naa a22 4500 510730361 CHVBK 20180411082950.0 cr unu---uuuuu 180411e20131201xx s 000 0 eng 10.1007/s11295-013-0648-2 doi (NATIONALLICENCE)springer-10.1007/s11295-013-0648-2 An assessor-specific Bayesian multi-threshold mixed model for analyzing ordered categorical traits in tree breeding [Elektronische Daten] [Eduardo Cappa, Luis Varona] Many traits of biological interest in tree breeding are assessed using more than two ordered discrete categories. These scores have a more or less arbitrary and subjective assignment by the assessors, which could lead to a strong departure from the Gaussian distribution. Different assessors may also use different regions of the available scale. This study describes the use of the multi-threshold mixed model proposed by Varona et al. (J Anim Sci 87:1210-1217, 2009), which allows different thresholds for different assessors on an underlying Gaussian distribution. This method was applied to a six-point score for stem quality in an open-pollinated progeny trial of Prosopis alba Griseb. Four mixed models were used: (1) a linear mixed model with observed score (LMM); (2) a linear mixed model with transformed "normal scores” (LMM_NS); (3) a threshold mixed model (TMM); and (4) an assessor-specific multi-threshold mixed model (MTMM). Dispersion parameters were estimated using Bayesian techniques via the Gibbs sampling with a data augmentation step. The proposed MTMM produced higher posterior mean heritabilities (0.096) than the commonly used LMM (0.077). Posterior mean heritabilities from LMM_NS (0.094) and TMM (0.097) were comparable to those obtained using MTMM; however, MTMM yielded slightly more precise estimates than TMM. Although correlations of the estimated breeding values were high between different models (from 0.88 to 0.99), the heterogeneity in the estimated posterior means of the thresholds between the three assessors caused notable changes in the top 10 families between TMM and MTMM. The proposed model is helpful in fitting subjective ordered categorical traits assessed by different assessors in tree breeding. Springer-Verlag Berlin Heidelberg, 2013 Ordered categorical traits nationallicence Assessor nationallicence Multi-threshold mixed model nationallicence Bayesian inference nationallicence Tree breeding nationallicence Cappa Eduardo Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Recursos Biológicos, De Los Reseros y Dr. Nicolás Repetto s/n, 1686, Hurlingham, Buenos Aires, Argentina aut Varona Luis Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain aut Tree Genetics & Genomes Springer Berlin Heidelberg 9/6(2013-12-01), 1423-1434 1614-2942 9:6<1423 2013 9 11295 https://doi.org/10.1007/s11295-013-0648-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11295-013-0648-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cappa Eduardo Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Recursos Biológicos, De Los Reseros y Dr. Nicolás Repetto s/n, 1686, Hurlingham, Buenos Aires, Argentina aut NATIONALLICENCE 700 1- Varona Luis Unidad de Genética Cuantitativa y Mejora Animal, Universidad de Zaragoza, 50013, Zaragoza, Spain aut NATIONALLICENCE 773 0- Tree Genetics & Genomes Springer Berlin Heidelberg 9/6(2013-12-01), 1423-1434 1614-2942 9:6<1423 2013 9 11295 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer