Diallel analysis of maize inbred lines for grain yield, oil and protein content

Werle, Amir José Klein; Ferreira, Fernando Rafael Alves; Pinto, Ronald José Barth; Mangolin, Claudete Aparecida; Scapim, Carlos Alberto; Gonçalves, Leandro Simões Azeredo

doi:10.1590/s1984-70332014000100004

Cited by 21 publications

(19 citation statements)

References 11 publications

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“…Use of 9 Effects of pollination treatments on genetic estimations in maize gene actions were not affected to any great extent by the pollination treatments; whereas non-additive gene actions showed significant changes in some of the tested plant material. Our figures for GCA and SCA were in agreement with other studies for kernel yield/ plant, while they were beyond the limit for protein, oil and carbohydrate content (Khadzhihov et al, 1978;Lorencetti et al, 2005;Balcı & Turgut, 2006;Aliu et al, 2008;Werle et al, 2014). This is because the parents we used, such as IHO, IHP and HYA, had higher values for oil and protein than parents used in those studies.…”

Section: Discussionsupporting

confidence: 91%

“…Oliveira et al (2006) and Okporie et al (2014) used controlled pollination to restrict pollen contamination in diallel experiments conducted for only kernel quality traits. In other studies, no information is provided about the pollination treatment or consideration was not given to pollen contamination (Balcı & Turgut, 2006;Abou-Deif et al, 2012;Mahesh et al, 2013;Werle et al, 2014). Considering the conflicting results obtained from previous studies, and the presence of a variety of choices about pollination method, there is clearly a need for detailed investigation into the effect of different pollination methods in diallel experiments.…”

Section: Observed Traitsmentioning

confidence: 99%

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Effects of open- and self-pollination treatments on genetic estimations in maize diallel experiment

Kahrıman

Egesel

Zorlu

2015

Span. j. agric. res.

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This study investigated the effects of open-and self-pollination treatments on genetic estimations and kernel biochemical content in a maize diallel experiment. A 7×7 complete reciprocal diallel set (7 parents and 42 hybrids) was used as plant material. Measured traits were: kernel weight per plant, protein content, oil content and carbohydrate content. General combining ability (GCA), specific combining ability (SCA), maternal effects (MAT), non-maternal effects (NMAT) and heterosis values were compared in open-and self-pollination treatments for measured traits. Results showed that the pollination treatments had a significant effect on all investigated traits. Parental lines and hybrid combinations gave different responses. Parents had relatively higher protein and oil content in self-pollination but hybrids had lower values in self-pollination compared with open-pollination. A considerable number of genotypes showed significant differences for genetic estimations (GCA, SCA, MAT, NMAT) and heterosis between open-and self-pollination treatments. Overall, findings suggest that evaluation of kernel quality traits should be made on selfed ear samples; however, evaluation for yield should be carried out on open-pollinated samples.Additional key words: protein; oil; carbohydrate content; pollen effect; Zea mays

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Section: Discussionsupporting

confidence: 91%

Section: Observed Traitsmentioning

confidence: 99%

Effects of open- and self-pollination treatments on genetic estimations in maize diallel experiment

Kahrıman

Egesel

Zorlu

2015

Span. j. agric. res.

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“…When this type of interaction exists, it presupposes that there is a variation between the same genotypes in different environments and is directed toward a particular selection. In this case, it probably resulted from the significant effect of SCA × E; assuming that the hybrids showed greater differences than the parents in the evaluated environments, an individual GCA and SCA analysis is therefore required for each environment (Werle et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

An accurate prediction of maize crosses using diallel analysis and best linear unbiased predictor (BLUP)

Oliveira

Buzinaro

Revolti

et al. 2016

Chilean J. Agric. Res.

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A major obstacle in corn (Zea mays L.) breeding programs is how to obtain strains which, when combined, ensure increased productivity in all crop characteristics. Therefore, the objective of this study was to evaluate the prediction efficiency of hybrid maize using diallel analysis and the best linear unbiased predictor (BLUP). Eight synthetic varieties were sown in a diallel scheme and the hybrid and their parents were then evaluated in three separate environments; both combining ability and predicted breeding values (BLUPs) were estimated. Correlations between the BLUP and combining abilities were also obtained. Combining ability analysis revealed that both additive and non-additive types of gene action were important in the studied traits. There was a moderate to high correlation between the mean square of the combining ability and the predicted breeding values. This shows that BLUP can be used to select the best parents for different traits, especially for ear height and ear position, which had the highest correlations. The parent VAR-01 had significant general combining ability (GCA) values, and it can be used in crosses to reduce plant height, ear height, and ear position while the parent VAR-06 can participate in crosses to increase ear height, plant height, and ear position. The result obtained for combining ability was moderately to highly consistent with BLUP results, but selection must be carefully undertaken.

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“…Twelve parental lines of sweet corn of an elite line group of the Maringá State University and Syngenta Seeds Ltd. (Werle et al 2014) were genetically evaluated with 20 SSR markers obtained from the Maize Genetic Data Bank (http:// www.maizegdb.org) ( Table 1). The genomic DNA was extracted using the protocol described by Gawel and Jarret (1991) with minor modifications, in young leaves from agricultural fields in Cascavel and Mauá da Serra, Paraná State of Brazil.…”

Section: Methodsmentioning

confidence: 99%

SSR-based genetic analysis of sweet corn inbred lines using artificial neural networks

Ferreira

Scapim

Maldonado

et al. 2018

Crop Breed. Appl. Biotechnol.

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Diallel analysis of maize inbred lines for grain yield, oil and protein content

Abstract: -

Cited by 21 publications

References 11 publications

Effects of open- and self-pollination treatments on genetic estimations in maize diallel experiment

Effects of open- and self-pollination treatments on genetic estimations in maize diallel experiment

An accurate prediction of maize crosses using diallel analysis and best linear unbiased predictor (BLUP)

SSR-based genetic analysis of sweet corn inbred lines using artificial neural networks

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