Optimizing the Genomic Evaluation Model in Crossbred Cattle for Smallholder Production Systems in India

Kashif Dawood Khan, Rani Alex, Ashish Yadav, Varadanayakanahalli N. Sahana, Amritanshu Upadhyay, Rajesh V. Mani, Thankappan Sajeev Kumar, Rajeev Raghavan Pillai, Vikas Vohra and Gopal Ramdasji Gowane ()
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Kashif Dawood Khan: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Rani Alex: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Ashish Yadav: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Varadanayakanahalli N. Sahana: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Amritanshu Upadhyay: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Rajesh V. Mani: Kerala Livestock Development Board (KLDB), Gokkulam, Thiruvananthapuram 695004, Kerala, India
Thankappan Sajeev Kumar: Kerala Livestock Development Board (KLDB), Gokkulam, Thiruvananthapuram 695004, Kerala, India
Rajeev Raghavan Pillai: Kerala Livestock Development Board (KLDB), Gokkulam, Thiruvananthapuram 695004, Kerala, India
Vikas Vohra: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India
Gopal Ramdasji Gowane: Division of Animal Genetics and Breeding, ICAR-National Dairy Research Institute, Karnal 132001, Haryana, India

Agriculture, 2025, vol. 15, issue 9, 1-19

Abstract: Implementing genomic selection in smallholder dairy systems is challenging due to limited genetic connectedness and diverse management practices. This study aimed to optimize genomic evaluation models for crossbred cattle in South India. Data included 305-day first lactation milk yield (FLMY) records from 17,650 cows (1984–2021), with partial pedigree and genotypes for 1004 bulls and 1568 cows. Non-genetic factors such as geography, season and period of calving, and age at first calving were significant sources of variation. The average milk yield was 2875 ± 123.54 kg. Genetic evaluation models used a female-only reference. Heritability estimates using different approaches were 0.32 ± 0.03 (REML), 0.40 ± 0.03 (ssGREML), and 0.25 ± 0.08 (GREML). Bayesian estimates (Bayes A, B, C, Cπ, and ssBR) ranged from 0.20 ± 0.02 to 0.43 ± 0.04. Genomic-only models showed reduced variance due to the Bulmer effect, as genomic data belonged to recent generations. Breeding value prediction accuracies were 0.60 (PBLUP), 0.45 (GBLUP), and 0.65 (ssGBLUP). Using the LR method, the estimates of bias, dispersion, and ratio of accuracies for ssGBLUP were −39.83, 1.09, and 0.69; for ssBR, they were 71.83, 0.83, and 0.76. ssGBLUP resulted in more accurate and less biased GEBVs than ssBR. We recommend ssGBLUP for genomic evaluation of crossbred cattle for milk production under smallholder systems.

Keywords: crossbred cattle; genomic selection; heritability; 305-DMY; ssGBLUP (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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