GGE bi-plot Analysis of Genotype by Environment Interaction in Finger millet (Eleusine coracana (L.) Gaertn.) Varieties in Different Locations of Southwestern Ethiopia

Tegegn Belete

Authors

Tegegn Belete EIAR, Jimma Research Center, P.O.Box 192, Jimma, Ethiopia

Keywords:

GGE, genotype by environment interaction, finger millet varieties

Abstract

Objective: To evaluate the yield performance of each genotype in relation to each environment, to examine the possible existence of different mega environments and to identify the winning genotype for each mega environment using GGE bi-plot method.

Methodology: Ten finger millet varieties which were obtained from Melkassa and Bako (regional) used for the experiment. The trial was conducted at Limu seka,Omonada,Buno bedele and Gooma sites. The experiment was laid out using randomized complete block design with four replications in all testing sites. The plot size was four harvestable rows and spacing between rows was 40cm with the length of 5m long. All management practices such as cultivation, fertilization and weeding were done based on the recommendations for each test sites. Data for all relevant agronomic traits were collected, but only plot yield data converted to qt/ha was subjected to statistical analysis.

Result and Discussion: The mean grain yield of the varieties was ranged from 18.9qt/ha to 15.3qt/ha.The highest mean was harvested from the variety Gudetu (18.9qt/ha) and the lowest from variety Meba (15.3qt/ha).Out of ten varieties, six varieties had grain yield below the average. Among the environments, the LM2017 and GM2019 had grain yield below the mean yields. The highest yield were recorded in the environment BD2018 and BD2017 with mean yields of 25.6 and 24.5qt/ha respectively. A combined analysis of variance indicated that genotype, environment and GEI showed significant (P<0.001) differences among finger millet varieities.This result showed that finger millet yields were significantly influenced by environment, which accounted 78.7% of the total yield variation, while genotype and GEI explained 1.55 and 9.86% of the variation respectively. The partitioning of GGE through GGE biplot analysis showed that PC1 and PC2 accounted 46.3 and 27.2% of GGE sum of squares, respectively, explaining a total of 73.5% variation.

Conclusion :GGE biplot identified G7 and BD19 as ideal genotype and enviornment respectively.

References

Adugna, A., Tesso, T., Degu, E., Tadesse, T., Merga, F., Legesse, W., Tirfessa, A., Kidane, H., Wole, A. and Daba, C. 2011. Genotype-by-environment interaction and yield stability analysis in finger millet (Elucine coracana L. Gaertn) in Ethiopia. American Journal of Plant Sciences, 2(03): 408-415
Ayalew, B. 2015. Trends, growth and instability of finger millet production in Ethiopia. Research Journal of Agriculture and Environmental Management, 4(2): 078-081.
Bezaweletaw, K., Sripichit, P., Wongyai, W., Hongtrakul, V. 2006. Genetic variation, heritability and path-analysis in Ethiopian finger millet (Eleusine coracana (L.) Gaertn) landraces. Kasetsart Journal of Natural Science 40: 322-334.
Central Statistical Authority (CSA) (2017), The Federal Democratic Republic of Ethiopia, Central Statistical Agency agricultural sample survey 2016/2017 (2009 E.C) volume I report on area and production of major crops (private peasant holdings, Meher season). Statistical Bulletin no.584, Addis Ababa, Ethiopia, pp. 118
Comstock, R.E. and Moll, R.H., 1963. Genotype x environment interactions. Statistical genetics and plant breeding (No. REP-1173. CIMMYT.).
Dagnachew, L., Kassahun, T., Awol, A., Masresha, F., Kebede, D., Girma, M., Geleta, G., Hailu, F., Kassa, M., Chemeda,B., Girma, C. and Gudeta, B. 2015. Registration of “Addis-01” Finger Millet Variety. East African Journal of Science, 9 (2): 141- 142.
Degu, E., Adugna, A., Tadesse, T. and Tesso, T. 2009. Genetic resources, breeding and production of millets in Ethiopia, in new approaches to plant breeding of orphan crops in Africa. Proceedings of an International Conference, Bern Switzerland, 19- 21 September, 2007
Dida, M., Srinivasachary, M., Ramakrishnan, S., Bennetzen, J. L., Gale, M. D. and Devos, K. M. 2007. The genetic map of finger millet, Eleusine coracana. Theoretical and Applied Genetics 114:321–332.
Fox, P.N., B.Skovmand, B.K.Thomson, H.J.Braun and R.Comier, 1996. Yield and adaptation of hexaploid spring triticale. Euphytica 47:57-64
Flores, F., Moreno, M.T., Cubero, J.I. .1998. A comparison of univariate and multivariate methods to analyze GE interaction. Field Crops Research 56: 271–286.
Gabriel, K R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrica, 58: 453-467
Gauch, H G and R W Zobel. 1997. Identifying mega-environments and targeting genotypes. Crop Sci. 37: 311-326.
Goron, T. L., and Raizada, M. N. 2015. Genetic diversity and genomic resources available for the small millet crops to accelerate a new green revolution. Front.Plant Sci. 6:157.
Gupta, S.M., Arora, S., Mirza, N., Pande, A., Lata, C., Puranik, S., Kumar, J. and Kumar, A. 2017. Finger millet: a “certain” crop for an “uncertain” future and a solution to food insecurity and hidden hunger under stressful environments. Frontiers in Plant Science, 8 (643): 1-11
Kang, M.S., and D.P.Gorman, 1989. Genotype x environment interaction in maize. Agron.J.81: 662-664.
Kaya, Y, M Akcura and S Taner. 2006. GGE-biplot analysis of multi-environment yield trials in bread wheat. Turk. J. Agric. 30: 325-337.
Kebede, Y. and Menkir A. 1986. Improvement of finger millet in Ethiopia, pp. 173-176. In: Seetheram, A., Rilley, K.W. and Upadhyaya, G. (eds.). Small Millet in Global Agriculture: Proceeding of the First International Small Millet Workshop. October 29-November 2, 1986. Bangalore, India.
Mitrovic, B, D Stanisavljevi, S Treski, M Stojakovic, M Ivanovic, G Bekabac and M Rajkovic. 2012. Evaluation of experimental maize hybrids tested in multi-location trials using AMMI and GGE biplot analysis. Turkish J. Field Crops. 17(1): 35-40
Mulatu, T. and Kebede, Y. 1993. Finger millet importance and improvement in Ethiopia. In: Riley K.W., Gupta S.C., Seetharam A. and Mushonga J.N. (eds), Advances in Small Millets. Oxford & IBH Publishing Co. Pvt. Ltd., New Delhi pp. 51–59.
Pham, H.N. and M.S. Kang, 1988. Interrelationships among respectability of several stability statistics estimated from international maize trials. Crop Sci., 28: 925-928.
Upadhyaya, H., Gowda, C., and Reddy, V. G. 2007. Morphological diversity in ?nger millet germplasm introduced from Southern and Eastern Africa. J. SATAgric. Res. 3, 1–3.Visioni, A., Tondelli
Solomon A. and Tegegn B. 2020. Finger millet (Eleusine coracana (L.) Gaertn) breeding, major production challenges and future prospects. J. Agri. Res. Adv. 02(02): 33-39.
Yan, W, L A Hunt, Q Sheng and Z Szlavnics. 2000. Cultivar evaluation and mega environment investigation based on the GGE biplot. Crop Sci. 40: 597-605
Yan, W. 2001. GGE biplot a windows application for graphical analysis of multi-environment trial data and other types of two way data. Agron. J. 93: 1111-1118.
Yan, W., Kang, M.S., Ma, B., Woods, S., Cornelius, P.L., 2007. GGE Biplot vs. AMMI Analysis of Genotype-by-Environment Data. Crop Science 47:643.
Yan, W. and Rajcan, I. 2002. Biplots analysis of the test sites and trait relations of soybean in Ontario. Crop Science 42:11-20.
Yan W., Cornelius P.L., Crossa J., Hunt L.A. 2001. Two types of GGE biplots for analyzing multi-environment trial data. Crop Science 41:656-663.
Yan W., Kang M.S. .2003. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. CRC Press, Boca Raton, FL.
Yan W., Hunt L.A. 2002. Biplot analysis of diallel data. Crop Science 42:21-30

GGE bi-plot Analysis of Genotype by Environment Interaction in Finger millet (Eleusine coracana (L.) Gaertn.) Varieties in Different Locations of Southwestern Ethiopia

Authors

Keywords:

Abstract

References

Published

How to Cite

Issue

Section