Path analysis of iron and zinc contents and others traits in cowpea

Moura, Jeane de Oliveira; Rocha, M. de M.; Gomes, Regina Lúcia Ferreira; Filho, F. R. Freire; Damasceno‐Silva, Kaesel Jackson; Ribeiro, V. Q.

doi:10.1590/s1984-70332012000400003

Cited by 20 publications

(21 citation statements)

References 12 publications

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“…Our results support this association in general, although some genotypes with a smooth testa texture and a large seed size had a shorter cooking time. As Moura et al (2012) suggested that crude protein content and cooking time were not correlated in their analysis with 11 populations, we found no clear correlation in the 20 genotypes. They also reported a negative correlation between crude protein content and grain size, but we found no relationship between crude protein and any grain size parameter in the 240 or 20 genotypes.…”

Section: Discussioncontrasting

confidence: 78%

Genetic diversity of physical, nutritional and functional properties of cowpea grain and relationships among the traits

Muranaka

Shono

Myoda

et al. 2015

Plant Genet. Resour.

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Cowpea is traditionally important as an affordable source of protein and minerals and of cash income in sub-Saharan Africa, especially for small-scale farmers who have limited options for food and cash crops. The development and deployment of cowpea varieties with improved nutrition and quality that meet the needs of farmers and consumers should enhance cowpea consumption and production in the region. We have identified genetic diversity in various grain quality-related traits of cowpea and relationships among the traits. Wide genetic variation and strong correlations among crude protein, Fe and Zn contents suggest the possibility of improving the concentrations of these nutritional factors simultaneously. Low associations among physical and nutritional properties of grain indicate the possibility of introgressing favorable traits utilizing identified genetic resources. However, narrow variation in amino acid (AA) composition suggests a lesser possibility of improving the contents of specific AAs in cowpea, but it gave a reliable nitrogen-to-protein conversion factor of 5.45 for the estimation of crude protein content. Several improved breeding lines were identified with low concentrations of flatulence-causing oligosaccharides and various favorable agronomic traits and nutrient contents. TVu-12802 had the highest contents of crude protein and high contents of micronutrients, with a low ratio of phytic acid to Fe and Zn contents.

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Section: Discussioncontrasting

confidence: 78%

Genetic diversity of physical, nutritional and functional properties of cowpea grain and relationships among the traits

Muranaka

Shono

Myoda

et al. 2015

Plant Genet. Resour.

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“…OM, overall mean, ns not significant, **significant at 1%, and 1 value transformed to The low magnitude of g 2 for iron and zinc concentrations indicates the existence of high environmental influence, which makes it more difficult to select iron and zinc concentrations in the cowpea grain, also confirmed by low Snedecor's F values and estimates of g 2 that were not significant (Table 1). The low magnitude of g 2 and high environmental influence for these characters were also found by Moura et al (2012) and Costa (2013), who evaluating cowpea parental and crosses also found low estimates for this parameter.…”

Section: Resultssupporting

confidence: 65%

“…The eight segregating populations were represented by plants in the F 3 (plant)/F 4 (seed) generations, obtained from the BRS Xiquexique x IT-98K-205-8 and BRS Xiquexique x IT-97K-1042-3 crosses (C) and backcrosses (BC) to the BRS Xiquexique parent, including reciprocal ones (Moura et al, 2012). …”

Section: Methodsmentioning

confidence: 99%

Research Article Genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses using mixed models.

Oliveira¹,

Rocha²,

Damasceno‐Silva³

et al. 2017

Genet. Mol. Res.

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ABSTRACT. The aim of this study was to estimate the genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses and to compare different selection indexes. Eleven cowpea populations were evaluated in a randomized complete block design with four replications. Fourteen traits were evaluated, and the following parameters were estimated: genotypic variation coefficient, genotypic determination coefficient, experimental quality indicator and selection reliability, estimated genotypic values -BLUE, genotypic correlation coefficient among traits, and genotypic gain with simultaneous selection of all traits. The genotypic gain was estimated based on tree selection indexes: classical, multiplicative, and the sum of ranks. The genotypic variation coefficient was higher than 2 D.G. Oliveira et al. Genetics and Molecular Research 16 (3): gmr16039736the environmental variation coefficient for the number of days to start flowering, plant type, the weight of one hundred grains, grain index, and protein concentration. The majority of the traits presented genotypic determination coefficient from medium to high magnitude. The identification of increases in the production components is associated with decreases in protein concentration, and the increase in precocity leads to decreases in protein concentration and cooking time. The index based on the sum of ranks was the best alternative for simultaneous selection of traits in the cowpea segregating populations resulting from the crosses and backcrosses evaluated, with emphasis on the F 4 BC 12 , F 4 C 21 , and F 4 C 12 populations, which had the highest genotypic gains.

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“…If the CN is 100-1000, multicollinearity is considered moderate to severe, and if CN ≥ 1000, it is considered severe (Moura et al, 2012).…”

Section: Methodsmentioning

confidence: 99%

“…The technique, introduced by Wright (1921Wright ( , 1923 and described in detail by Li (1956Li ( , 1975, identifies miscorrelations between two traits that may not necessarily be related by direct cause-andeffect, because of the influence of a third trait. Path analysis has been widely used by plant breeders in a variety of crops, e.g., soybean (Peter et al, 2014), corn (Faria et al, 2015), common bean (Cabral et al, 2011), green bean (Araujo et al, 2012), cowpea (Moura et al, 2012;Santos et al, 2014), rice (Marchezan et al, 2005), wheat (Kavalco et al, 2014), cotton (Hoogerheide et al, 2007;Farias et al, 2016), sweet sorghum (Lombardi et al, 2015), and sugarcane (Saccharum officinarum) (Kang et al, 1983;Reddy and Reddy, 1986;Sukhchain and Sain, 1997;Ferreira et al, 2007;Silva et al, 2009;Souza et al, 2011;Esposito et al, 2012). However, studies of this nature are still necessary, because different population structures, environments, and management strategies should be considered.…”

Section: Introductionmentioning

confidence: 99%

Early selection of sugarcane using path analysis

et al. 2017

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ABSTRACT. The aim of this study was to analyze sugarcane (Saccharum officinarum) biometric and technological data, obtained at different timepoints, using path analysis. The experiment was conducted in União, PI, Brazil, and evaluated 12 sugarcane genotypes (RB036066, RB9438, RB935744, RB021764, RB021754, RB021534, RB966229, RB977540, RB863129, and RB987935, and the varieties RB92579 and RB867515 as controls) in a randomized block design with four replications. Data were collected at six timepoints that were spaced 30 days apart (90, 120, 150, 180, 210, and 240 days). Direct and indirect effects of the following production components were compared: stalk length, stalk diameter, internode length, number of tillers, number of green leaves, and stalk dry matter. The technological variables evaluated were total recoverable sugar, degrees Brix, tons of polarization (pol, apparent sucrose content) per hectare, juice purity, fiber, juice pol, and tons of sugarcane per hectare. The coefficients of determination were 2 R.P. Barbosa et al. Genetics and Molecular Research 16 (1): gmr16019038 high in all path analyses, suggesting that the components evaluated explained a large part of the variation in stalk production and in the technological variables. Stalk diameter was the trait that best correlated with stalk dry matter yield at all timepoints, with positive values that were higher than the residual effect. This demonstrates the possibility of obtaining significant gains via indirect selection for stalk dry matter yield via stalk diameter or via stalk diameter and number of tillers. The technological variables degrees brix and juice pol were the traits that best correlated with total recoverable sugar production, indicating that they could be used to indirectly select for total recoverable sugar.

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Path analysis of iron and zinc contents and others traits in cowpea

Abstract: Abstract

Cited by 20 publications

References 12 publications

Genetic diversity of physical, nutritional and functional properties of cowpea grain and relationships among the traits

Genetic diversity of physical, nutritional and functional properties of cowpea grain and relationships among the traits

Research Article Genotypic gain with simultaneous selection of production, nutrition, and culinary traits in cowpea crosses and backcrosses using mixed models.

Early selection of sugarcane using path analysis

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