Multiple-trait BLUP in longitudinal data analysis on Jatropha curcas breeding for bioenergy

Abstract

Abstract Despite being a species with great potential for biodiesel production, little research has been done on the breeding of Jatropha curcas, mainly with respect to its yield across harvests. Thus, the present study was carried out to analyze longitudinal data via multiple-trait Best Linear Unbiased Prediction (BLUP) for the genetic improvement of Jatropha curcas. The experiment was set up as a randomized block design with two blocks and five plants per plot. The seed yield of 730 individuals of 73 half-sib families was evaluated over six years. Variance components and genetic parameters were estimated via Restricted Maximum Likelihood (REML). The Additive Index was used for ranking and selection purposes. Genetic correlations of low to moderate magnitude were observed between pairs of harvests. The Multiple-trait BLUP / Additive Index procedure allowed for the selection of superior families based on the predicted genetic values, considering all the harvests. Therefore, it can be efficiently applied in the breeding of Jatropha curcas.