Genomic Prediction of Milk Fat Percentage Among Crossbred Cattle in the Indian Subcontinent
Year: 2025
Type: article
Abstract: This study focused on improving the milk fat percentage for crossbred dairy cows in smallholder systems, using GEBV. The data were collected from 2507 animals between 2016 and 2023 under BAIF's Enhanced Genetic Gains program in Pune, India. After refining the dataset, 33,845 records from 1896 animals were analyzed. The result showed that 75.54% of farms had either one or two animals. Prior to quality control, the mean milk fat percentage was 3.94%, but it decreased to 3.83% after data pruning, which necessitated removing the outliers. Genetic analysis involved 1478 animals genotyped for 49,911 SNPs after applying a rigorous quality control process, and imputation improved the accuracy of genomic data, boosting allele frequency correlation from 0.594 to 0.882. The study revealed that the additive genetic variance, phenotypic variance, and error variance were calculated as 0.012, 0.118, and 0.106, respectively. The heritability was estimated at 0.10, suggesting cautious use for breeding improvements. The GEBV ranged from 0.096 to 3.10%, which offers breeders a practical tool for selecting high-fat-producing cows. This research provides valuable insights into optimizing milk quality and advancing genetic improvement strategies in smallholder dairy systems.
Source: Animals
DOI: 10.3390/ani15071004
Authors: Raghavendran Vadivel Balasubramanian, Murali Nagarajan, Marimuthu Swaminathan, Raja Angamuthu, Muralidharan Jaganadhan, Saravanan Ramasamy, Malarmathi Muthusamy, Thiruvenkadan Aranganoor Kannan, Sunday Olusola Peters
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4408995602
