Selection via simulated individual BLUP based on family genotypic effects in sugarcane

The objective of this work was to propose a new selection strategy for the initial stages of sugarcane improvement, based on the methodology 'simulated individual BLUP (BLUPIS)', which promotes a dynamic allocation of individuals selected in each full-sib family, using BLUP as a base for both the genotypic effects of the referred families and plot effects. The method proposed applies to single full-sib families or those obtained from unbalanced or balanced diallel crosses, half-sib families and self-pollinated families. BLUPIS indicates the number of individuals to be selected within each family, the total number of clones to be advanced, and the number of families to contribute with selected individuals. Correlation between BLUPIS and true BLUP was 0.96, by method validation. Additionally, BLUPIS allows the identification of which replication contains the best individuals of each family.

Sample size for full-sib family evaluation in sugarcane

The objective of this study was to determine the minimum number of plants per plot that must be sampled in experiments with sugarcane (Saccharum officinarum) full-sib families in order to provide an effective estimation of genetic and phenotypic parameters of yield-related traits. The data were collected in a randomized complete block design with 18 sugarcane full-sib families and 6 replicates, with 20 plants per plot. The sample size was determined using resampling techniques with replacement, followed by an estimation of genetic and phenotypic parameters. Sample-size estimates varied according to the evaluated parameter and trait. The resampling method permits an efficient comparison of the sample-size effects on the estimation of genetic and phenotypic parameters. A sample of 16 plants per plot, or 96 individuals per family, was sufficient to obtain good estimates for all traits considered of all the characters evaluated. However, for Brix, if sample separation by trait were possible, ten plants per plot would give an efficient estimate for most of the characters evaluated.