Chief EditorHarjinder Singh
Print ISSN 0971-4456
Online ISSN 0976-0563
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Full Research Article
Impact of Non-genetic Factors on Kleiber Ratio in Field Flocks of Marwari Goat
Methods: The linear mixed model used for kleiber ratio estimation included: year of birth, sex, cluster, birth type and age of dam as fixed factors.
Result: Overall least-squares means (LSM) for Kleiber ratio (KR) from birth to 3 months (KR1), 3 to 6 months (KR2) and 6 to 12 months (KR3) were 12.89±0.03, 9.69±0.05 and 4.59±0.06, respectively. Year of birth and cluster had highly significant effect on all KR. The birth type had significant on all KR except KR1. The non-significant effect of sex and age of dam were observed on all KR except KR1. The study revealed that the KR was affected by different non-genetic factors. The heritability estimates for KR1, KR2 and KR2 were 0.66±0.28, 0.07±0.07 and 0.54±0.26, respectively.
MATERIALS AND METHODS
W2=Body weight at the end (kg).
W1=Body weight at the start (kg).
t2 = Animal’s age at the end of the period (days).
t1 = Animal’s age at the start of the period (days).
Arthur et al. (2001) explained KR as a fraction of ADG and live weight (LWT)0.75 as both observations were under a similar unit (Kg.). Kleiber ratio from birth to 3-months (KR1), Kleiber ratio from 3-months to 6 months (KR2) and 6 months to 12 months (KR3) were calculated by following formulae:
The data were assigned to linear mixed model equation (LMME) analysis using IBM SPSS (2005) version 25.0. The LMME included fixed covariates were year of birth, sex of the kid, cluster, type of birth and dam’s age at kidding. Duncan’s multiple range test (Kramer, 1957) was used for analysing subclass differences.
The statistical model used to investigate the effect several factors on kleiber ratio were as follow:-
Yijklmn= µ + Ai + Bj+ Ck + Dl + Gm + eijklmn
Yijklmn= Performance of the nth kid born in ith year of jth sex in kth cluster of lth birth type and belonging to mth age of dam.
µ = Mean of the whole population.
Ai = Fixed effect of ith year period of birth (i=1 to 6).
Bj = Fixed effect of jth sex (j=1 and 2).
Ck = Fixed effect of kth cluster (k=1 to 5).
Dl = Fixed effect of birth type lth (l=1 and 2).
Gm=Fixed effect of mth age of dam (m=1 to 3).
eijklmn= Is a residual random error associated with Yijklmn which is assumed to be normally and independently distributed with mean zero and error variance (0,σ2).
After normalising data for important non-genetic factors, paternal half-sib correlation approach was used to evaluate heritability, genetic (rg) and phenotypic (rp) correlations (Harvey, 1990).
RESULTS AND DISCUSSION
The Kleiber ratio (KR) measures the metabolic weight gain in animals. The overall least-squares means (LSM) of KR1, KR2 and KR3 were observed to be 12.89±0.03, 9.69±0.05 and 4.59±0.06, respectively (Table 1). This proves that animals are more capable of converting food at a younger age. KR reduced as the animal became older, which indicated that as animals grow older, their efficiency of feed conversion weakens. The mean of KR was comparable with those of Khadda et al. (2018) in Pantja goat; Gupta et al. (2016) in Mehsana goat and Barazandeh et al., (2012) in Raini Cashmere goat.
Effect of non-genetic factors
The effects of different non-genetic factors are shown in Table 1. The effect of year of birth was found highly significant (P<0.01) on all KR. The increasing trend of KR in Marwari kids shows the performance of productive animals for the transformation of feed. In years with greater average rainfall, post-weaning KR (KR2 and KR3) was seen to be higher. The significant influence of year of birth on KR obtained was similar to those reported by Gupta et al. (2016) in Mehsana goat and Casey and Webb (2010) in Boer goats.
The effect of sex and age of dam had highly significant (P<0.01) effect on pre-weaning KR (KR1). The sex difference may be related to the anabolic action of hormones that allow them to gain weight. It showed that males grew at faster rate, conversion of feed and acquired more body weight upto weaning age. The significant influence of sex on KR1 was similar to reports of Khadda et al. (2018) in Pantja goat, Moghbeli et al. (2013) in Raini Cashmere goats and Pralomkarn (2012) in native goats. The effect of sex and age of dam had non-significant effect on post-weaning KR (KR2 and KR3). The non-significant effect of sex on post weaning KR were also observed by Gupta et al. (2016) in Mehsana goat and Khadda et al. (2018) in Pantja goat.
The effect of the cluster was found highly significant (P<0.01) on all KRs. In pre-weaning period KR1 was reported significantly higher in Daiya cluster while in post weaning period it was significantly higher in Kan singh ki sid and in Kalayansar, respectively. There was no clear cut consistency observed in different clusters. Environmental differences such as difference in managemental practices followed by the goat rears, agro-climatic conditions, goat management strategies used by goat herders, socio-economic heterogeneity among goat rears and difference in maternal effect in pre and post weaning period might be the cause of significant effect of cluster on KRs.
The effect of type of birth was found highly significant (P<0.01) on KR2 and significant (P<0.05) on KR3 whereas it was found non-significant on KR1. At both pre-and post-weaning ages, twins performed better in terms of food conversion. The significant effect of birth type on pre-weaning age was observed by Khadda et al. (2018) in Pantja goat and Pralomkarn (2012) in native goats.
The model that was used to describe the different KRs was able to explain that KR3 was the most accurate (adjusted R2=39.1%), followed by KR1 and then KR2.
The heritability estimates for KR1, KR2 and KR3 were 0.66±0.28, 0.07±0.07 and 0.54±0.26, respectively, which were medium and comparable with the findings of Gupta et al. (2016) in Mehsana goat and Khadda et al. (2018) in Pantja goat. The genetic correlation between KR1-KR2 (-0.50±0.59), KR2-KR3 (-0.08±0.67) and KR1-KR3 (-0.84±0.20) was very high, negative. However, phenotypic correlation between KR1-KR2 (-0.49), KR2-KR3 (-0.33) and KR1-KR3 (-0.41) was moderately negative. Pre- and post-weaning KRs had medium to high heritability estimates, suggesting that a selection procedure might increase the flock’s feed conversion efficiency. Because of the substantial genetic connection between pre- and post-weaning KRs, it may be possible to select kids even at the time of weaning to increase performance based on a six-month weight and it may also be feasible to cull kids even before weaning because of the correlated response to selection. Furthermore, selection for higher early body weights may lead to genetic improvements in subsequent body weights.
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