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Vol. 12, Special Issue 12 (2023)

Simulation model for the heritability estimation of milk yield in crossbred dairy cattle under field conditions

Author(s):
R Saravanan, E Geetha, M Jeyakumar, CM Vandana and DN Das
Abstract:
The successful selection of superior animals requires a combination of accurate data collection, rigorous evaluation methods, and a clear understanding of breeding objectives. The absence of performance records poses a significant challenge to conducting meaningful research and developing analytical models for field animals. The simulation study was conducted in ten replicates of 500, 1000, and 3000 first lactation records with different levels of input heritability (0.15, 0.20, and 0.25) from the field performance records of crossbred dairy cattle. The datasets were examined to assess the heritability of lactation milk yield and determine the optimal simulation model for analysis. Two distinct models, incorporating varied combinations of fixed effects such as village, year, and month of calving, were tested, each including the sire effect. Between the models considered, the heritability was generally higher for model 2 and the trend was similar for data sets with different sizes. The trend in the variation of R2–values and heritability among models and replicates exhibited a decrease with an increase in progeny size. The magnitude of R2–values explained by various models across different datasets was greater for a heritability of 0.25 compared to values of 0.15 and 0.20.
Pages: 616-621  |  78 Views  40 Downloads
How to cite this article:
R Saravanan, E Geetha, M Jeyakumar, CM Vandana and DN Das. Simulation model for the heritability estimation of milk yield in crossbred dairy cattle under field conditions. The Pharma Innovation Journal. 2023; 12(12S): 616-621.
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