87±0.23 b|
|Male||97||85.75±1.12||82.96±1.15 a||86.48±0.49 a||86.58±1.19 a||87.00±4.14 a|
|Female||800||77.05±0.13||73.39±0.26 b||76.33±0.26 b||78.43±0.26 b||80.07±0.26 b|
|Male||97||88.40±1.36||84.23±1.39 a||88.35±0.59 a||89.04±1.45 a||92.00±5.03 a|
|Female||800||80.59±0.14||76.37±0.28 b||80.01±0.28 b||82.27±0.28 b||83.74±0.28 b|
|Male||97||22.02±0.29||21.54±0.30 a||21.84±0.13 a||22.00±0.37 a||22.71±1.09 a|
|Female||800||20.19±0.04||18.61±0.08 b||19.87±0.08 b||20.77±0.08 b||21.51±0.08 b|
|Male||97||78.90±0.98||76.85±1.01 a||79.08±0.43 a||79.75±1.05 a||79.95±3.65 a|
|Female||800||69.63±0.13||66.00±0.26 b||68.94±0.26 b||70.59±0.26 b||72.99±0.26 b|
The Regression Equation for the 2-Teeth Age Group was established as
Bwt = -10.579 + 0.569*WH; R2 = 0.616. When height at withers and chest girth were considered together, the coefficient of determination increased to 63.4 per cent and the equation was changed to Bwt = -12.952 + 0.461*HW+0.137*CG; R2 = 0.634. When paunch girth was included in the equation, the coefficient of determination increased to 68.3 per cent; Bwt = -16.819 + 0.444*HW – 0.069*CG + 0.266*PG; R2 = 0.683. When hip width was included in the equation, the coefficient of determination increased to Bwt = -1.4808 + 0.373*HW – 0.068*CG + 0.193*PG + 0.564*HW; R2 = 0.714. When five different measurements were used in the equation, the equation established as Bwt = -16.103 + 0.315*HW – 0.08*CG + 0.187*PG + 0.536*HW + 0.079*BL; R2 = 0.719.
For the 4-Teeth Age Group, the Regression Equation was established as
Bwt = -28.267 + 0.820*HW; R2 = 0.757. When height at withers and chest girth were considered together, the coefficient of determination increased to 78.1 per cent and the equation was changed to Bwt = -31.099 + 0.606*HW + 0.247*CG; R2 = 0.781. When paunch girth was included in the equation, the coefficient of determination increased to 79.5 per cent; Bwt = -32.831 + 0.598*HW + 0.051*CG + 0.216*PG; R2 = 0.795. When hip width was included in the equation, the coefficient of determination increased to Bwt = -32.980 + 0.507*HW + 0.028*CG + 0.168*PG + 0.629*HW; R2 = 0.812. When five different measurements were used in the equation, the equation established as Bwt = 32.956 + 0.387*HW + 0.017*CG + 0.163*PG + 0.595*HW + 0.156*BL; R2 = 0.817.
The Regression Equation for the 6-Teeth Age Group, was Established as
Bwt = -13.954 + 0.634*HW; R2 = 0.572. When height at withers, chest girth and paunch girth were considered together, the coefficient of determination increased to 61 per cent and the equation was changed to Bwt = -17.164 + 0.560*HW – 0.119*CG + 0.221*PG; R2 = 0.610. When five different measurements were used in the equation, the equation established as Bwt = -18.365 + 0.490*HW – 0.129*CG + 0.203*PG + 0.236*HW + 0.059*BL; R2 = 0.621.
The Regression Equation for the 8-Teeth Age Group, was Established as
Bwt = – 4.265 + 0.508*HW; R2 = 0.373. When height at withers, chest girth and paunch girth were considered together, the coefficient of determination increased to 48.5 per cent and the equation was changed to Bwt = -13.106 + 0.445*HW – 0.184*CG + 0.341*PG; R2 = 0.485. When five different measurements were used in the equation, the equation established as Bwt = – 17.199 + 0.361*HW – 0.185*CG + 0.277*PG + 0.544*HW + 0.06*BL; R2 = 0.518. In general it was observed that the regression coefficients were higher for chest girth and body length to predict the body weight in the established regression equations. These results are similar with the findings of Atta and El Khidir, 2004. It was concluded that irrespective of division, prediction of body weight is more precise at 4T (0.817) age followed by 2T (0.719), 6T (0.621) and 8T (0.518) age consisting of all body measurements.