ABSTRACT
This study aimed to evaluate the genetic potential of the Jamunapari goat and formulate a selection strategy for improving lactation traits. The data set included 4049 phenotypic records for across parity milk yield at 90 days (MY90), 140 days (MY140), total milk yield (TMY), and lactation length (LL) obtained from the progeny of 83 sires and 1643 dams between the period 1990 and 2019. Animal model employing average information restricted maximum likelihood (AIREML) was used to estimate genetic parameters for milk yield traits and LL. The direct additive heritability estimates for across parity lactation traits that used repeatability model were 0.10 ± 0.03, 0.08 ± 0.03, and 0.12 ± 0.02 for MY90, MY140, and TMY, respectively, while it was low for LL (0.06 ± 0.02). The repeatability estimates were moderate ranging from 0.17 to 0.22 for milk yield traits and LL, indicating persistent performance over the parities. Animal permanent environment influence (c2) was significant in milk yield attributes, whereas direct maternal genetic effects were absent. As the early selection criteria based on first parity records are essential, we analyzed the data for the first parity separately and obtained moderate h2 estimates, viz., 0.26 ± 0.05, 0.16 ± 0.06, and 0.25 ± 0.06 for MY90, MY140, and TMY, respectively. These estimates augur further scope of selection in Jamunapari goats for higher milk yield. High and positive genetic correlation of MY90 with MY140 (0.97 ± 0.01) and TMY (0.91 ± 0.05) revealed the scope of using MY90 as the selection criterion. Based on these results, we recommend use of first parity MY90 as a single trait selection criterion for genetic improvement of all lactation traits in Jamunapari goat.
Subject(s)
Goats , Milk , Animals , Female , Pregnancy , Goats/genetics , Lactation/genetics , Parity , Maternal InheritanceABSTRACT
Goats are adaptable to varied farming environments and contribute significantly towards sustainable livestock production and food security. Selective breeding of goats for improved performance is an important component of sustainable production. The objectives of the present study were to determine the most appropriate models of analysis for growth traits, to estimate genetic parameters, survival potential of kids from birth to 12 months of age and to estimate genetic trends for growth traits of Jamunapari kids at different ages. Genetic parameter estimates were obtained from 6590 records generated between 1982 and 2012 from 5922 animals with a pedigree covering over 13 generations. The most parsimonious model for early growth traits included permanent environmental effects due to the dam (PE) and litter effects. Similarly, the most appropriate model for early average daily gain (ADG) between birth and 3 or 6 months also included PE and litter effects. The estimates of heritability for survival from birth to 12 months of age ranged from 0.10 to 0.43. The estimates of heritability for ADG varied from 0.04 to 0.41. In general, higher estimates of heritability were observed when a sire model was fitted in the random effect. There was no genetic variation observed for survival between birth and 3 months of age. However, heritability estimates of between 0.18 and 0.39 were observed for survivability during post-weaning period to 12 months of age. The genetic trend at 9 months of age and 12 months of age was 0.144â¯kg 0.189â¯kg per year respectively. The genetic trend at all the ages was positive during the study period.
ABSTRACT
Deep inspiration shifted the mean frontal plane axis of P, QRS and T waves to the right in all the cases. Greater degree of shift in AP and AQRS was observed in cases where the resting axis had been 0 degrees to +30 degrees and minimum shift was observed where the resting axis was between +61 degrees to +90 degrees. Axis of the T wave though shifted to the right with deep inspiration in all the cases but there had been no statistically significant difference in the degree of shift in the three groups. In none of the case, axis changed from normal to abnormal degree.
