Genetic and phenotypic analysis of milk yield and composition in Murciano-Granadina goats.

Abstract

The Murciano-Granadina goat breed was imported from Spain to the southern region of Iran to enhance production efficiency in the native and nomadic goat flocks of the region, primarily maintained under a low-input, low-output production system. In this study, the genetic and phenotypic aspects of milk production traits in the Murciano-Granadina goat breed were investigated using data collected from a private dairy farm in Ghale-Ganj city, located in southern Kerman province, Iran, between 2017 and 2024. Data on 76,874 test-day lactation records of milk yield (MY), fat yield (FY), protein yield (PY) and somatic cell count from 7,196 first-parity Murciano-Granadina does were used. The investigated traits were total MY, total FY, total PY, average fat-to-protein ratio (FPR) and average somatic cell score (SCS), all calculated based on a 275-day lactation period. A multivariate animal model was used to estimate the genetic and phenotypic parameters of the investigated traits. The heritability estimates for MY, FY, PY, FPR and SCS were 0.15, 0.06, 0.09, 0.10 and 0.26, respectively. The estimates of genetic correlations among the studied traits ranged from -0.38 for FY-FPR to 0.91 for FY-PY, while the phenotypic correlations ranged from -0.05 for MY-FPR to 0.90 for PY-FY. Genetic correlations between SCS and MY, FY and PY were low estimates of 0.16, 0.19 and 0.08, respectively. The corresponding phenotypic correlations were low estimates of 0.03 (MY-SCS), 0.05 (FY-SCS) and 0.06 (PY-SCS). Genetic and phenotypic correlation estimates among MY, FY and PY were positive and medium to high, with the corresponding genetic correlations generally higher than the phenotypic ones. These low heritability estimates for all the studied traits, except for SCS, suggest that non-additive genetic and environmental effects play a more significant role in the performance of the Murciano-Granadina goat. The high positive genetic correlation estimates between MY, FY and PY suggest that selection for higher MY should also increase in both FY and PY.