5 resultados para yield components

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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This study evaluated the yield, components of production and oil content of two castor bean cultivars through drip irrigation with different water depths. The research was conducted in 2009 in an Oxisol clay in the experimental field in Dourados, Mato Grosso do Sul State. The experimental design was randomized blocks in factorial scheme with five water depths (0, 25, 50, 100 and 150% of evapotranspiration for drip irrigation) in two castor bean cultivars (IAC 2028 and IAC 80) with four replications. The irrigation schedule was predetermined up to two irrigations per week except on rainy days. The increase of irrigation provided significant increase in most components of production and crop yield without changing the oil content of seeds. The application of higher water depth increased yield by 80% in relation to the treatment that received no supplemental irrigation.

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Genotypic, phenotypic and environmental correlations were estimated for all possible pairs among eleven characters of tomatoes. Fifteen treatments including five parents and ten hybrids of Instituto Agronômico (IAC) tomato breeding program were evaluated using a randomized complete block experimental design, with tree replications in Itatiba, São Paulo state, Brazil, during 2005/2006. The following traits were evaluated: fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW), cluster number per plant (CN), fruit number per cluster (FC), number of locules per fruit (NL), fruit length (FL), fruit width (WI), fruit wall thickness (FT), total soluble solids (SS), and total titratable acidity (TA). The genotypic (rG), phenotypic (rF) and environmental correlations (rA) for two pairs of plant traits were estimated using the Genes© program. High similarity was found among the estimates of genotypic and phenotypic correlations. Positive and high phenotypic and genotypic correlations were observed between FP and the traits FN, FW and FT, and these associations contributed for yield increasing. FW and FT contributed to yield increase and should be considered together as primary yield components in tomato. Positive values of the genotypic and phenotypic correlations revealed that FP influenced FN with high direct effect and significant positive correlation. These traits may be included as the main selection criteria for tomato yield improvement.

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The general combining ability (GCA), specific combining ability (SCA), and heterosis were studied in a complete diallel cross among fresh market tomato breeding lines with reciprocal excluded. Fifteen genotypes (five parents and ten hybrids) were tested using a randomized complete block design, with three replications, and the experiments were conducted in Itatiba, São Paulo state, Brazil, in 2005/06. The yield components evaluated were fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW); cluster number per plant (CN); fruit number per cluster (FC), fruit wall thickness (FT) and number of locules per fruit (NL). Fruit quality components evaluated were total soluble solids (SS); total titratable acidity (TA); SS/TA ratio, fruit length (FL); fruit width (WI); length to width ratio (FL/WI). The data for each trait was first subjected to analysis of variance. Griffing's method 2, model 1 was employed to estimate the general (GCA) and specific (SCA) combining abilities. Parental and hybrid data for each trait were used to estimate of mid-parent heterosis. For plant fruit yield, IAC-2 was the best parental line with the highest GCA followed by IAC-4 and IAC-1 lines. The hybrids IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-4 showed the highest effects of SCA. High heterotic responses were found for fruit yield and plant fruit number with values up to 49.72% and 47.19%, respectively. The best hybrids for fruit yield and plant fruit number were IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-5, for fruit yield and plant fruit number, the main yield components.

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A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

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The objectives of the present study were to determine if variance components of calving intervals varied with age at calving and if considering calving intervals as a longitudinal trait would be a useful approach for fertility analysis of Zebu dairy herds. With these purposes, calving records from females born from 1940 to 2006 in a Guzerat dairy subpopulation in Brazil were analyzed. The fixed effects of contemporary groups, formed by year and farm at birth or at calving, and the regressions of age at calving, equivalent inbreeding coefficient and day of the year on the studied traits were considered in the statistical models. In one approach, calving intervals (Cl) were analyzed as a single trait, by fitting a statistical model on which both animal and permanent environment effects were adjusted for the effect of age at calving by random regression. In a second approach, a four-trait analysis was conducted, including age at first calving (AFC) and three different female categories for the calving intervals: first calving females; young females (less than 80 months old, but not first calving); or mature females (80 months old or more). Finally, a two-trait analysis was performed, also including AFC and Cl, but calving intervals were regarded as a single trait in a repeatability model. Additionally, the ranking of sires was compared among approaches. Calving intervals decreased with age until females were about 80 months old, remaining nearly constant after that age. A quasi-linear increase of 11.5 days on the calving intervals was observed for each 10% increase in the female's equivalent inbreeding coefficient. The heritability of AFC was 0.37. For Cl. the genetic-phenotypic variance ratios ranged from 0.064 to 0.141, depending on the approach and on ages at calving. Differences among genetic variance components for calving intervals were observed along the animal's lifetime. Those differences confirmed the longitudinal aspect of that trait, indicating the importance of such consideration when accessing fertility of Zebu dairy females, especially in situations where the available information relies on their calving intervals. Spearman rank correlations among approaches ranged from 0.90 to 0.95, and changes observed in the ranking of sires suggested that the genetic progress of the population could be affected by the approach chosen for the analysis of calving intervals. (C) 2012 Elsevier ay. All rights reserved.