Optimizing selection strategy for enhancing reproduction efficiency in Indian crossbred goats using milk productivity as a selection criterion

Abstract

The present study was aimed at optimizing the selection strategy for enhancing reproductive efficiency and milk productivity of Alpine × Beetal crossbred goats. The data set included 2949 milk trait records across parities and 1389 milk records from first parity and corresponding reproductive traits. The traits included for analysis were 150‐day milk yield (150DMY), days in milk (DIM), peak yield (PY) and total milk yield (TMY). The litter size (LS) and litter weight (LW) were used for specifically formulating selection plan using indirect selection. The least squares mean for lactation traits during the first parity were 150DMY: 195.32 ± 2.09 kg, DIM: 236.42 ± 3.04 days, PY: 1.82 ± 0.02 kg, TMY: 269.62 ± 4.52 kg. Notably, Alpine × Beetal goats demonstrated genetic superiority pan India for milk productivity as compared to other native goat breeds. The least squares mean for 150DMY across all parities was 236 ± 3.13 kg. An animal model employing average information restricted maximum likelihood was used for (co)variance component estimation to get the genetic parameters. The analysis revealed total heritability estimates for 150DMY, DIM, PY and TMY as 0.18 ± 0.06, 0.04 ± 0.04, 0.12 ± 0.06 and 0.08 ± 0.05, respectively. Repeatability estimates for 150DMY, DIM, and TMY were 0.28 ± 0.04, 0.21 ± 0.03 and 0.37 ± 0.03, respectively. Bivariate analysis of 150DMY with reproductive traits revealed heritability for LS and LW as 0.05 ± 0.01 and 0.10 ± 0.01, respectively using Gibbs sampling. Strong and positive genetic correlations of 150DMY with other production and reproduction traits was observed, such as DIM (0.72), PY (0.98), TMY (0.88), LS (0.57) and LW (0.33). Moderate heritability and repeatability estimate of 150DMY, along with its positive correlation with production and reproductive traits suggested it as a suitable selection criterion for early selection and overall genetic progress of lactation traits. The genetic trend analysis showed an overall improvement in all these traits, with observed gain of 98.4 g per year for 150DMY, 0.04 days per year for DIM, 0.5 g per year for PY and 220.5 g per year for TMY. We observed that selecting based on 150DMY would lead to a favourable indirect improvement for LW as 79 g and LS 0.04 units per generation. We, therefore, recommend employing 150DMY as the single trait selection criteria to enhance both milk productivity and reproductive potential of Alpine × Beetal goats.

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

“…It initiates at 0.93 kg during the initial milk measurement, reaches a peak of 1.35 kg in the 7th week post-kidding and subsequently declines progressively in subsequent milk measurements, reaching 1.19 kg by the 22nd week of lactation. It is worth mentioning here that the average first lactation cumulative 150-day milk yield (150DMY) in this particular flock was 195.32 ± 2.09 kg (Upadhyay et al, 2023). Figure 1 also shows the predicted mean lactation curve obtained by fitting an RRM of LP3 with R 2 value of 69% for the first-parity TDMY in Alpine × Beetal goats.…”

“…Alpine × Beetal crossbreds were developed at ICAR-National Dairy Research Institute, Karnal, during the early 1970s and maintained ever since at the Livestock Research Centre of NDRI. These crossbred goats exhibit enhanced prolificacy (Sahoo et al, 2023) and milk production (Upadhyay et al, 2023) while acclimating to Karnal's sub-tropical climate.…”

Assessing genetic parameters for first parity reproductive traits for early selection in Saanen × Beetal goats of India

“…A successful breeding programme relies on a higher additive genetic variance for the trait of interest (Rauw et al, 1988). Previous studies have highlighted the importance of estimating genetic parameters in devising a successful breeding programme for different breeds of goats (Dige et al, 2021;Gowane et al, 2011;Kebede et al, 2012;Mohammadi et al, 2012;Rashidi et al, 2011;Rout et al, 2018;Sahoo et al, 2023b;Upadhyay et al, 2024b;Zhou et al, 2015). Despite the importance of estimating genetic parameters for reproductive traits, there has been lack of scientific research investigating strategies to improve prolificacy in this flock.…”