Livestock Research for Rural Development 17 (7) 2005  Guidelines to authors  LRRD News  Citation of this paper 
Data on body weight and body measurements were individually collected from Kanni Adu kids (114 males and 214 females) from its breeding tract.
The correlation coefficients between body weights and body measurements at different ages were positive and strongly correlated (P<0.01). The correlation coefficient for different body measurements ranged between 0.506 and 0.968. Simple and multiple regression models were fitted with body weight as dependant variable and height at withers, chest girth and body length as independent variables. The coefficient of determination indicated that body measurements succeed to describe more variation in live weight. The chest girth accounted maximum of 80.4 to 93.6 per cent of total variation in body weight. The model constructed with pooled data from birth12 months of age was the best fitted multiple regression models with chest girth, body length and height at withers as an independent variables (R^{2} = 0.913, MS_{E} = 1.82 for males and R^{2} = 0.948, MS_{E} = 1.195 for females). In all age groups the highest R^{2} was obtained, if we include all the body measurements in the regression equation. This suggests that weight could be estimated more accurately by combination of two or more measurements. However, a study of different criteria revealed that model having a larger R^{2} with a smaller MS_{E} and SD_{E} produced a better goodness of fit.
It was concluded that the body weight of Kanni Adu kids could be estimated accurately in farmer's field condition using morphometric measurements taken with a tape.
Key words: body weight, correlation, Kanni Adu, prediction, regression
Goat rearing is of great importance in Indian households and plays major role for the sustenance of small and marginal farmers and landless agricultural labourers. Kanni Adu goats are found in the southern part of India especially in Tamil Nadu. They are valuable for meat and for their skin (Acharya 1982 and Thiruvenkadan et al 2000a 2000b). Measurements of various body conformations are of value in judging the quantity characteristics of meat and also helpful in developing suitable selection criteria (Bose and Basu 1984;Sarma et al 1984; Sharaby and Suleiman 1987; Islam et al 1991). Knowing the body weight of a goat is important for a number of reasons, related to breeding (selection), feeding and health care. However this fundamental knowledge is often unavailable to those working with goats in the small scale farming sector, due to unavailability of scales. Hence, farmers have to rely on questionable estimates of the body weight of their goats, leading to inaccuracies in decisionmaking and husbandry. The chief method of weighing animals without scales is to regress body weight on a certain number of body characteristics, which can be measured readily. Body measurements have been used to predict body weight by several authors in many breeds of Indian goats (Tandon 1965; Das et al 1990; Prasad et al 1990; Ulaganathan et al 1992; Singh and Mishra 2004), Sahel goats of Nigeria (Mohammed and Amin 1996; Slippers et al 2000), West African Dwarf goats (Mayaka et al 1995) and Nguni goats (Slippers et al 2000). Such procedures are almost non existent for Kanni Adu goats. Enevoldsen and Kristensen (1997) reported that different models might be needed to predict body weight in different environmental conditions and breeds. Hence, this study has been made to determine the best fitted regression model for prediction of live weight of Kanni Adu goats under field conditions and also to identify the criteria to be applied to investigate fitting state of simple and multiple models to actual data for estimation of body weight.
The study was carried out in Tamil Nadu in the southern part of India. The breed under study, is commonly known as Kanni Adu goats and a detailed description of it may be found elsewhere (Acharya 1982; Thiruvenkadan et al 2000a 2000b).
Data were collected from a total of 328 (114 males and 214 females) Kanni Adu goats in its breeding tract. Measurements recorded were live body weight, height at withers, body length and chest girth as per Sasimowski (1987) and as indicated in Photo 1.
Photo 1. A Kanni Adu goat showing the exact points at which the measurements were taken 
Within each group, weight was regressed on body measurements using least square by stepwise regression analysis (Harvey 1990) to determine the combination of body dimensions for each sex that explains variation in the dependent variable (Sharaby and Suleiman 1987). Separate prediction equations were developed for male and female kids. The comparison amongst actual body weight and predicted body weight was made by paired 't' test (Slippers et al 2000). In addition, the prediction bias was estimated using sample average (D_{i} = W_{i}  Ŵ_{i} (i = 1 to n), i.e. D_{i}  Proportion difference, W_{i}  Actual weight and Ŵ_{i}  Predicted weight) and standard deviation (Mayaka et al 1995). Pearson's correlation coefficients were estimated between body weight and all body measurements. To determine the best fitted regression equation the criteria viz., coefficient multiple determination (R^{2}), residual mean square (MS_{E}) of Snedecor and Cochran (1989) and error standard deviation (SD_{E}) and range observed in predicted weight were also used for evaluating and comparing different regressions models.
Means and standard errors of live weight and body measurements are presented in Table 1. In all the age groups, among the body measurements, height at withers was highest followed by chest girth and body length. Males had higher values than females of all the traits studied and they were not significantly different.
Table 1. Mean (± SE) body weight and body measurements of Kanni Adu kids 

Age group 
Sex 
Number of observations 
Height at withers, cm 
Chest girth, 
Body length, cm 
Body weight, 
03 months 
Male 
76 
46.7 ± 0.69^{a} 
40.4 ± 0.60^{ a} 
40.3 ± 0.28^{ a} 
6.4 ± 0.28^{ a} 
Female 
102 
45.3 ± 0.63^{ a} 
39.6 ± 0.64^{ a} 
39.5 ± 0.62^{ a} 
5.9 ± 0.28^{ a} 

Pooled 
178 
45.8 ± 0.47 [13.7] 
39.9 ± 0.45 [15.0] 
39.8 ± 0.44 [14.7] 
6.1 ± 0.20 [43.9] 

>36 months 
Male 
19 
58.1 ± 1.23^{ a} 
52.0 ± 1.26^{ a} 
49.8 ± 0.64^{ a} 
11.8 ± 0.64^{ a} 
Female 
49 
58.8 ± 0.64^{ a} 
51.8 ± 0.53^{ a} 
51.6 ± 0.32^{ a} 
12.1 ± 0.32^{ a} 

Pooled 
68 
58.6 ± 0.57 [8.2] 
51.8 ± 0.51 [8.1] 
51.1 ± 0.29 [4.7] 
12.0 ± 0.29 [19.9] 

>69 months 
Male 
13 
64.6 ±1.04^{ a} 
57.9 ± 1.40^{ a} 
56.3 ± 0.50^{ a} 
14.5 ± 0.50^{ a} 
Female 
26 
59.7 ± 0.71^{ a} 
54.3 ± 0.62^{ a} 
53.1 ± 0.30^{ a} 
13.2 ± 0.30^{ a} 

Pooled 
39 
61.3 ± 0.69 [7.0] 
55.5 ± 0.67 [7.5] 
54.1 ± 0.28 [3.2] 
13.7 ± 0.28 [12.8] 

>912 months 
Male 
6 
66.2 ± 2.81^{ a} 
59.7 ± 2.84^{ a} 
57.2 ± 1.27^{ a} 
18.0 ± 1.27^{ a} 
Female 
37 
65.4 ± 0.53^{ a} 
57.9 ± 0.61^{ a} 
57.2 ± 0.41^{ a} 
15.7 ± 0.34^{ a} 

Pooled 
43 
65.5 ± 0.59[5.9] 
58.2 ± 0.65 [7.3] 
57.2 ± 0.4 [4.6] 
16.0 ± 0.40 [16.4] 

Means bearing same superscript do not differ significantly between sexes 
The correlation coefficients between body weight and body measurements for males and females are presented in Table 2.
Table 2. Phenotypic correlation between body weight and body measurements in Kanni Adu kids 

Age group 
Sex 
Number of observations 
Height at withers 
Chest girth 
Body length 
0 – 3 months 
Male 
76 
0.865^{**} 
0.922^{**} 
0.885^{**} 
Female 
102 
0.939^{**} 
0.937^{**} 
0.920^{**} 

>3 – 6 months 
Male 
19 
0.766^{**} 
0.917^{**} 
0.951^{**} 
Female 
49 
0.774^{**} 
0.897^{**} 
0.758^{**} 

>6 – 9 months 
Male 
13 
0.672^{*} 
0.506^{NS} 
0.578^{ NS} 
Female 
26 
0.636^{**} 
0.623^{**} 
0.719^{**} 

>9 – 12 months 
Male 
6 
0.884^{*} 
0.580^{NS} 
0.671^{ NS} 
Female 
37 
0.568^{**} 
0.635^{**} 
0.783^{**} 

0 – 12 months 
Male 
114 
0.936^{**} 
0.944^{**} 
0.940^{**} 
Female 
214 
0.958^{**} 
0.968^{**} 
0.956^{**} 

NS – Non Significant * Significant (P<0.05) ** Highly Significant (P<0.01) 
Positive and highly significant (P<0.01) correlations were observed. The correlations coefficients observed in Kanni Adu kids was comparable to the reported values of Mukherjee et al 1981, 1986; Singh et al 1987; Das and Sharma 1994; Topal et al 2003 and Topal and Macit 2004. The high correlation coefficients between body weight and body measurements for all age groups suggest that either of these variables or their combination could provide a good estimate for predicting live weight of Kanni Adu kids. Among these three body measurements, chest girth had the highest correlation coefficient in males at 03 months and in females at >36 months and in both sexes at 012 month age groups. The body length had the highest correlation coefficient in males of >36 months and in females of >69 and >912 months. The height at withers had high correlation with body weight in males of >69 and >912 months and in females of 03 months age groups. This tends to infer that at different ages different conformational traits may be more successfully used for selection. The correlations between body weights and body measurements in pooled data from 012 months of age were higher than those at different age groups. This might be due to more or less similar environmental influence at different age groups. Looking at the values of the correlation coefficients, in general, females showed a higher tendency of relationship than that of male kids. This agrees to the report of Singh (1975). Since body measurements had high correlation with body weight, this may be used as selection criteria, Bhattacharya et al. (1984) and Bose and Basu (1984) also reported that selection based on body measurements should improve meat production in goats.
Table 3 details the regression output including the fitted functions and coefficient of determinations. It shows the seven final models for the estimation of body weight in each age groups of both sexes.
Table 3. Prediction equations and coefficient of determination (R^{2}) at different age groups in Kanni Adu kids 

Age group 
Male 
Female 

Equation 
R^{2} 
Equation 
R^{2} 

>0 – 3 Months 
Y= 28.33 + 0.4009 X1 + 0.3225 X2+ 0.0750 X3 
0.855 
Y= 12.23 + 0.1935 X1 + 0.1428 X2 + 0.0935X3 
0.909 
Y= 11.49 + 0.0567 X1 + 0.3765 X2 
0.852 
Y = 12.18 + 0.2236 X1 + 0.2005 X2 
0.905 

Y= 11.07 + 0.1508 X1 + 0.2587 X3 
0.810 
Y=  12.71 + 0.2714 X1 + 0.1592X3 
0.901 

Y= 11.43 + 0.3509 X2 + 0.0895 X3 
0.854 
Y=  10.72 + 0.2703 X2 + 0.1495 X3 
0.892 

Y= 10.18 + 0.3557 X1 
0.748 
Y=  13.06 + 0.4181 X1 
0.883 

Y= 11.27 + 0.4361 X2 
0.849 
Y=  10.23 + 0.4071 X2 
0.878 

Y= 10.19 + 0.4110 X3 
0.783 
Y= 10.35 + 0.4104 X3 
0.847 

>3 – 6 months 
Y=  12.49 + 0.0168 X1 + 0.4494 X2 + 0.0394 X3 
0.852 
Y= 17.60 + 0.0853 X1 + 0.4314 X2 + 0.0456 X3 
0.818 
Y= 12.51 +  0.0016 X1 + 0.4696 X2 
0.842 
Y= 17.24 + 0.0901 X1 + 0.4644 X2 
0.816 

Y= 11.39 + 0.3326 X1 + 0.0799 X3 
0.632 
Y= 15.64 + 0.2452 X1 + 0.2582 X3 
0.697 

Y= 12.73 + 0.4365 X2 + 0.0382 X3 
0.852 
Y= 16.84 + 0.5001 X2 + 0.0592 X3 
0.807 

Y= 11.32 + 0.3982 X1 
0.590 
Y= 11.14 + 0.3952 X1 
0.599 

Y=12.53 + 0.4682 X2 
0.842 
Y= 16.36 + 0.5498 X2 
0.804 

Y= 2.39 + 0.1929 X3 
0.334 
Y= 11.41 + 0.4555 X3 
0.575 

>6  9 months 
Y= 9.29 + 0.2462 X1 + 0.0494 X2 + 0.0901 X3 
0.522 
Y= 10.65 + 0.1076 X1 + 0.0897 X2 + 0.2374 X3 
0.580 
Y=  8.46+ 0.2699 X1+ 0.0962 X2 
0.510 
Y= 7.60 + 0.1775 X1 + 0.1884 X2 
0.507 

Y= 9.29 + 0.2459 X1+ 0.1412 X3 
0.515 
Y=  9.82 + 0.1219 X1 + 0.2974 X3 
0.563 

Y= 0.76 + 0.0476 X2 + 0.2231X3 
0.341 
Y= 11.09 + 0.1440 X2 + 0.3112 X3 
0.545 

Y=  6.46 + 0.3253 X1 
0.452 
Y= 2.91 + 0.2705 X1 
0.405 

Y= 3.99 + 0.1823 X2 
0.256 
Y=  3.22 + 0.3030 X2 
0.388 

Y=  0.77+ 0.2722 X3 
0.334 
Y= 8.17 + 0.4036 X3 
0.517 

>9– 12 months 
Y= 3.29 + 0.5457 X1 + 0.0266 X2 + 0.2746 X3 
0.817 
Y= 21.29 + 0.0531 X1 + 0.0746 X2 + 0.5108 X3 
0.624 
Y=7.59 + 0.4592 X1 + 0.0800 X2 
0.796 
Y= 15.86 + 0.2094 X1+ 0.3087X2 
0.447 

Y=  3.76 + 0.5430 X1 + 0.2370 X3 
0.817 
Y=  66.83+ 0.7749 X1+ 0.5577 X3 
0.619 

Y= 8.38 + 0.0414 X2 + 0.4840 X3 
0.452 
Y=19.98 + 0.0910 X2 + 0.5319 X3 
0.622 

Y=  8.38 + 0.3990 X1 
0.782 
Y=12.73+ 0.4351 X1 
0.323 

Y= 2.59 + 0.2589 X2 
0.336 
Y=  8.98 + 0.4260 X2 
0.403 

Y=  7.68 + 0.4309 X3 
0.450 
Y=  19.11 + 0.6089 X3 
0.613 

> 1 12 months 
Y= 14.28 + 0.1544 X1 + 0.2006 X2 + 0.1357 X3 
0.913 
Y= 14.71 + 0.1544 X1 + 0.2551 X2 0.0913 X3 
0.948 
Y=  13.84 + 0.1963 X1 + 0.2766 X2 
0.910 
Y=14.62 + 0.1805 X1 + 0.3144 X2 
0.946 

Y= 14.92 + 0.2136 X1 + 0.2854 X3 
0.903 
Y=15.12 + 0.2518 X1 + 0.2456 X3 
0.937 

Y= 13.75 + 0.2696 X2 + 0.2319 X3 
0.904 
Y=14.01 + 0.3497 X2 + 0.1573 X3 
0.941 

Y=  14.20 + 0.4466 X1 
0.876 
Y=15.15 + 0.4677 X1 
0.919 

Y= 12.51 + 0.4703 X2 
0.891 
Y=13.61 + 0.4975 X2 
0.936 

Y= 14.42 + 0.5210 X3 
0.883 
Y=13.95 + 0.5078 X3 
0.914 

X1 = Height at withers X2 = Chest girth X3 = Body length Y= Body weight 
The coefficient of determination (R^{2}) indicated that the body measurements succeed to describe more variation in live weight. The variation of body weight due to body measurements differed between sexes and age groups. Thus chest girth accounted maximum of 80.4 to 93.6 per cent of the total variation in body weight, together with ease of measurement, justifies the use of chest girth as a foremost weight predictor. The higher association of body weight with chest girth was possibly due to relatively larger contribution in body weight by chest girth (consisting of bones, muscles and viscera). It is in concert with findings of Mayaka et al 1995; Mohammed and Amin 1996; Benyi 1997; Myeni and Slippers 1997; Nesamvuni et al 2000; Slippers et al 2000; Topal et al 2003 and Topal and Macit 2004.
Using of chest girth was less reliable in predicting the body weight at >69 and >912 months age groups. In these age groups height at withers and body length accounted for the greatest amount of variation in body weight for males and females respectively. This result is similar to the report of Mukherjee et al 1981, 1983; Prasad et al1990 and Ulaganathan et al 1992. In general, the analysis of R^{2} at different age groups in both sexes revealed that a comparatively lower relationship between body weight and body height was observed. This is mainly due to the fact that the height is due to growth of bones, whose function of increase in weight is probably not proportionate to increase in general body weight. The results are supported by other research (Singh et al 1979a; Mukherjee et al 1983; Bhattacharya et al 1984, Das et al 1990 and Ulaganathan et al 1992). As the age advances, the coefficient of determination for all characteristics decreased. This indicated that body measurements could predict 06 months body weight more accurately than >612 months body weight. On the contrary, Das and Sharma (1994) reported lower R^{2} values for weaning than those of yearling weight. However, highest variation of body weight was accounted for by combination of height at withers, chest girth and body length than individually of all the age groups in both sexes. These results are also supported by Bose and Basu (1984); Bhattacharya et al (1984); Prasad et al (1990); Das and Sharma (1994); Topal et al (2003) and Topal and Macit (2004). Since in all the age groups the highest R^{2} was obtained when all the body measurements were included in the regression equations, this suggests that weight could be estimated more accurately by combination of two or more measurements than by girth alone.
The coefficient of determination (R^{2}) was highest (89.1 per cent in males and 93.6 per cent in females) in a regression model constructed using pooled data, within sexes, from 012 months of age, when compared to equations constructed at different age groups. Hence, this regression equation alone may be used to predict the body weight of Kanni Adu goats at different age groups. Mayaka et al (1995) reported similar findings.
Table 4 shows the statistical parameters viz. R^{2}, MS_{E} , F value, C.V and SD_{E} for all the regression equations investigated. In a multiple regression analysis the important thing to be considered was which independent variables were most considered in determining the dependent variable.
Table 4. Statistical parameters for different equations 

Age group 
Equation 
Male 
Female 

F 
MS_{E} 
Sd_{E} 
CV 
R^{2} 
F 
MS_{E} 
Sd_{E} 
CV 
R^{2} 

03 months 
A 
140.3^{**} 
0.934 
0.966 
15.2 
0.855 
245.8^{**} 
0.739 
0.860 
14.6 
0.909 
B 
103.9^{**} 
1.20 
1.10 
17.2 
0.852 
313.4^{**} 
0.769 
0.877 
14.9 
0.905 

C 
142.2^{**} 
0.928 
0.964 
15.1 
0.810 
301.4^{**} 
0.797 
0.893 
15.2 
0.901 

D 
106.4^{**} 
0.927 
0.962 
15.2 
0.854 
271.2^{**} 
0.876 
0.936 
15.9 
0.892 

E 
109.9^{**} 
1.57 
1.25 
19.7 
0.748 
375.7^{**} 
0.939 
0.969 
16.5 
0.883 

F 
208.2^{**} 
0.941 
0.970 
15.3 
0.849 
351.2^{**} 
0.972 
0.986 
16.8 
0.878 

G 
133.8^{**} 
1.35 
1.16 
18.3 
0.783 
275.8^{**} 
1.227 
1.11 
18.9 
0.847 

>36 months 
A 
32.61^{**} 
1.27 
1.13 
6.1 
0.852 
50.5^{**} 
1.003 
1.00 
8.3 
0.818 
B 
48.10^{**} 
1.28 
1.13 
10.1 
0.842 
67.9^{**} 
0.992 
0.996 
8.2 
0.816 

C 
15.43^{**} 
2.98 
1.73 
7.8 
0.632 
35.4^{**} 
1.62 
1.28 
10.6 
0.697 

D 
51.7^{**} 
1.20 
1.09 
6.5 
0.852 
67.3^{**} 
1.04 
1.02 
8.4 
0.807 

E 
27.4^{**} 
3.14 
1.77 
9.8 
0.590 
35.1^{**} 
2.11 
1.45 
12.0 
0.599 

F 
101.5^{**} 
1.21 
1.10 
7.6 
0.842 
96.4^{**} 
1.03 
1.02 
8.4 
0.804 

G 
9.55^{**} 
5.10 
2.26 
15.8 
0.334 
31.8^{**} 
2.24 
1.50 
12.4 
0.575 

>69 months 
A 
2.5^{NS} 
2.11 
1.45 
10.0 
0.522 
7.6^{**} 
1.14 
1.07 
8.1 
0.580 
B 
3.5^{ NS} 
1.94 
1.39 
9.6 
0.510 
7.9^{**} 
1.28 
1.13 
8.5 
0.507 

C 
3.5^{ NS} 
1.93 
1.39 
9.6 
0.515 
9.9^{**} 
1.13 
1.06 
8.0 
0.563 

D 
1.7^{ NS} 
2.62 
1.62 
11.1 
0.341 
9.2^{**} 
1.18 
1.09 
8.2 
0.545 

E 
4.5^{*} 
1.98 
1.41 
9.7 
0.452 
8.2^{**} 
1.48 
1.23 
9.2 
0.405 

F 
1.9^{ NS} 
2.69 
1.64 
11.3 
0.256 
7.6^{**} 
1.52 
1.23 
9.3 
0.388 

G 
2.8^{ NS} 
2.40 
1.55 
10.7 
0.334 
12.8^{**} 
1.20 
1.10 
8.3 
0.517 

>912 months 
A 
3.4^{ NS} 
4.12 
2.03 
11.3 
0.817 
16.6^{**} 
3.0 
1.72 
11.0 
0.624 
B 
5.2^{ NS} 
3.44 
1.86 
10.3 
0.796 
11.1^{**} 
4.3 
2.06 
13.2 
0.447 

C 
5.9^{ NS} 
3.10 
1.76 
9.8 
0.817 
22.2^{**} 
2.94 
1.71 
10.9 
0.619 

D 
1.1^{ NS} 
9.27 
3.04 
16.9 
0.452 
22.5^{**} 
2.92 
1.71 
10.9 
0.622 

E 
9.0^{*} 
2.95 
1.72 
9.5 
0.782 
10.0^{**} 
5.10 
2.26 
14.4 
0.323 

F 
1.3^{ NS} 
8.98 
3.00 
16.6 
0.336 
14.2^{**} 
4.49 
2.12 
13.5 
0.403 

G 
2.0^{ NS} 
7.44 
2.73 
15.1 
0.450 
33.1^{**} 
2.91 
1.71 
10.9 
0.613 

012 months 
A 
288.6^{**} 
1.82 
1.35 
15.3 
0.913 
949^{**} 
1.195 
1.09 
11.0 
0.948 
B 
372.0^{**} 
1.87 
1.37 
15.5 
0.910 
1234^{**} 
1.223 
1.11 
11.1 
0.946 

C 
343.9^{**} 
2.02 
1.42 
16.1 
0.903 
1039^{**} 
1.439 
1.20 
12.1 
0.937 

D 
348.2^{**} 
1.99 
1.41 
16.0 
0.904 
1124^{**} 
1.336 
1.16 
11.6 
0.941 

E 
397.2^{**} 
2.54 
1.59 
18.1 
0.876 
1196^{**} 
1.839 
1.36 
13.7 
0.919 

F 
459.4^{**} 
2.23 
1.50 
17.0 
0.891 
1551^{**} 
1.445 
1.20 
12.1 
0.936 

G 
422.0^{**} 
2.41 
1.55 
17.6 
0.883 
1128^{**} 
1.939 
1.39 
14.0 
0.914 

A= a + b_{1} X1+ b_{2}
X2 + b_{3} X3; B= a + b_{1} X1+ b_{2} X2; C= a
+ b_{1} X1+ b_{3} X3; D= a + b_{2} X2 + b_{3}
X3; E= a + b_{1}X1; F= a + b_{2} X2; G= a + b_{3}
X3 
As a criterion, the value of R^{2} always increased as more independent variables were added to the regression. So, R^{2 } was not suitable for comparing the different equations. Hence, the criterion that was free from this disadvantage viz., residual mean square (MS_{E}) as per Snedecor and Cochran (1989) was used. Inclusion of chest girth and body length at 03 and >36 months in males, all the three body measurements at 03 months in females and at 012 months in both sexes, height at withers and body length at >69 months of both sexes, height at withers and chest girth at >36 months of females, height at withers alone at >912 months in males and body length at >912 months in females produced higher R^{2} with the smallest MS_{E} and SD_{E}. Hence, at different age groups, the regression equation with the above combinations may be used for estimating the body weight of Kanni Adu kids at respective age groups. Selection of criteria for prediction indicated that the independent variables with the smallest residual mean square might be selected. Since the decrease of residual mean square (MS_{E}) resulted in decrease of error standard deviation (SD_{E}), the same may also be used as a criterion. This is similar to the report of Topal et al (2003), Topal and Macit (2004). Ulaganathan et al (1992) who reported that larger R^{2} and smaller MS_{E} produced better goodness of fit.
The coefficient of variation for males (residual standard deviation/ mean of the dependent variable) was 6.1 to 19.7 per cent for males and 8.1 to 18.9 per cent for females. The F values were highly significant in both males and females of all age groups except at >69 months and >912 months in males. These results are similar to the report of Singh et al 1979a, 1979b; Bhattacharya et al 1984.
The predicted weight, difference between actual weight in proportions and the range for actual and predicted weight in different equations of both sexes is presented in Table 5.
Table 5. Mean (± SE) of actual weight (Kg) and predicted weight (Kg) in different equations for Kanni Adu male kids 

Age group 

Actual weight 
Male 

A 
B 
C 
D 
E 
F 
G 

0 – 3 months 
Predicted weight 
6.35 ± 0.28 
6.35 ± 0.50 
6.35 ± 0.26 
6.35 ± 0.26 
6.35 ± 0.26 
6.35 ± 0.25 
6.35 ± 0.26 
6.35 ± 0.25 
Difference (proportion) 
0.007 ± 0.27 
0.00 ± 0.11 
0.001 ± 0.12 
0.004 ± 0.11 
0.005 ± 0.14 
0.007 ± 0.11 
0.005 ± 0.13 

Range (min–max) 
12.2 (2.014.2) 
12.4 (0.913.5) 
12.4 (0.212.6) 
11.8 (0.912.7) 
12.5 (0.212.7) 
11.2 (0.912.1) 
12.3 (0.212.5) 
11.5 (1.112.6) 

>3 – 6 months 
Predicted weight 
11.68 ± 0.59 
11.68 ± 0.54 
11.68 ± 0.54 
11.68 ± 0.47 
11.70 ± 0.54 
11.70 ± 0.45 
11.68 ± 0.54 
11.69 ± 0.34 
Difference (proportion) 
0.005 ± 0.23 
0.005 ± 0.23 
0.00 ± 0.36 
0.014 ± 0.23 
0.014 ± 0.38 
0.005 ± 0.23 
0.001 ± 0.48 

Range (min–max) 
9.8 (7.217.0) 
10.2 (8.718.9) 
10.3 (8.819.1) 
8.4 (7.716.1) 
10.2 (8.718.9) 
7.3 (9.116.4) 
10.3 (8.819.1) 
7.8 (5.613.4) 

>6 – 9 months 
Predicted weight 
14.54 ± 0.50 
14.54 ± 0.36 
14.54 ± 0.36 
14.54 ± 0.36 
14.55 ± 0.29 
14.55 ± 0.34 
14.54 ± 0.25 
14.55 ± 0.29 
Difference (proportion) 
0.00 ± 0.35 
0.00 ± 0.36 
0.00 ± 0.35 
0.015 ± 0.41 
0.008 ± 0.38 
0.00 ± 0.44 
0.015 ± 0.41 

Range (min–max) 
5.6 (11.617.2) 
5.3 (12.017.3) 
5.1 (12.017.1) 
5.3 (12.017.3) 
3.3 (12.916.2) 
4.8 (12.317.1) 
3.3 (13.316.6) 
3.3 (12.916.2) 

>9 – 12 months 
Predicted weight 
18.04 ± 1.26 
18.04 ± 1.15 
18.06 ± 1.13 
18.04 ± 1.15 
16.81 ± 0.85 
18.04 ± 1.11 
18.03 ± 0.74 
16.96 ± 0.85 
Difference (proportion) 
0.001 ± 0.23 
0.014 ± 0.54 
0.001 ± 0.54 
1.229 ± 0.94 
0.0 ± 0.59 
0.014 ± 1.03 
1.086 ± 0.94 

Range (min–max) 
8.4 (15.423.8) 
7.4 (15.022.4) 
6.8 (14.821.6) 
7.3 (15.022.3) 
5.6 (13.819.4) 
7.0 (14.621.6) 
4.9 (15.720.6) 
5.6 (1.419.6) 

0 – 12 months 
Predicted weight 
8.92 ± 0.42 
8.86 ± 0.40 
8.90 ± 0.40 
8.80 ± 0.40 
8.83 ± 0.40 
8.89 ± 0.39 
8.90 ± 0.39 
8.74 ± 0.41 
Difference (proportion) 
0.056 ± 0.13 
0.020 ± 0.13 
0.114 ± 0.15 
0.086 ± 0.14 
0.03 ± 0.15 
0.017 ± 0.14 
0.176 ± 0.19 

Range (min–max) 
21.8 (2.023.8) 
19.6 (0.319.3) 
19.7 (0.319.4) 
19.4 (0.219.2) 
19.6 (0.319.3) 
19.7 (0.319.4) 
20.4 (2 20.2) 
24.3 (5.818.5) 

A= a + b_{1}
X1+ b_{2} X2 + b_{3} X3, B= a + b_{1} X1+ b_{2}
X2, C= a + b_{1} X1+ b_{3} X3, D= a + b_{2}
X2 + b_{3} X3, E= a + b_{1} X1, F= a + b_{2}
X2, G= a + b_{3} X3. 
In all the age groups of both sexes there was no significant difference between actual weight and predicted weight. But there was a difference in range values in each equation and the approximation to the actual was observed in equations with high R^{2} and lower MS_{E} and SD_{E.} Cross validation was performed for males and females for different equations and in most cases the prediction bias did not differ from zero. The equations with larger R^{2} with smallest MS_{E} and SD_{E} showed a range similar to the range observed in actual weight category. Lower R^{2} showed wide variation of range, which was, much higher than those observed in actual weight of both sexes.
Body weight and the three body measurements were significantly correlated with each other.
Body weight had higher association with heart girth than with length or height.
Correlations and coefficient of determination between 012 months age groups were higher than between weight at 03, >36, >69 and >912 months age group separately.
Instead of using separate equations for different age groups, the regression equation of 012 months may be used for predicting the body weight of Kanni Adu goats at different ages.
The chest girth alone or combinations of three measurements, may be used for predicting the body weight.
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Received 15 March 2005; Accepted 8 June 2005; Published 1 July 2005