Sour passion fruit breeding: Strategy applied to individual selection in segregating population of Passiflora resistant to Cowpea aphid-born mosaic virus (CABMV)
2016
de Oliveira Freitas, Jôsie Cloviane | Pio Viana, Alexandre | Santos, Eileen Azevedo | Paiva, Claudia Lougon | de Lima e Silva, Fernando Higino | Souza, Margarete Magalhães
The Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) method has been widely used in plant breeding programs, since besides estimating and predicting the genetic values, it takes into account several experimental designs. Therefore, this study aimed to estimate genetic parameters and predict gain via selection in a segregating population derived from interspecific crosses of Passiflora. Five quantitative characteristics of fruit were evaluated in 77 individuals during two growing seasons, through the REML/BLUP methodology. The experiment was arranged in an incomplete block design with two replications. Both individual and within plot heritabilities presented the highest values for number of fruits (0.32 and 0.30, respectively) and pulp mass (0.30 and 0.46, respectively), which favors gains in both yield and pulp yield. The 30 best genotypes for each evaluated trait were selected. The genetic correlation between harvests was less than the unity, for all the characteristics observed, which indicates different genetic control in different harvests. Progenies 5 and 9 were considered the most promising due to their higher percentage of selected genotypes over the harvest seasons for the traits number for fruits, pulp mass and production, with 50, 47 and 28%, respectively. The genotypes H5-1, H9-11, H9-57 and H2-20 stood out over the harvest seasons as the best individuals for number for fruits, yield and pulp mass and,therefore, are the best suited for being used as parents in backcrosses with sour passion fruit.
Mostrar más [+] Menos [-]Palabras clave de AGROVOC
Información bibliográfica
Este registro bibliográfico ha sido proporcionado por National Agricultural Library