![]() In animal breeding, random regression methodology (RRM) has been widely used for genetic evaluation of dairy cattle ( Schaeffer and Dekkers 1994) and dairy sheep ( Kominakis et al. Lactation curves with lower peaks may be more persistent and the overall milk yield may therefore be larger in more persistent lactations. However, none of these measurements became the standard method for calculation of persistency. Measures based upon parameter estimates from mathematical models of lactation curves. Measures derived from the variation of test day yields and 3. Measures expressed as a ratio (or a rate) of yields 2. (1999) categorized persistency measures into three groups: 1. Persistent animals therefore generate more return. 2006) and finally, lower reproductive costs ( Muir et al. This allows for better usage of cheap roughage ( Solkner and Fuchs 1987), reduction of stress during peak production and increase profit ( Weller et al. Higher persistency or a flat lactation curve has several advantages. Thus, persistent animals are those that show flatter lactation curves ( Togashi and Lin 2004). 1997) or the ability of a cow to maintain a relatively constant milk yield throughout lactation ( Strabel et al. Persistency can be defined as the ability of a cow to continue producing milk at a high level after reaching the peak of lactation ( Jamrozik et al. Milk production and persistency are two economic important traits in dairy cows. Key words: additive genetic effects lactation curve persistency total milk yield It can therefore be concluded that calculation of persistency using random regression methodology is preferred to the best prediction method. However, due to the flexibility of random regression methodology, some measures of persistency using this method can have higher heritability and genetic correlation with total milk yield compared to the best prediction methodology. ![]() The results showed that the best prediction method is powerful and accurate in measuring persistency. Heritabilities of milk yield persistency for Pers1 predicted breeding value from 106-205 days in milk, subtracted from predicted breeding value from 6-105 days in milk) and Pers2 (predicted breeding value from 206-305 days in milk subtracted from predicted breeding value from 6-105 days in milk) calculated by Random regression methodology were 0.09 to 0.185, respectively. Evaluation of persistency using best prediction methodology showed that the phenotypic correlation between this persistency measure and total milk yield was 0.450, while the best reference day, the heritability of persistency and 305 d milk yield estimated by this method, were day 130, 0.11 and 0.305, respectively. The data consisted of 435,390 test day milk yield records of primiparous cows in 659 herds calving from 2001 to 2011. ![]()
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