TY - JOUR T1 - Deciphering cattle temperament measures derived from a four-platform standing scale using genetic factor analytic modeling JF - bioRxiv DO - 10.1101/2020.01.20.913343 SP - 2020.01.20.913343 AU - Haipeng Yu AU - Gota Morota AU - Elfren F. Celestino, Jr. AU - Carl R. Dahlen AU - Sarah A. Wagner AU - David G. Riley AU - Lauren L. Hulsman Hanna Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/01/21/2020.01.20.913343.abstract N2 - Background The animal’s reaction to human handling, also known as temperament, is critical for work safety, productivity, and welfare. Subjective phenotyping methods, such as docility score, have been traditionally used in cattle production as a means for improving the safety, productivity, and welfare of animals. Even so, subjective scales rely on the evaluator’s knowledge and interpretation of temperament, which may require substantial experience. With that being said, selection based on such subjective scores may not precisely impact temperament preferences in cattle.Results We investigated the statistical relationships among subjective methods including docility score (DS), temperament score (TS), 12 qualitative behavior assessment (QBA) attributes along with a movement-based objective method (four-platform standing scale, FPSS) including the standard deviation of total weight on FPSS over time (SSD) and coefficient of variation of SSD (CVSSD) using 1,528 calves at weaning age. An exploratory factor analysis (EFA) identified two underlying latent variables contribute to TS and 12 QBA attributes that were named difficult and easy according to their characteristics. As DS is evaluated under constraint and other measures are not, inclusion of DS in EFA of subjective methods was not a good fit. A Bayesian confirmatory factor analysis inferred the factor scores of difficult and easy using the latent structure discovered in EFA. This was followed by fitting a pedigree-based Bayesian multi-trait model using difficult, easy, DS, SSD, and CVSSD to characterize the genetic interrelationships between subjective and FPSS measures. The estimates of heritability range from 0.17 to 0.4 with the posterior standard deviation averaging 0.06. The factors of difficult and easy exhibited a large negative genetic correlation of −0.92. DS displayed a moderate genetic correlation with difficult (0.36), easy (−0.31), SSD (0.42), and CVSSD (0.34). FPSS and DS were found to have a moderate genetic correlation with difficult (0.35 to 0.41) and easy (−0.39 to −0.31), indicating selection could be performed with either and have similar outcomes.Conclusions The application of genetic factor analytic model for temperament measures provided a new approach to unravel the complexity of animal behaviors. In summary, we contend that FPSS measures could increase the efficiency of genetic selection by providing automatic, objective, and consistent phenotyping measures with a lower cost, and may potentially become an alternative of DS which has been widely used in beef production.CFAConfirmatory Factor AnalysisCGRECCentral Grasslands Research Extension CenterCVSSDCoefficient of Variation of SSDDSDocility ScoreEFAExploratory Factor AnalysisFPSSFour-platform Standing ScaleMCMCMarkov chain Monte CarloPCAPrincipal Component AnalysisPCsPrincipal ComponentsPSRFPotential Scale Reduction FactorQBAqualitative behavior assessmentSSDstandard deviation of total weight on FPSSTSTemperament Score ER -