Abstract
Abstract The objectives of this study were to estimate genetic parameters for temperament via three approaches and to examine associations of temperament with other economically important traits in Chinese Holstein. Records for temperament score (TS) on 6,586 lactating cows from 2015 to 2017 were obtained. Temperament assessed during rectal temperature measurements was recorded on a 3-point scale (1 = quiet; 2 = average; 3 = nervous). TS was treated as a ternary trait or a binary trait in different scenarios. The genetic parameters were estimated by: 1) a linear model using AI-REML; 2) a Generalized Linear Mixed Model (GLMM); or 3) a Bayesian threshold model via Gibbs sampling. Each record was partitioned into the fixed effects of herd-scorer and parity, an additive genetic effect and a residual effect. Then approximate genetic correlation between TS with production traits [milk yield (MY), fat and protein percentage (FP and PP)], fertility traits [age at first service (AFS), age at first calving (AFC), stillbirth (SB)], overall type, health traits [somatic cell score (SCS), udder diseases (UD) claw and leg diseases (CLD) metabolic disorders (MD)] and productive life (PL) were estimated. Estimates of heritability and accuracy of EBV for TS were listed in Table 1. Low to moderate genetic correlation between TS and above-mentioned traits were found. There was a favorable genetic correlation between TS and FP (-0.35), PP (-0.42), AFC (0.31), UD (0.58) and PL (-0.24); however, undesirable genetic correlation existed between TS and the other traits (-0.43~0.27). Current results suggested that a Bayesian threshold model can be the most recommended algorithm for analyzing temperament since it brought a relatively higher heritability and consequently EBV with higher accuracy, and selection for calmer individuals will translate into increased fat and protein yields, a lower age at first calving, better resistance to udder diseases and a longer functional longevity.
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