Elucidating genotype by environment interaction over the growth trajectory of Malpura sheep in the semi-arid region of India through Random regression model

Dhakad, Govind Singh; Saini, Samita; Mallick, P.K.; Misra, S. S.; Gowane, G. R.; Sharma, Sanjita; Prakash, Ved; Kumar, Arun; Mahala, Sudarshan; Singh, Navav

doi:10.1016/j.smallrumres.2022.106791

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…Researchers worldwide have evaluated lactation traits in goats using random regression test-day model (Amin, 2018;Andonov et al, 2013;Arnal et al, 2019Arnal et al, , 2020Brito et al, 2018;Liu et al, 2000;Menéndez-Buxadera et al, 2010;Menezes et al, 2011;Mucha et al, 2014;Nogueira et al, 2020;Silva et al, 2013;Thepparat et al, 2015;Zumbach et al, 2008). In India, few studies have applied random regression models to small ruminants, primarily for modelling growth curves (Dhakad et al, 2022;Dige et al, 2021;Mahala et al, 2020;Venkataramanan, 2016). Dige et al (2022) conducted a genetic evaluation of the lactation curve using RRM in Jamunapari goats.…”

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confidence: 99%

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B‐spline functions

Upadhyay,

Alex,

Dige

et al. 2024

J Animal Breeding Genetics

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The current study sought to genetically assess the lactation curve of Alpine × Beetal crossbred goats through the application of random regression models (RRM). The objective was to estimate genetic parameters of the first lactation test‐day milk yield (TDMY) for devising a practical breeding strategy within the nucleus breeding programme. In order to model variations in lactation curves, 25,998 TDMY records were used in this study. For the purpose of estimating genetic parameters, orthogonal Legendre polynomials (LEG) and B‐splines (BS) were examined in order to generate suitable and parsimonious models. A single‐trait RRM technique was used for the analysis. The average first lactation TDMY was 1.22 ± 0.03 kg and peak yield (1.35 ± 0.02 kg) was achieved around the 7th test day (TD). The present investigation has demonstrated the superiority of the B‐spline model for the genetic evaluation of Alpine × Beetal dairy goats. The optimal random regression model was identified as a quadratic B‐spline function, characterized by six knots to represent the central trend. This model effectively captured the patterns of additive genetic influences, animal‐specific permanent environmental effects (c2) and 22 distinct classes of (heterogeneous) residual variance. Additive variances and heritability (h2) estimates were lower in the early lactation, however, moderate across most parts of the lactation studied, ranging from 0.09 ± 0.04 to 0.33 ± 0.06. The moderate heritability estimates indicate the potential for selection using favourable combinations of test days throughout the lactation period. It was also observed that a high proportion of total variance was attributed to the animal's permanent environment. Positive genetic correlations were observed for adjacent TDMY values, while the correlations became less pronounced for more distant TDMY values. Considering better fitting of the lactation curve, the use of B‐spline functions for genetic evaluation of Alpine × Beetal goats using RRM is recommended.

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Section: Introductionmentioning

confidence: 99%

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B‐spline functions

Upadhyay,

Alex,

Dige

et al. 2024

J Animal Breeding Genetics

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Multi-trait Bayesian analysis and genetic parameter estimates in production characters of Mecheri sheep of India

Thiruvenkadan¹,

Muralidharan

Ramanujam³

et al. 2022

Trop Anim Health Prod

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The present study was conducted to calculate the genetic parameters for direct and maternal in uences on Mecheri sheep growth features by Bayesian analysis using multi-trait animal model for designing suitable breeding application and genetic assessment methodologies. The genetic determinants for varying body weights at different ages were calculated using data from 2825 Mecheri lambs born between 2010 and 2020 that were kept in a warm and semiarid climate. Mecheri sheep body weight (mean ± SE) at various stages viz., BW, WW and BW12 were 2.6 ± 0.01, 11.1 ± 0.05 and 20.7 ± 0.13 kg respectively. The direct estimates of heritability (± SD) for BW, WW, BW6 and BW12 were 0.21 ± 0.041, 0.21 ± 0.041, 0.12 ± 0.052 and 0.13 ± 0.053 respectively and the maternal heritability for BW, WW, BW6 and BW12 was 0.18 ± 0.021, 0.08 ± 0.023, 0.11 ± 0.022 and 0.13 ± 0.033, respectively. Estimates of maternal heritability suggests that even at later stages, there were considerable maternal effects. For several growth traits, positive estimates of additive genetic connections were observed, with values ranging from low to high. The additive genetic correlation between WW and BW6, BW9 and BW12 was 0.70 ± 0.145, 0.57 ± 0.171 and 0.50 ± 0.194. The maternal genetic correlations ranged from 0.06 ± 0.152 (BW-BW12) to 0.86 ± 0.046 (BW6-BW9) and the residual correlation increased progressively from 0.18 ± 0.034 (BW-WW) to 0.85 ± 0.013 (BW9-BW12). The medium to high estimates of heritability and genetic correlation of body weight parameters at various ages in Mecheri sheep indicated the genetic potential for all traits. In general, the features WW and BW6 both refer to the same genetic growth process, hence, it is recommended to undertake single trait selection based on weight at weaning age rather than using the present selection procedure of weight at six-month of age. By choosing the top performers from the Mecheri sheep ocks, it is possible to take advantage of the strong genetic potential for improvement in these parameters.

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Elucidating genotype by environment interaction over the growth trajectory of Malpura sheep in the semi-arid region of India through Random regression model

Cited by 2 publications

References 37 publications

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B‐spline functions

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B‐spline functions

Multi-trait Bayesian analysis and genetic parameter estimates in production characters of Mecheri sheep of India

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