Factor analysis applied to genome prediction for high-dimensional phenotypes in pigs.

The aim of the present study was to propose and evaluate the use of factor analysis (FA) in obtaining latent variables (factors) that represent a set of pig traits simultaneously, for use in genome-wide selection (GWS) studies. We used crosses between outbred F2 populations of Brazilian Piau X commercial pigs. Data were obtained on 345 F2 pigs, genotyped for 237 SNPs, with 41 traits. FA allowed us to obtain four biologically interpretable factors: ?weight?, ?fat?, ?loin?, and ?performance?. These factors were used as dependent variables in multiple regression models of genomic selection (Bayes A, Bayes B, RR-BLUP, and Bayesian LASSO). The use of FA is presented as an interesting alternative to select individuals for multiple variables simultaneously in GWS studies; accuracy measurements of the factors were similar to those obtained when the original traits were considered individually. The similarities between the top 10% of individuals selected by the factor, and those selected by the individual traits, were also satisfactory. Moreover, the estimated markers effects for the traits were similar to those found for the relevant factor.

Certificação socioambiental para a agricultura: desafios para o setor sucroalcooleiro.

Parte 1 Conceitos e aplicações: Fundamentos da Certificação, Luis Fernando Guedes Pinto e Laura de Santis Prada - Possibilidades na cana-de-açúcar, Luís Fernando Guedes Pinto, Laura de Santis Prada e Isabel Cristina Rodrigues. Parte 2: Perspectivas do Setor: Produção e suas alternativas, Francisco Alves e Tamás Szmrecsányi - Mercados de Açúcar Orgânico, Antonio Oswaldo Storel Júnior e Pedro Ramos. Parte 3: Desafios Socioambientais: Relações de Trabalho, Marcelo Paixão e Francisco Alves - Agroindústria e Meio-Ambiente, Daniel Bertoli Gonçalves, José Maria Gusman Ferraz e Tamás Szmrecsányi - Especificidades do Nordeste, Paulo José Adissi e Wagner Spagnul