Published in Scientific Papers. Series D. Animal Science, Vol. LXVIII, Issue 1
Written by Roxana-Bianca COSA, Horia Grosu
Milk production in dairy cattle is influenced by multiple genetic and environmental factors, making precise lactation curve modeling essential for accurate milk yield estimation and genetic evaluation. In recent decades, numerous scientific studies have focused on improving these models to enhance the accuracy of milk production estimates for standard lactation. This study aims to identify the most suitable model for predicting breeding values using a limited number of test-day records at different lactation stages. Data from two lactations were analyzed. For the first lactation, 9235 test records from 1270 Romanian Spotted Simmental cows were examined, while the second lactation included 9984 test records from 1409 cows of the same breed. Production and pedigree data were modeled using three biometric functions: Legendre Orthogonal Polynomial, Natural Cubic Spline, and P-Spline Function. Among these, the P-Spline Function provided the most accurate results. These findings are particularly valuable in animal breeding, enabling more precise genetic evaluations and contributing to improved selection strategies for dairy cattle.
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