The aim of this study was to identify the traits that most affect production of sugarcane, fiber and lignin content (LIG) with a view toward optimizing the process of assessment and selection of families of energy cane. Fifty full-sibs families were assessed using an incomplete-block design, with five replications. The traits assessed were mean stalk height (SH), mean stalk diameter (SD), mean number of stalks per plant (NS), mean stalk weight (SW), fiber content (FIB), LIG, tons of cane per hectare (TCH), tons of fiber per hectare (TFH) and tons of lignin per hectare (TLH). Based on path analysis, it was possible to observe that the traits SW and NS, in that order, exhibited the greatest direct effects on TCH, TFH, and TLH. These traits they were indirectly affected to a greater degree by NS. The direct effects of FIB, LIG, SH, and SD on TCH, TFH, and TLH were smaller than the residual effects on the analyses carried out, showing their little importance in the selection process. The increase of TFH and TLH mainly occur due to greater biomass production, which is associated with greater tillering capacity and with the SW of the families. Thus, selection of families with greater FIB might not show genetic gains if the mean values for TCH of their offsprings are low. Therefore, selection of the best families for energy cane should be carried out based on TCH, which may be estimated by way of NS and SW.
The purpose of this study was to compare the method BLUPIS (best linear unbiased prediction individual simulated) with mass selection in terms of efficiency in identifying the best genotypes in sugarcane (Saccharum officinarum L.) families. Mass selection was performed by two breeders with 25 yr of experience. The BLUPIS procedure selected families with higher means for tons of cane per hectare (TCH) than the overall mean. The number of plants selected per family was calculated by nk=(trueg^k/trueg^i)ni, where ĝ indicates the genotypic value of the kth family; ĝ the genotypic value of the best family; and nj is equal to the number of plants selected in the best family, determined as nj = 45 in this study. Out of 20 best clones forwarded to the third test phase (T3), BLUPIS selected all in the first test phase (T1) and mass selection only two. Therefore, 100% of the clones in the second test phase (T2) had been selected by BLUPIS. The BLUPIS was most efficient in detecting the best genotypes, since all clones that were promoted up to phase T3 were descendants from the best families. The BLUPIS method should be applied in sugarcane breeding programs to ensure the selection of the best genotypes.
-The objective of this work was to evaluate the genetic diversity in a segregating population F3 of castor bean in the Recôncavo Baiano using the Ward-MLM multivariate technique. The experiment was conducted at the Universidade Federal do Recôncavo da Bahia between April 2009 and March 2010. The 259 genotypes used were derived from crosses between the BRS 149 Nordestina, BRS 188 Paraguaçu, EBDA MPA-17, Sipeal 28 and Mirante 10 varieties. The design was in randomized complete blocks with four replicates in spacing of 3x1 m. The number of days to the appearance of the first female flower, plant height (cm), number of racemes emitted per plant, total length of the raceme (cm), raceme weight (g), fruit weight per plant (g), number of seeds per raceme, number of seeds per plant, weight of seeds per raceme (g), productivity (kg ha -1) and oil content in seeds (%) were evaluated. The formation of four groups occurred as follows: Group I with 84 genotypes, Group II with 142 genotypes, Group III with 15 genotypes and Group IV with 18 genotypes. The Ward-MLM strategy allows for an appropriate clustering between the genotypes, and the variables that contribute most to the divergence are: fruit weight per plant, weight of seed per raceme, raceme weight and productivity. . O delineamento foi em blocos completos casualizados com quatro repetições num espaçamento de 3x1 m. Avaliouse o número de dias para o aparecimento da primeira flor feminina, estatura de planta, número de racemos emitidos, comprimento do racemo, peso de racemo, peso de fruto por planta, número de sementes por racemo, número de sementes por planta, peso de sementes por racemo, produtividade e teor de óleo na semente. Ocorreu a formação de quatro grupos, sendo o grupo I composto por 84 genótipos, o II por 142 genótipos, o III por 15 genótipos e o IV por 18. A estratégia Ward-MLM possibilitou um adequado agrupamento entre os genótipos, sendo que as variáveis que mais contribuíram para a divergência foram o peso de fruto por planta, peso de semente por racemo, produtividade e peso de racemo. Palavras-chave:Mamona. Plantas-melhoramento genético. Modelo de locação modificado.
The aim of this study was to evaluate the genetic diversity and coefficient of kinship in 50 sugarcane genotypes, in addition to identifying potential parents for obtaining cultivars of energy cane. Diversity analysis was carried out based on the evaluation of morphological and agronomical characteristics. The coefficient of kinship was obtained from information on pedigree. According to analyses carried out, genotypes were separated into two groups. Group G1 consisted of 13 genotypes from the species Saccharum spontaneum and Saccharum robustum. The other 37 genotypes were from back-crosses with Saccharum officinarum, and were allocated to group G2. The genotypes displayed low values for genetic similarity and coefficient of kinship, indicating broad genetic variability in the population. Carrying out crosses involving genotypes from group G1, especially those with a fibre content of over 17% (IJ76-293, 57NG12, IN84-82, IN84-88, IM76-228 and UM69/001), with genotypes from group G2 which have high stalk yield (RB92579,
-The aim of this research was to evaluate the consistency of path analyses in sugarcane experiments based on genetic, phenotypic and genotypic correlations. Forty-four analyses were made with a view toward quantifying the direct and indirect effects of stalk height (SH), stalk diameter (SD) and number of stalks (NS) on sugarcane weight (SW). NS had the greatest direct effect on SW in all the analyses with the use of genetic and phenotypic correlations and in 12 analyses with use of the genotypic correlations. SD had a high direct effect on SW, going beyond NS in only one experiment, while SH had the lowest direct effect on SW in most of the experiments. The results showed greater consistency with the use of genetic and phenotypic correlations. In the balanced experiments, the phenotypic and genetic correlations showed equivalent results. NS is the main determinant of changes in sugarcane production.
ABSTRACT. The use of efficient breeding methods depends on knowledge of genetic control of traits to be improved. We estimated genetic parameters, selection gain, and genetic diversity in physic nut half-sib families, in order to provide information for breeding programs of this important biofuel species. The progeny test included 20 halfsib families in 4 blocks and 10 plants per plot. The mean progeny heritability values were: 50% for number of bunches, 47% for number of fruits, 35% for number of seeds, 6% for stem diameter, 26% for number of primary branches, 14% for number of secondary branches, 66% for plant height, and 25% for survival of the plants, demonstrating good potential for early selection in plant height, number of branches, and number of fruits per plant. In the analysis of genetic diversity, genotypes were divided into 4 groups. Genotypes 18, 19, 20, and 8 clustered together and presented the highest means for the vegetative characters and production. Lower means were observed in the 17, 12, 13, and 9 genotypes from the same group. We detected genetic variability in this population, with high heritability estimates and accuracy, demonstrating the possibility of obtaining genetic gains for vegetative characters and production at 24 months after planting.
The objective of this research was to analyze the use of cultivar index selection (GARCIA, 1998) ELSTON (1963), MULAMBA & MOCK (1978), SCHWARZBACH (1972) and GARCIA (1998) GARCIA (1998) proved to be more effi cient than the other indexes, since it showed more correlation with PRODV and selected more productive strains. The recommended genotypes were: UENF 7-5-1 and UENF 7-6-1, followed by the genotypes
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