Conservation & local programs

Assessment and Maintenance of Genetic Purity in Indonesian Local Cattle Populations via Integrated Genomic Selection and SNP Parentage Analysis

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Abstract

Genetic improvement programs aimed at enhancing productivity, adaptability, and sustainability in cattle populations had benefited from robust breeding and selection strategies. In parallel with rapid technological advances and the emergence of the big data era, the application of AI, particularly machine learning approaches, had expanded opportunities to advance local cattle production systems in Indonesia. This study proposed an integrated resolution framework to enhance national cattle production through the use of parentage analysis data while preserving the genetic integrity of indigenous cattle breeds. Indonesia maintained an estimated cattle population of 11.79 million head, with per capita beef consumption reaching approximately 2.60 kg. National statistics indicated that beef consumption in 2022 reached 627,952 tons, substantially exceeding domestic production of 413,669 tons. This imbalance highlighted the urgent need for sustainable strategies to increase cattle populations without compromising superior genetic traits inherited from elite sires and dams. The proposed framework emphasized population expansion in parallel with the conservation of valuable local genetic resources within national production systems. Improvements in smallholder recording practices were identified as a critical foundation, enabling the integration of high-quality phenotypic and pedigree data with AI-based models to identify predictive genetic biomarkers aligned with specific breeding objectives. Advanced genomic approaches, including GWAS and RNA-seq, were incorporated as key inputs for genomic selection pipelines. These methods supported informed selection and mating decisions, forming the basis of systematic and evidence-driven breeding programs. The integration of improved data management, genomic technologies, and machine learning-based prediction was expected to enhance breeding efficiency and long-term genetic gain, with predictive accuracy reaching approximately 80-85%. Overall, the proposed integrative strategy was expected to support sustainable growth of local cattle populations, maintain genetic purity of indigenous breeds, enhance meat and milk availability, and mitigate supply-demand imbalances in Indonesia.

Keywords: 2026

How to Cite:

Rahmatullah, S., Mahawan, T. & Phakdeedindan, P., (2026) “Assessment and Maintenance of Genetic Purity in Indonesian Local Cattle Populations via Integrated Genomic Selection and SNP Parentage Analysis”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2284677. doi: https://doi.org/10.31274/wcgalp.23610

Rights: 1