Alface ( Lactuca sativa L.) is a leafy vegetable worldwide consumed. It is found in its constitution vitamins and minerals, as well as bioactive compounds, such as phenolic compounds, flavonoids and anthocyanins. Since anthocyanins are responsible for the red color of the leaves and in the body prevents the appearance of non-communicable chronic diseases by the fight against free radicals. The lettuce for being present in the diet of the population becomes a promising plant for biofortification with the selection of plants with high levels of anthocyanins. The objective of the present work was to study the quantitative distribution of anthocyanin in leaves of lettuce plants of a segregating F2 population obtained from the initial crossing between two color contrasting parents (green and red).. The color, anthocyanin and flavonoid contents, as well as color correlation with anthocyanin content and the heritability of these characteristics. It was concluded that the anthocyanin content in leaves of lettuce is controlled by more than one gene with partial dominance of the genes that confer higher levels. Intense red coloration can be used as an alternative in lettuce breeding programs to identify superior lettuce genotypes with high anthocyanin content. Transgressive segregation as well as the higher heritability values observed in the studied traits will allow selecting in segregating generations, superior genotypes in accordance with the proposed objectives.

The objective of this work was to estimate the optimal number of harvests for the reliable selection of zucchini (Cucurbita pepo) hybrids through the repeatability coefficient. The experimental design was randomized complete blocks with 33 treatments (31 experimental hybrids and 2 commercial ones) and four replicates, with six plants per plot. Fifteen harvests were carried out. Seven morphoagronomic fruit characteristics were evaluated, and repeatability coefficients were estimated using four statistical methods. The repeatability coefficients ranged from low to moderate, regardless of the studied characteristic. For a high-precision selection (R2≥90%), a high number of evaluated harvests was required, especially for traits related to fruit yield, as follows: 30 to 54 harvests for selection based on total yield; and 43 to 83 harvests for commercial yield, which varied according to the statistical estimation method. The principal component analysis based on the covariance matrix required the least number of harvests for a satisfactory selection precision. Fifteen harvests are sufficient for a satisfactory selection of all evaluated characteristics, with a precision above 70%.

The growing consumer demand for sweet potato roots results in the need for genotypes with higher yields and better root quality. Thus, the objective of this study was to agronomically evaluate sweet potato genotypes via mixed models to select superior genotypes for human consumption and predict their selection gains. The study had a partially balanced triple lattice design with three replicates.As treatments, 92 sweet potato genotypes from the Universidade Federal de Lavras germplasm bank selected in the first selection cycle were evaluated along with eight controls, namely,