GGE Biplot Analysis for Combining Ability of Grain Yield and Early Maturity in Maize Mutant in Indonesia

Ruswandi, Dedi; Supriatna, Jajang; Waluyo, Budi; Makkulawu, Andi Takdir; Suryadi, Edy; Chindy, Z. U.; Ruswandi, S.

doi:10.3923/ajcs.2015.160.173

Cited by 15 publications

(16 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The genotype + genotype × environment (GGE) biplot analysis is the main method to demonstrate the combining abilities of parents and crosses. Thus, this method has commonly been used to evaluate combining abilities in maize breeding experiments in recent years (Mostavi et al, 2012;Badu-Apraku et al, 2013;Ruswandi et al, 2015). Additionally, the canonical discriminant analysis with yypothesis error (CDA-HE) plot has also been used to evaluate genotypes in breeding experiments for investigated traits (Egesel et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Comparison of graphical analyses for maize genetic experiments: Application of biplots and polar plot to line × tester design

Kahrıman

Egesel

Orhun

et al. 2016

Chilean J. Agric. Res.

View full text Add to dashboard Cite

Graphical techniques have become important tools to show results of maize (Zea mays L.) breeding experiments in current literature. The present study compared different graphical techniques to determine the best parental lines and cross combinations for yield and kernel quality traits in maize breeding experiments. We measured single plant yield, protein content, oil content, carotenoid content, oleic acid, and linoleic acid in a 5 × 2 line × tester design. Genotype + genotype × environment (GE) biplot, principal component analysis (PCA) biplot, and polar plot were used to analyze data and compare them with conventional line × tester analysis. In the conventional analysis, parents with high means and positive general combining ability (GCA) values were A680 and HYA for single plant yield, IHP for protein content, IHO and HYA for oil content, A680 and Q2 for carotenoid content, IHP for oleic acid content, and A680 for linoleic acid content. The B73 tester exhibited positive GCA values for most investigated traits. The HYA × B73 combination was the best cross in terms of single plant yield, protein, and oil contents. Results showed that biplot methods had both advantages and disadvantages. The PCA biplots can be used alone while the GGE biplot and polar plots are both useful for combining ability, heterosis, and gene action analysis in a line × tester design. Overall, graphical analysis results were very similar to conventional analysis. Consequently, it was assumed that the graphical methods used could be useful to analyze/present data from maize breeding experiments carried out with a line × tester design.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparison of graphical analyses for maize genetic experiments: Application of biplots and polar plot to line × tester design

Kahrıman

Egesel

Orhun

et al. 2016

Chilean J. Agric. Res.

View full text Add to dashboard Cite

show abstract

“…Differences in the SCA effects are attributed to the differences in the heterotic potential of different cross combinations and differences in the genetic background of the genotypes. Ruswandi et al (2015) also observed the SCA effects of lines for different agronomic traits of maize using GGE biplot analysis for line × tester data and found that different lines were having different SCA effects for different traits.…”

Section: Discussionmentioning

confidence: 99%

“…It was evident that T5 (14966) was average tester for PVAC and YPH among studied five different testers. Ruswandi et al (2015) also visualized the average testers for different agronomic traits of maize using GGE biplot analysis for line × tester data and found that different testers were average testers for different traits.…”

Section: Discussionmentioning

confidence: 99%

“…For improving the comprehensibility and visualization of the results from line × tester analysis based studies, different alternative methods are being explored. GGE biplot analysis provides best graphical visualization of the results for two way data tables (Badu-Apraku et al, 2013;Ruswandi et al, 2015). Thus, GGE biplot could be used as graphical approach for combining ability estimation of line × tester data and to decide that whether it could be used as alternative to the conventional Kempthorne's numerical approach.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Single Cross Yellow Maize Hybrids for Agronomic and Carotenoid Traits

Maqbool¹

2017

IJAB

View full text Add to dashboard Cite

Provitamin A bioforitification of maize endosperm was found to be most convenient solution to the resolve its deficiency in the masses. Continuous efforts for persistent evaluation of diverse genetic material are prerequisite for genetic improvement of maize endosperm for provitamin A. Distinctively selected inbred lines and testers were evaluated for their yield and provitamin A related performance in single cross F1 hybrid combinations. Total 50 single cross hybrids were evaluated for different agronomic and carotenoid related traits. Significant differences were observed among genotypes, lines, testers and line × tester interaction for studied traits. L5, L6 and T1 had high GCA effects for YPH, RPC and FW whereas, L1, L5 and T4 had high GCA effects for TCC, PVAC and NPVAC. Among studied crosses, L7×T3, L8×T4 and L5×T2 had high SCA effects for PVAC whereas, L2×T5, L3×T3 and L4×T2 had high SCA effects for YPH. L3×T3 had high SCA effects for YPH, TCC, PVAC and NPVAC. L8×T4 had high SCA effects for PVAC, RPC and FW. L2×T5 had high SCA effects for PVAC, YPH, NPVAC and TCC. Most of variability was contributed by L×T interaction which showed that performance of the parents could only be evaluated in specific cross combinations. Phenotypic variances and phenotypic coefficient of variations were higher which showed that performance of the crosses was also dependent on the environmental factors. Gene action showed that all of the traits were under the control of non-additive gene action which strongly directs the manipulation of heterosis breeding for genetic improvement of studied traits. L3×T3, L5×T4, L3×T1, L4×T3, L2×T1, L8×T3 and L5×T2 for RPC and TCC whereas, L1×T1, L3×T5, L7×T1, L10×T5, L7×T2 and L9×T1 for FW, YPH and PVAC had highest better parent heterosis. Results of Kempthorne's analysis and GGE biplot analysis were comparable for estimation of GCA, SCA effects and identification of desired crosses. Therefore, GGE biplot could be preferred for providing visual explanation of the effects and additionally provides information about heterotic grouping of testers, SCA effects of parents, best parent and best crosses. Combining ability, gene action and heterosis studies based on Kempthorne's analysis and GGE biplot analysis revealed that genetic improvement can be made for studied agronomic and carotenoid related traits. Improvement of yield and provitamin A carotenoids may help the peoples of Pakistan to suffice the food security issue and to alleviate the sub-clinical symptoms of vitamin A deficiency.

show abstract

“…The GGE biplot has extensively been used to study the GCA and SCA in a cross and identifying best cross combinations for diallel data (Anido et al 2004;Bertoia et al 2006;Darvishzadeh et al 2009;Vivek et al 2010). But such studies have been less done for line × tester data (Fotokian and Agahi 2014;Kahriman et al 2016;Kannababu et al 2017;Ruswandi et al 2015).…”

Section: Introductionmentioning

confidence: 99%

The usefulness of GGE biplot methodology for line × tester data of maize inbred lines

Momeni

Shiri²,

Hervan

et al. 2020

Bragantia

View full text Add to dashboard Cite

The genotype + genotype × environment (GGE) biplot methodology has the potential to determine combining ability effects, identify efficient testers, and distinct heterotic groups in a line × tester study. However, it has not been adequately applied for such analysis. Therefore, this study was done to assess the combining ability of some maize inbred lines and testers for grain yield, identify most efficient testers and classify inbred lines into heterotic groups using GGE biplot. Fifteen experimental single cross hybrids, generated from a 5 × 3 line by line × tester crosses procedure, were evaluated across seven sites in Iran in 2018 using a randomized complete block design with three replicates per entry at each site. According to the pooled analysis of variance, crosses showed significant differences for grain yield. Also, the differences observed among the testers, inbred lines, and interactions for the line × tester, crosses × environments, line × tester × environment was significant. The inbred line L4 was recognized as outstanding for its general combining ability (GCA) effect and the tester K18 was highly efficient based on its discriminating power. It can be concluded that the crosses of L4 × K47/3 and L4 × B73 are suggested to release high grain yield hybrids. Results of the GGE biplot analyses were close to the conventional line × tester method in combining ability and heterotic patterns of the yield of lines, grouping, and identification of testers.

show abstract

GGE Biplot Analysis for Combining Ability of Grain Yield and Early Maturity in Maize Mutant in Indonesia

Cited by 15 publications

References 16 publications

Comparison of graphical analyses for maize genetic experiments: Application of biplots and polar plot to line × tester design

Comparison of graphical analyses for maize genetic experiments: Application of biplots and polar plot to line × tester design

Evaluation of Single Cross Yellow Maize Hybrids for Agronomic and Carotenoid Traits

The usefulness of GGE biplot methodology for line × tester data of maize inbred lines

Contact Info

Product

Resources

About