ABSTRACT. The aim of this study was to evaluate a diallel of maize hybrids for traits related to forage production and nutritional value. Six commercial hybrids were used as parents. The crosses were made according to a complete diallel design, obtaining the F1 and reciprocal crosses. The evaluations were performed in the main and second crop seasons in the 2010/2011 crop year at the Center for Technological Development in Agriculture of the Federal University of Lavras, located in Lavras, Minas Gerais State, Brazil. The experimental precision indicated by the coefficient of variation was good for all the traits measured. Significant differences were not observed among the crosses for traits related to the nutritional value of the forage. For fresh matter yield and dehusked ear yield, the general combining ability (GCA) and specific combining ability (SCA) effects were significant. Sowing in the second crop season reduced the yield and nutritional value of the forage. The interaction among the crosses and sowing seasons was not significant. For the beginning of an intrapopulational breeding program, the parent BM 3061 stands out by showing high estimates of GCA for the grain and forage yields.

The aim of this study was to estimate the repeatability of some phenotypic stability parameters: reliability index (I), regression coefficient (b 0 e b 1), ecovalence, and the mean of the absolute scores (MAS), and to check the implications of estimating stability parameters using a reduced number of environments. A dataset comprising 25 common bean lines assessed in 36 environments was used. These environments comprise different locations, sowing seasons, and years. Different experimental groups, from three to 18 environments, were simulated. For each group, analysis of variance was performed and the stability parameters were estimated. The greater repeatability estimates were observed for the mean (b 0), followed by the I and b 1. Ecovalence and MAS had the lowest values for the repeatability estimates, which is not desirable for breeding programs aiming at selection for high stability. The phenotypic stability parameter should not be estimated from fewer than 12 environments.

The success of any forestry operation depends on the careful choice of the clones to be planted. At existing yield levels, the differences among clones are becoming smaller, leading to the need to use experimental strategies for a more successful choice. To obtain information in regard to better experimental strategies, data from two clonal tests of eucalyptus were used. One of the tests consisted of 35 clones and another of 48 clones. In both tests, the experimental plot consisted of 100 plants at commercial spacing (12 m2 per plant). The trait wood volume was evaluated, taking the relative position of the plant in the plot as a reference. The data were evaluated by different means, and it was observed that the use of border plot in clonal tests in eucalyptus is not necessary. Experimental accuracy with 15 to 20 plants is similar in comparison to the plot with 100 plants.

The purpose of this study was to identify the ideal sample size representing a family in its potential, to identify superior families and, in parallel, determine in which spatial arrangement they may have a better accuracy in the selection of new varieties of sugarcane. For such purpose, five families of full-sibs were evaluated, each with 360 individuals, in the randomized blocks design, with three replications in three different spacing among plants in the row (50 cm, 75 cm, and 100 cm) and 150 cm between the rows. To determine the ideal sample size, as well as the better spacing for evaluation, the bootstrap method was adopted. It was observed that 100 cm spacings provided the best average for the stalk numbers, stalk diameter and for estimated weight of stalks in the stool. The spacing of 75 cm between the plants allowed a better power of discrimination among the families for all characters evaluated. At this 75 cm spacing  was also possible to identify superior families with a sample of 30 plants each plot and 3 reps in the trial. Highlights The bootstrap method was efficient to determine the ideal sample size, as well as the best spacing for evaluation. The 75-cm spacing had the highest power of discrimination among families, indicating that this spacing is the most efficient in evaluating sugarcane families for selection purposes. From all the results and considering selective accuracy as the guiding parameter for decision making, the highest values obtained considering the number of stalks and weight of stalks in the stools were found at the 75-cm spacing.

For a reciprocal recurrent selection (RRS) program to succeed, it is essential to maintain genetic variability throughout the selection cycles and to obtain accurate estimates of genetic parameters, which in turn are directly related to the number of progenies and repetitions evaluated. This study evaluates the potential of maize progenies of the sixth cycle of RRS and proposes, using simulation methods, the ideal combination of the number of progenies and repetitions to employ in reciprocal full-sib recurrent selection. A total of 163 full-sib progenies were evaluated in a randomized block design with six repetitions. Based on the yield data, analysis of variance was carried out, and different scenarios were simulated using the Monte Carlo chain method. These scenarios varied in the number of repetitions (two, four, and six) and progenies (30 to 163). The contrast between progenies and controls was significant, revealing the potential of the progenies of the sixth cycle of RRS. The high magnitude of the selective accuracy (0.77) was reflected in high estimates of heritability, which allowed for efficient phenotypic selection, obtaining selection gains of 14.07%. From the estimates of phenotypic and genotypic variance, heritability, accuracy, and standard error, it was found that a repetition number above two results in drastic changes in the estimates of these parameters; however, with the use of 130 progenies, these estimates tend to stabilize, implying that a high number of progenies does not interfere decisively in the quality of most parameters, except for the limits of maximum and minimum variation.