Ação de herbicidas inibidores da PROTOX sobre o desenvolvimento, acamamento e produtividade da soja

Gallon, Mônica da Silva; Buzzello, Gederson Luiz; Trezzi, Michelangelo Müzell; Diesel, Francielli; Silva, Henrique Luis da

doi:10.7824/rbh.v15i3.471

Cited by 5 publications

(11 citation statements)

References 8 publications

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“…Factors 3 and 4 had the effect of reducing the PHM. This character has a high positive correlation with lodging (L), already reported by Gallon et al (2016), Degrees of freedom (DF); ns not significant, * significant at 5% and ** significant at 1% of probability by F test. Number of days for flowering (NDF in days), grain filling period (GP in days), number of days to maturity (NDM in days), plant height at maturity (PHM in cm), lodging (L in notes), leaf retention (LR in notes), agronomic value (AV in notes), grain yield (GY in g), healthy seeds weight (HSW in g) and weight of one hundred seeds (WHS in g).…”

Section: Resultsmentioning

confidence: 56%

Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

Bermudez

Pinheiro

2020

Bragantia

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Stink bugs that affect soybeans are responsible for significant losses in seed production, quality and germination potential, in addition to hindering the mechanized harvest. To develop insect resistant materials, the breeder can compile a selection index by factor analysis. Therefore, the objective of this work was to validate the use of factor analysis, by means of its estimated gains, for the selection of highly productive and stink bugs resistant genotypes in two soybean segregating populations. For this, the phenotypic evaluation was performed in the generation F 2:3 , in two distinct experiments, being the populations from the crosses between IAC-100 × PI 295952 and IAC-100 × PI 306712. The experiments were installed in an 18 × 9 alpha-lattice design, with three replicates for each population. Agronomic and resistance characters were evaluated. The factorial scores for each character were obtained for the creation of "supercharacters". These were designed to check if the selection in the new characters could provide satisfactory simultaneous gains in the original characters. Subsequently, the analysis of variance was performed for all factors, in both populations. The F test showed the presence of variability among genotypes, allowing the selection of superior genotypes. None of the factors selected progenies with all the characters favorably, and their use was not interesting for both populations. With this, complementary studies should be performed with other selection indices in these populations.

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Section: Resultsmentioning

confidence: 56%

Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

Bermudez

Pinheiro

2020

Bragantia

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“…Soybean is the most important legume species in the world (Gallon et al, 2016) and it stands out in the Brazilian agribusiness for its high productive potential in different regions (Cruz et al, 2016). Soybean is widely used for the elaboration of animal feed and oil and as Ávila & Albrecht (2010) explained, it has been emphasized as an alternative in the prevention of diseases and in human food, being able to be transformed into several protein foods.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Spatial Linear Model of Soybean Yield Using Bootstrap Methods

et al. 2018

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This study aims to quantify the uncertainties associated to the parameters of a Gaussian spatial linear model (GSLM) and the assumption of normality residuals in the modeling of the spatial dependence of the soybean yield as a function of soil chemical attributes. The spatial bootstrap methods were used to determine the point and interval estimators associated with the model parameters. Hypothesis tests were carried out on the significance of the model parameters and the quantile-quantile probability plot was elaborated to verify the data normality. The uncertainties associated to the parameters of the spatial dependence structure were quantified and the potassium content, phosphorus content and soil pH covariates were significant to explain the soybean yield mean. These covariates were used in the elaboration of a new model, which provided the elaboration of a contour map of soybean yield. Analysis of the quantile-quantile plot indicated that soybean yield data follow a normal probability distribution.

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“…Its high protein content allows it to have multiple applications in human and animal feeding, being of great socioeconomic importance for Brazilian agribusiness due to its high productive potential (Cruz et al, 2016;Gallon et al, 2016). The productive chain of Brazilian soy has undergone modernization processes, which provide the increase in grain yield (Zuffo et al, 2015a).…”

Section: Introductionmentioning

confidence: 99%

Path Analysis in Soybean Cultivars Grown under Foliar Spraying and Furrow Inoculation with Azospirillum brasilense

Zuffo¹,

Júnior²,

Fonseca³

et al. 2017

JAS

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The objective of this study was to evaluate, through path analysis, the influence of agronomic characters as a function of foliar spraying and furrow inoculation by Azospirillum brasilense on soybean yield. Two experiments were conducted in the crop years of 2013/14 and 2014/15, grown in Lavras, Minas Gerais. In the first experiment, the experimental design was a randomized block in a factorial 4 × 6, four cultivars (Anta 82 RR ) and two treatments with A. brasilense (inoculated and non-inoculated) with three replications. For both experiments, it was established plant height, phytomass of the aerial part, plant height at harvest, first legume insertion, number of legumes, number of grains per legume, mass of one thousand grains and grain yield. In the study with foliar spraying of soybean with A. brasilense, plant height at harvest was the only variable that had a direct effect on soybean grain yield. As such, in the study with furrow inoculation of A. brasilense in soybean, plant height at harvest and number of vegetables were the variables with the greatest direct effects on soybean grain yield.

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Ação de herbicidas inibidores da PROTOX sobre o desenvolvimento, acamamento e produtividade da soja

Cited by 5 publications

References 8 publications

Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

Selection to high productivity and stink bugs resistance by multivariate data analyses in soybean

Gaussian Spatial Linear Model of Soybean Yield Using Bootstrap Methods

Path Analysis in Soybean Cultivars Grown under Foliar Spraying and Furrow Inoculation with Azospirillum brasilense

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