Biplot Analysis of Genotype by Environment for Cooking Quality in Hybrid Rice: A Tool for Line × Tester Data

Fotokian, Mohammad Hossein; Agahi, Kayvan

doi:10.1016/s1672-6308(13)60193-6

Cited by 13 publications

(15 citation statements)

References 8 publications

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“…For example the GCA values and the best hybrids for grain yield and maturity from biplot analysis and Kempthorne's method are similar (Ruswandi et al, 2015;Supriatna and Ruswandi, 2014). Fotokian and Agahi (2014) reported similar result, when he compared his biplot analysis of line×tester data and Kempthorne's analysis of line×tester data from Maleki et al (2014). Furthermore, Yan and Hunt (2002) explained that the advantage of the GGE biplot is its graphical presentation of the data, which improve the ability to understand patterns of the data.…”

Section: Best Crosses Between the Lines And The Testersmentioning

confidence: 64%

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

Ruswandi¹,

Supriatna²,

Waluyo³

et al. 2015

Asian J. of Crop Science

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Determination of combining abilities and heterotic groupings of parental lines is very important in selecting the mutant lines and to decide breeding strategies for maize hybrid production. Fourty six new mutant lines used in maize breeding programs in Indonesia, were crossed to three tester lines in a lines×testers mating design. The 138 F1 hybrids, the 46 parental lines and 3 tester lines were evaluated at Arjasari, West Java, Indonesia for the following objectives: (i) to analyze line×tester data for maturity and grain yield using GGE for identifying genetic inter-relationships among parents and (ii) to identify the best combinations for maturity and grain yield in maize hybrids. The GGE biplot graphic allowed a rapid and effective overview of General Combining Ability (GCA) and Specific Combining Ability (SCA) effects of the inbred lines, best lines and tester, as well as their performance in crosses. High GCA effect for maturity and grain yield was determined based on Average Tester Coordination function of GGE Biplot. Thus, it was revealed that DR 4 is the best tester for early maturity and DR 6 for grain yield. The maximum best-parent heterosis values and the highest SCA effects resulted from mutants (10, 31, 32, 34, 36, 48) and mutants (5, 7, 10, 32, 34, 36, 37 and 48) crosses to testers (4, 6 and 8) for early maturity and grain yield, respectively. This is potentially useful in maize breeding programs to obtain high-yielding hybrids in areas with the same climate of Indonesia.

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Section: Best Crosses Between the Lines And The Testersmentioning

confidence: 64%

“…This method is rarely reported for line×tester data analysis. Fotokian and Agahi (2014) reported that identification of suitable parents, heterotic crosses and the best hybrids in line×tester data can be analyzed using GGE biplot.…”

Section: Asian J Cropmentioning

confidence: 99%

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

Ruswandi¹,

Supriatna²,

Waluyo³

et al. 2015

Asian J. of Crop Science

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“…Previous research has shown that the polygon view of GGE biplots enabled classifying genotypes according to their heterotic group (Fotokian and Agahi, 2014). We did not take this view because our study aimed to show the potential for presenting results from conventional analysis by graphical analysis.…”

Section: Resultsmentioning

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.

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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.

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“…The GGE biplot analysis of plant traits focused on identifying a stable genotype for deployment as well as suitable areas for subsequent commercial grain production (Lakew, Tariku, Alem, & Bitew, 2014), stability of disease resistance (Idowu, Salami, Ajayi, Akinwale, & Sere, 2013;Tabien, Samonte, Abalos, & San Gabriel, 2008;Yan & Falk, 2002), stability of F1 hybrid (Akter et al, 2015), cooking quality (Fotokian & Agahi, 2014), and anthocyanin content (Somsana, Wattana, Suriharn, & Sanitchon, 2013). Therefore, the analysis of disease reaction also aims to determine suitable donor parents for the trait and to identify BLB isolates that will be useful in further screening for resistance breeding program.…”

Section: Introductionmentioning

confidence: 99%

Stability of Four New Sources of Bacterial Leaf Blight Resistance in Thailand Obtained from Indigenous Rice Varieties

et al. 2017

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Bacterial leaf blight (BLB) disease caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious diseases in rice production. Breeding varieties specifically for their resistance to BLB disease is therefore an efficient and cost-effective strategy. However, the resistance gene for BLB can be race and non-race specific, meaning it is often overcome by the pathogen. The identification of new sources of resistance genes for Xoo is crucial in rice breeding programmes. In this study, six rice varieties were assessed using six Xoo isolates in multiple screening conditions. The GGE biplot analysis considers both genotype (G) and genotype environment (GE) interaction effects and demonstrates GE interaction. The first two principal components (PCs) accounted for 95.46% of the total GE variation in the data. Based on lesion length and stability performance, Phaladum was the most ideal genotype against all Xoo isolates in the four screening conditions. The results relayed that Phaladum indigenous rice varieties could be considered as new sources of bacterial leaf blight resistance in Thailand. In the future, the BLB resistance gene in this variety will be identified in regard to mode of inheritance and used as parental line in rice breeding programmes for resistance to BLB.

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Biplot Analysis of Genotype by Environment for Cooking Quality in Hybrid Rice: A Tool for Line × Tester Data

Cited by 13 publications

References 8 publications

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

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

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

Stability of Four New Sources of Bacterial Leaf Blight Resistance in Thailand Obtained from Indigenous Rice Varieties

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