7
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A study on genotype–environment interaction based on GGE biplot graphical method in sunflower genotypes ( Helianthus annuus L.)

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          GGE biplot technique is one of the appropriate methods for investigating the genotype–environment interaction. An experiment was conducted to examine and evaluate the stability and adaptability of grain yield of 12 sunflower genotypes using the randomized complete block design (RCBD) with three replications in five regions including Karaj, Birjand, Firooz‐Abad, Kashmar, and Arak within two agricultural years. Analysis of variance indicated that the effect of location, year, location × year, genotype, and genotype × location was significant at 1% probability level. Results of biplot analysis showed that the first and second principle components accounted 50.6% and 22.8%, respectively, and in total 73.4% of grain yield variance. In this study, genotype, location, year, year × location, genotype × location, genotype × year, and genotype × year × location explained 2.75%, 17.36%, 5.47%, 17%, 10.8%, 1.04%, and 7.48% of total variance, respectively. Investigating the polygon view led to the identification of three top genotypes and also three mega‐environment. The first mega‐environment included Karaj, Birjand, and Kashmar. The second was Arak, and the third was Firooz‐Abad. To study the kernel yield and stability of genotypes simultaneously, average coordinate view of environments was used and it was determined that genotype Zaria with the highest grain yield has high yield stability also. Ranking the cultivars based on the ideal genotype introduced the genotype Zaria as the best genotype. The highest grain yield belonged to Zaria cultivar at 3.34 t/ha followed by Favorite with 3.23 t/ha. Results obtained from ranking the environments based on the ideal environment introduced Kashmar and Birjand regions as the best environments. Examining the biplot figure for testing environments correlation confirms the positive correlation among Karaj, Birjand, and Kashmar. Correlation between Karaj with Arak, Karaj with Firooz‐Abad, and Arak with Firooz‐Abad was negative. Arak and Firooz‐Abad were highly discriminating and representative and would be used to identification of superior genotypes.

          Abstract

          Polygon view of GGE biplot method for determining the appropriate cultivars in every environment. (G1: Progress, G2: Gabur, G3: Zargol, G4: Armaverski, G5: Azargol, G6: Master, G7: SHF81‐90, G8: Zaria, G9: Favorite, G10: Record, G11: Lakumka, G12: Bulg3).

          Related collections

          Most cited references21

          • Record: found
          • Abstract: not found
          • Article: not found

          Cultivar Evaluation and Mega-Environment Investigation Based on the GGE Biplot

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Breeding and Cereal Yield Progress

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Biplot Analysis of Test Sites and Trait Relations of Soybean in Ontario.

              Superior crop cultivars must be identified through multi-environment trials (MET) and on the basis of multiple traits. The objectives of this paper were to describe two types of biplots, the GGE biplot and the GT biplot, which graphically display genotype by environment data and genotype by trait data, respectively, and hence facilitate cultivar evaluation on the basis of MET data and multiple traits. Genotype main effect plus genotype by environment interaction effect (GGE) biplot analysis of the soybean [Glycine max (L.) Merr.] yield data for the 2800 crop heat unit area of Ontario for MET in the period 1994-1999 revealed yearly crossover genotype by site interactions. The eastern Ontario site Winchester showed a different genotype response pattern from the three southwestern Ontario sites in four of the six years. The interactions were not large enough to divide the area into different mega-environments as when analyzed over years, a single cultivar yielded the best in all four sites. The southwestern site, St. Pauls, was found to always group together with at least one of the other three sites; it did not provide unique information on genotype performance. Therefore, in future cultivar evaluations, Winchester should always be used but St. Pauls can be dismissed. Applying GT biplot to the 1994-1999 multiple trait data illustrated that GT biplots graphically displayed the interrelationships among seed yield, oil content, protein content, plant height, and days to maturity, among other traits, and facilitated visual cultivar comparisons and selection. It was found that selection for seed yield alone was not only the simplest, but also the most effective strategy in the early stages of soybean breeding.
                Bookmark

                Author and article information

                Contributors
                mostafavi@kiau.ac.ir
                Journal
                Food Sci Nutr
                Food Sci Nutr
                10.1002/(ISSN)2048-7177
                FSN3
                Food Science & Nutrition
                John Wiley and Sons Inc. (Hoboken )
                2048-7177
                06 May 2020
                July 2020
                : 8
                : 7 ( doiID: 10.1002/fsn3.v8.7 )
                : 3327-3334
                Affiliations
                [ 1 ] Department of Agronomy and Plant Breeding Science and Research Branch Islamic Azad University Tehran Iran
                [ 2 ] Department of Agronomy and Plant Breeding, Karaj Branch Islamic Azad University Karaj Iran
                [ 3 ] College of Agriculture & Natural Resources (UCAN) University of Tehran Karaj Iran
                [ 4 ] College of Agriculture & Natural Resources University of Tehran Pakdasht Iran
                Author notes
                [*] [* ] Correspondence

                Khodadad Mostafavi, Department of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj, Iran.

                Email: mostafavi@ 123456kiau.ac.ir

                Author information
                https://orcid.org/0000-0001-8093-8717
                Article
                FSN31610
                10.1002/fsn3.1610
                7382153
                32724597
                9288cf00-1ee6-499d-97b1-724de4484557
                © 2020 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 March 2020
                : 06 April 2020
                : 07 April 2020
                Page count
                Figures: 5, Tables: 3, Pages: 8, Words: 4725
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                July 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.8.5 mode:remove_FC converted:25.07.2020

                combined analysis of variance,main components,mega‐environment,sunflower

                Comments

                Comment on this article