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Genotype-by-environment interaction and stability of sweetpotato genotypes for root dry matter, β-carotene and fresh root yield

Fekadu Gurmu / Shimelis Hussein
  • University of KwaZulu-Natal, African Centre for Crop Improvement, Private Bag X01Scottsville 3209, Pietermaritzburg, South Africa
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Mark Laing
  • University of KwaZulu-Natal, African Centre for Crop Improvement, Private Bag X01Scottsville 3209, Pietermaritzburg, South Africa
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-09-13 | DOI: https://doi.org/10.1515/opag-2017-0052

Abstract

The study was conducted to estimate the magnitude of genotype x environment interactions (G x E) and to select stable and high yielding sweetpotato genotypes for root dry matter content (RDMC), β-carotene content and fresh root yield, and to identify the most discriminating and representative test environments in Ethiopia. The study was conducted across six environments (Halaba, Kokate, Areka, Arbaminch, Hawassa and Dilla) in southern Ethiopia. Twenty four selected genotypes and one check variety (Tula) were evaluated using a 5 × 5 simple lattice design. Stability analysis was conducted using Genotype plus Genotype by Environment Interaction (GGE bi-plot). Environment, genotype and G × E interaction variances were significant (p < 0.001) for the three traits. The magnitude of environment and G x E interaction was 66.8% for fresh root yield, 44.0% for RDMC and 7.6% for β-carotene content. Three genotypes designated as G1, G6 and G20 were identified as having above average RDMC of 31.82, 32.60 and 30.06%, high β-carotene content of 12.48, 14.27 and 13.99 mg 100 g-1 and, stable and high fresh root yields of 25.09, 26.92 and 25.46 t ha-1, respectively. These genotypes were selected for final evaluation and recommendations. Among the test environments, Arbaminch, Halaba and Areka better discriminated among genotypes for RDMC and fresh root yield while Areka, Dilla and Halaba were the environments better discriminated among genotypes for β-carotene content. Four environments, Arbaminch, Halaba, Areka and Dilla can be considered good environments for sweetpotato screening in southern Ethiopia. Kokate is not a good environment for sweetpotato testing in Southern Nation, Nationalities and People’s Regional State (SNNPRS). Generally, the current study demonstrated the possibility of breeding sweetpotato varieties with combined high RDMC, β-carotene content and a high fresh root yield, with wide adaptation for large scale production.

Keywords: Genotypes; GGE; multi-environment; stability analysis

References

  • Annicchiarico P., Genotype x Environment Interactions. Challenges and Opportunities for Plant Breeding and Cultivar Recommendations, Food and Agriculture Organization, Rome, Italy, 2002Google Scholar

  • ARC, Sweetpotato production and field management in Ethiopia, Production Manual. Awassa Agricultural Research Center, Hawassa, Ethiopia, 2015Google Scholar

  • Belehu T., Agronomical and Physiological Factors Affecting Growth, Development and Yield of Sweetpotato in Ethiopia, PhD Thesis, University of Pretoria, Pretoria, 2003Google Scholar

  • Cervantes-Flores J.C., Sosinski B., Pecota K.V., Mwanga R.O.M., Catignani G.L., Truong V.D.,. Watkins R.H, Ulmer M.R., Yencho G.C., Identification of quantitative trait loci for dry-matter, starch, and β-carotene content in sweetpotato, Molecular Breeding, 2010, 28, 201-216Web of ScienceCrossrefGoogle Scholar

  • Chiona M, Towards Enhancement of β-carotene Content of High Dry Mass Sweetpotato Genotypes in Zambia, PhD Thesis, University of KwaZulu-Natal, Pietermaritzburg, South Africa, 2009Google Scholar

  • CSA, Ethiopia Agricultural Sample Survey 2014/2015, Report on Land Utilization (Private Peasant Holdings, Meher Season), Central Statistical Agency (CSA), Federal Democratic Republic of Ethiopia, Addis Ababa, Ethiopia, 2015Google Scholar

  • Gauch H.G., Model selection and validation for yield trials with interaction. Biometrics, 1988, 44, 705-715 CrossrefGoogle Scholar

  • Gauch H.G., Zobel R.W., Predictive and postdictive success of statistical analysis of yield trials. Theoretical and Applied Genetics, 1988, 76, 1-10CrossrefGoogle Scholar

  • Gonzales I.C, Yield performance of newly bred sweetpotato entries under cold weather cnditions of La Trinidad, Benguet, Philippines, International Journal of Agriculture Innovations and Research, 2015, 4(3), 496-501Google Scholar

  • Grüneberg W.J., Manrique K., Zhang D., Hermann M., G x E interaction for a diverse set of sweetpotato genotypes evaluated across varying ecogeographic conditions in Peru, Crop Science, 2005, 45, 2160-2171Google Scholar

  • Gurmu F, Breeding of Sweetpotato for Improvement of Root Dry Matter and β-carotene Contents in Ethiopia, PhD Thesis, Univeristy of KwaZulu-Natal, Pietermaritzburg, South Africa, 2015Google Scholar

  • Gurmu F., Hussein S., Laing M., The potential of orange-fleshed sweetpotato to prevent vitamin A deficiency in Africa, International Journal for Vitamin and Nutrition Research, 2015, 84(1-2), 65-78Google Scholar

  • Huaman Z., Descriptors for Sweetpotato, International Board for Plant Genetic Resources, Rome, Italy, 1991Google Scholar

  • Huaman Z., Sweetpotato (Ipomoea batatas) Germplasm Management, International Potato Center (CIP), Lima, Peru, 1999Google Scholar

  • Janssens M.J.J, Genotype by environment interactions of the yield components in sweetpotato, In: Shideler, S.F. and H. Rincon, editors. Proceedings of the 6th Symposium of the International Society of Tropical Root Crops (ISTRC), Lima, Peru. 21-26 February, CIP, 1983, pp. 543-551Google Scholar

  • Kathabwalika D.M., Chilembwe E.H.C., Mwale V.M., Evaluation of dry matter, starch and β-carotene content in orange-fleshed sweet potato (Ipomoea batatas L.) genotypes tested in three agroecological zones of Malawi, African Journal of Food Science, 2016, 10(11), 320-326Google Scholar

  • Manrique K., Hermann M., Effect of G x E Interaction on Root Yield and β-carotene Content of Selected Sweetpotato [Ipomoea batatas (L) Lam.] Varieties and Breeding Genotypes, International Potato Center (CIP), Lima, Peru, 2001Google Scholar

  • Mbwaga Z., Mataa M., Msabaha M., Quality and yield of orange fleshed sweetpotato (Ipomoea batatas) varieties grown in different agro-ecologies, In: Kasem, Z.A., editors, The 8th African Crop Science Society (ACSS) Conference Proceeding, El-Minia, Egypt. 27-31 October, 2007, African Crop Science Society, 2008, pp. 339-345Google Scholar

  • Moussa S.A.M., Hala A.A.E, Nashwa I.A.E., Stability study of sweetpotato yield and its component characters under different environments by joint regression analysis, Journal of Horticultural Science and Ornamental Plants, 2011, 3, 43-54Google Scholar

  • Nasayao L.Z., Saladaga F.A., G x E interaction for yield in sweetpotato [Ipomoea batatas (L.) Lam.], Philippine Journal of Crop Science, 1988, 13, 99-104Google Scholar

  • Osiru M.O., Olanya O.M., Adipala E., Kapinga R., Lemaga B., Yield stability analysis of Ipomoea batatas L. cultivars in diverse environments, Australian Journal of Crop Science, 2009, 3, 213-220Google Scholar

  • Payne R.W., Murray D.A., Harding S.A., Baird D.B., Soutar D.M., GenStat for Windows (14th Edition) Introduction, VSN International, Hemel Hempstead, UK, 2011 Google Scholar

  • SAS Institute Inc, Version 9.1, SAS Institute Inc., Cary, NC, 2003Google Scholar

  • Simonne A.H., Kays S.J., Koehler P.E., Eilenmiller R.R., Assessment of β-carotene in sweetpotato breeding lines in relation to dietary requirements. Journal of Food Composition and Analysis, 1993, 6, 336-345Google Scholar

  • Tofu A., Anshebo T., Tsegaye E., Tadesse T., Summary of progress on orange-fleshed sweetpotato research and development in Ethiopia, In: Proceedings of the 13th International Society for Tropical Root Crops (ISTRC) Symposium, Arusha, Tanzania, 9-15 November, 2003. ISTRC, Arusha, 2007, pp. 728 - 731Google Scholar

  • Tsegaye E., Cherinet M., Kifle A., Mekonen D., Tadesse T., Genotype x environment interactions and yield stability of orange fleshed sweetpotato varieties grown in Ethiopia, In: Tropical Roots and Tubers in a Changing Climate: A Critical Opportunity for the World, 2-6 November, 2009, Lima. International Society for Tropical Root Crops (ISTRC), Lima, Peru, 2011Google Scholar

  • Tsegaye E., Dechassa N., Sastry E.V.D., Genetic variability for yield and other agronomic traits in sweet potato genotypes. Journal of Agronomy, 2007, 6, 94-99Google Scholar

  • Tumwegamire S., Rubaihayo P.R., Gruneberg W.J., LaBonte D.R., Mwanga R.O.M., Kapinga R., Genotype x Environment Interactions for East African Orange-Fleshed Sweetpotato Clones Evaluated across Varying Ecogeographic Conditions in Uganda. Crop Sci., 2016, 56, 1-17Web of ScienceGoogle Scholar

  • Yan W., GGE Biplot: A Windows application for graphical analysis of multi-environment trial data and other types of two-way data, Agronomy Journal, 2001, 93, 1111-1118CrossrefGoogle Scholar

  • Yan W., Singular-value partitioning in biplot analysis of multienvironment trial data, Agronomy Journal, 2002, 94, 990-996CrossrefGoogle Scholar

  • Yan W., Cornelius P.L., Crossa J., Huntt L.A., Two types of GGE biplots for analyzing multi-environment trial data, Crop Science, 2001, 41, 656-663CrossrefGoogle Scholar

  • Yan W., Kang M.S., GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists, CRC Press, Boca Raton, Florida, 2003Google Scholar

  • Yan W., Hunt L.A., Sheng Q., Szlavnics Z., Cultivar evaluation and mega-environment investigation based on the GGE biplot, Crop Science, 2000, 40, 597-605CrossrefGoogle Scholar

  • Yan W., Kang M.S., Ma B., Woods S., Cornelius P.L., GGE Biplot vs. AMMI analysis of genotype-by-environment data, Crop Science, 2007, 47, 643-655Web of ScienceGoogle Scholar

About the article

Received: 2017-02-23

Accepted: 2017-08-15

Published Online: 2017-09-13

Published in Print: 2017-09-26


Citation Information: Open Agriculture, Volume 2, Issue 1, Pages 473–485, ISSN (Online) 2391-9531, DOI: https://doi.org/10.1515/opag-2017-0052.

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© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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