Comprehensive Stability Analysis of Wheat Genotypes through Multi-Environmental Trials

Abstract

In rainfed areas, due to variable environmental factors, improving the yield stability of the introduced cultivars along with increasing yield should be considered. The main aim of this study is to obtain high-yield wheat genotypes that are stable and adaptable to cold climatic conditions in Iran. For this purpose, 25 wheat genotypes were evaluated in a randomized complete blocks design with three replications during three cropping seasons (2013-2016) under supplementary irrigation and rainfed conditions. PBSTAT-GE software was used for genotype × environment interaction (GEI) analysis and comprehensive sustainability analysis. The results showed that G5, G14, G16 and G18 genotypes had good stability and general adaptation based on parametric and non-parametric stability statistics. Combined analysis of variance based on the Additive Main Effect and Multiplicative Interaction (AMMI) model showed that GEI is significant in the term of grain yield. Also, the ratios between the sum of squares G, GE and IPC1 showed that the AMMI is suitable for data analysis. GGE biplot analysis identified five mega-environments (MEs), in which ME I including E1, E2, E3, E4, E5, E6, and G7, G5, G14, G13, G16, G18, G20 being the superior ME I genotypes. According to AMMI and GGE biplote stability methods, lines G20, G18, G13, G16, G14 and Saein cultivar (G5) can be considered as desirable genetic resources in wheat production programs under variable environments in Iran, due to having the appropriate combination of yield and stability.

Keywords

• Adaptability and stability
• AMMI
• ANOVA
• GE interaction
• GGE biplot
• wheat

References

1. Ahmadi J, Vaezi B, Shaabani A, Khademi K, Fabriki-Ourang S & Pour-Aboughadareh A (2015). Non-parametric measures for yield stability in grass pea (Lathyrus sativus L.) advanced lines in semi warm regions. Journal of Agricultural Science and Technology 17: 1825–1838
2. Ajay B, Bera S, Singh A, Kumar N, Gangadhar K & Kona P (2020). Evaluation of genotype×environment interaction and yield stability analysis in peanut under phosphorus stress condition using stability parameters of AMMI Model. Agricultural Research 9: 477–486
3. Aktas H (2016). Tracing highly adapted stable yielding bread wheat (Triticum aestivum L.) genotypes for greatly variable south-eastern Turkey. Applied Ecology and Environmental Research 14: 159-176
4. Altay F (2012). Yield stability of some turkish winter wheat (Triticum aestivum L.) genotypes in the western transitional zone of Turkey. Turkish Journal of Field Crops 17(2): 129-134
5. Ashraful M, Farhad M, Abdul M, Barma N, Kumar P, Mostofa M, Amir M & Li M (2017). AMMI and GGE biplot analysis for yield stability of promising bread wheat genotypes in Bangladesh. Pakistan Journal of Botany 49(3): 1049-1056
6. Ayed S, Othmani A, Chaieb N, Bechrif S, Rezgui M & Younes M (2016). Assessment of adaptability and stability of six Tunisian cereal genotypes under rainfed conditions and at two semi-arid environments. European Scientific Journal 12(6): 1857–7881
7. Bavandpori F, Ahmadi J & Hossaini M (2018). Stability analysis of bread wheat landraces and lines using biometrical genetic models. Genetika 50(2): 449-464
8. Bayuardi-Suwarno W, Sobir A & Syukur M (2008). PBSTAT: a web-based statistical analysis software for participatory plant breeding. The 3rd International Conference on Mathematics and Statistics, Bogor, Indonesia

9. Bornhofen E, Benin G, Storck L, Woyann L, Duarte T, Stoco M & Marchioro S (2017). Statistical methods to study adaptability and stability of wheat genotypes. Bragantia, Campinas 76(1): 1-10
10. Dia M, Wehner T & Arellano C (2016). Analysis of genotype×environment interaction (G×E) using SAS programming. Agronomy Journal 108: 1838-1852
11. Eberhart S & Russell W (1966). Stability parameters for comparing varieties 1. Crop Science 6(1): 36-40
12. Elakhdar A, Kumamaru T, Smith K, Brueggeman R, Capo-chichi L & Solanki S (2017). Genotype by environment interactions (GEIs) for barley grain yield under salt stress condition. Journal of Crop Science and Biotechnology 20: 193-204
13. Elias A, Robbins K, Doerge R & Tuinstra M (2016). Half a century of studying genotype×environment interactions in plant breeding experiments. Crop Science 56: 2090–2105
14. Farshadfar E, Sabaghpor H & Zali H (2012). Comparison of parametric and non-parametric stability statistics for selecting stable chickpea (Cicer arietinum L.) genotypes under diverse environments. Australian Journal of Crop Science 6(3): 514-524
15. Finlay K & Wilkinson G (1963). The analysis of adaptation in a plant-breeding programme. Australian Journal of Agricultural Research 14(6): 742-754
16. Fox P, Skovmand B, Thompson B, Braun H & Cormier R (1990). Yield and adaptation of hexaploid spring triticale Euphytica 47: 57-64
17. Francis T & Kannenberg L (1978). Yield stability studies in short-season maize. I. A descriptive method for grouping genotypes. Canadian Journal of Plant Science 58: 1029-1034
18. Gauch H (2013). A simple protocol for AMMI analysis of yield trials. Crop Science 53(5): 1860–1869
19. Hagos H & Abay F (2013). AMMI and GGE biplot analysis of bread wheat genotypes in the Northern part of Ethiopia. Journal of Plant Breeding and Genetics 1: 12-18
20. Hanson W D (1970). Genotypic stability. Theoretical and Applied Genetics 40: 226–231
21. Heidari S, Azizinezhad R & Haghparast R (2017). Determination of yield stability in durum wheat genotypes under rainfed and supplementary irrigation conditions. Journal of Agricultural Sciences and Technology 19: 1355-1368
22. Huehn M (1996). Non-parametric analysis of genotype × environment interactions by ranks. pp. 213-228 in M Kang & H Gauch (Eds.) Genotype by Environment Interaction. CRC Press, Boca Raton, New York
23. Kang M S (1993). Simultaneous selection for yield and stability in crop performance trials: Consequences for growers. Agronomy Journal 85: 754-757
24. Karimizadeh, Mohammadi M, Sabaghnia N & Shefazadeh M (2012). Using different aspects of stability concepts for interpreting genotype by environment interaction of some lentil genotypes Australian Journal of Crop Science 6: 1017–1023
25. Kaya Y & Sahin M (2015). Non-parametric stability analyses of dough properties in wheat. Food Science and Technology 35(3): 509-515
26. Khalili M & Pour-Aboughadareh A (2016). Parametric and non-parametric measures for evaluating yield stability and adaptability in barley doubled haploid lines. Journal of Agricultural Science and Technology 18: 789–803
27. Khan M, Mohammad F, Khan F, Ahmad S & Ullah I (2020). Additive main effect and multiplicative interaction analysis for grain yield in bread wheat. The Journal of Animal & Plant Sciences 30(3): 677-684
28. Kumar V, Kharub A & Singh G (2018). Additive main effects and multiplicative interaction and yield stability index for genotype by environment analysis and wider adaptability in Barley. Cereal Research Communication 46(2): 365–375
29. Lai R (2012). Stability for oil yield and variety recommendations using AMMI (additive main effects and multiplicative interactions) model in Lemongrass (Cymbopogon species). Industrial Crops and Products 40: 296-301
30. Lozada D & Carter A (2020). Insights into the genetic architecture of phenotypic stability traits in winter wheat. Agronomy 10(368): 1-15
31. Malosetti M, Ribaut J & Eeuwijk F (2013). The statistical analysis of multi-environment data: modeling genotype-by-environment interaction and its genetic basis. Frontiers in Physiology 4(44): 1-17
32. Mehari M, Tesfay M, Yirga H, Mesele A, Abebe T, Workineh A & Amare B (2015). GGE biplot analysis of genotype-by-environment interaction and grain yield stability of bread wheat genotypes in south Tigray, Ethiopia. Communications Biology Crop Science 10(1): 17–26
33. Mekonnen M, Sharie G, Bayable M, Teshager A, Abebe E, Ferede M, Fentie D, Wale S, Tay Y, Getaneh D, Ayaleneh Z & Malefia A (2020). Participatory variety selection and stability analysis of Durum wheat varieties (Triticum durum Desf) in northwest Amhara. Cogent Food & Agriculture 6: 1746229
34. Mohammadi M, Sharifi P, Karimizadeh R, Jafarby J, Khanzadeh H, Porsiabidi M, Roostaei M, Hassanpour M & Mohammadi P (2015). Stability of grain yield of durum wheat genotypes by AMMI model. Agricultural and Forest Meteorology 61(3): 181–193
35. Mohammadi M, Karimizadeh R, Sabaghnia N & Shefazadeh M (2012). Genotype × environment interaction and yield stability analysis of new improved bread wheat genotypes. Turkish Journal of Field Crops 17(1): 67-73
36. Mohammadi R, Aghaee M, Haghparast R, Pourdad S, Rostaii M, Ansari Y, Abdolahi A & Amri A (2009). Association among non-parametric measures of phenotypic stability in four annual crops. Middle Eastern and Russian Journal of Plant Science and Biotechnology 1: 20-24
37. Mohammadi R, Sadeghzadeh B, Ahmadi M & Amri A (2020). Biological interpretation of genotype×environment interaction in rainfed durum wheat. Cereal Research Communication 1–8
38. Naroui rad M, Abdul kadir M, Rafii M, Jaafar H, Naghavi M & Ahmadi F (2013). Genotype×environment interaction by AMMI and GGE biplot analysis in three consecutive generations of wheat (Triticum aestivum L.) under normal and drought stress conditions. Australian Journal of Crop Science 7(7): 956-961
39. Nassar R & Huehn M (1987). Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics 43: 45-53
40. Oliveira E, Freitas J & Jesus O (2014). AMMI analysis of the adaptability and yield stability of yellow passion fruit varieties. Scientia Agricola 71(2): 139–145
41. Paderewski J, Gauch H, Mądry W & Gacek E (2016). AMMI analysis of four-way genotype×location×management×year data from a wheat trial in Poland. Crop Science 56(5): 2157–2164
42. Reynolds M, Quilligan E, Aggarwal P, Bansal K, Cavalieri A, Chapman S & Yadav O (2016). An integrated approach to maintaining cereal productivity under climate change. Global Food Security 8: 9-18
43. Rodrigues, P. Monteiro, A & Lourenco V (2016). A robust AMMI model for the analysis of genotype-by-environment data. Bioinformatics 32(1): 58–66
44. Roostaei M, Mohammadi R & Amri A (2014). Rank correlation among different statistical models in ranking of winter wheat genotypes. The Crop Journal 2: 154–163
45. Sadiyah H & Hadi A (2016). AMMI Model for yield estimation in multi-environment trial: A comparison to BLUP. Agriculture and Agricultural Science Procedia 9: 163-169
46. Shahzad K, Qi T, Guo L, Tang H, Zhang X, Wang H, Qiao X, Zhang M, Zhang B, Feng J & Shahid Iqbal M (2019). Adaptability and stability comparisons of inbred and hybrid cotton in yield and fiber quality traits. Agronomy 9(9): 516
47. Shukla S, Mirshra B, Siddiqui A, Pandey R & Rastogi A (2015). Comparative study for stability and adaptability through different models in developed high thebaine lines of opium poppy (Papaver somniferum L.). Industrial Crops and Products 74: 875–886
48. Shukla G (1972). Some statistical aspects of partitioning genotype environmental components of variability. Heredity 29: 237-245
49. Singh C, Gupta A, Gupta V, Kumar P, Sendhil R, Tyagi B, Singh G, Chatrath R & Singh G (2019). Genotype×environment interaction analysis of multi-environment wheat trials in India using AMMI and GGE biplot models. Crop Breeding and Applied Biotechnology 19 (3): 309-318
50. Tekdal S & Kendal E (2018). AMMI model to assess durum wheat genotypes in multi-environment trials. Journal of Agricultural Sciences and Technology 20: 153-166
51. Temesgen T, Keneni G, Sefera T, Jarso M (2015). Yield stability and relationships among stability parameters in faba bean (Vicia faba) genotypes. The crop journal 3: 258–268
52. Thennarasu K (1995). On certain non-parametric procedures for studying genotype environment interactions and yield stability. PhD Thesis, New Delhi University, India
53. Vaezi B, Pour-Aboughadareh A, Mehraban A, Hossein-Pour T, Mohammadi R, Armion M & Dorri M (2018). The use of parametric and non-parametric measures for selecting stable and adapted barley lines. Archives of Agronomy and Soil Science 64: 597-611
54. Verma A & Singh G (2021). Stability, adaptability analysis of wheat genotypes by AMMI with blup for restricted irrigated multi location trials in peninsular zone of India. Agricultural Sciences 12: 198-212
55. Wricke G (1962). About a method for recording the ecological spread in field tests. Magazine f Plantenz 47: 92-96
56. Yan W & Tinker N (2006). An integrated system of biplot analysis for displaying, interpreting, and exploring genotype-by-environment interactions. Crop Science 45: 1004-1016
57. Yan W & Kang M S (2003). GGE biplot analysis: a graphical tool for breeders, geneticists and agronomist. CRC Press, Boca Raton, pp. 271
58. Yan W & Fregeau-Reid J (2018). Genotype by yield×trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Scientific Reports 8(1): 1–10
59. Yan W, Hunt L, Sheng Q & Szlavnics Z (2000). Cultivar evaluation and mega‐environment investigation based on the GGE biplot. Crop Science 40: 597-605
60. Yan W, Kang M, Woods S & Cornelius P (2007). GGE Biplot vs AMMI analysis of genotype-by-environment data. Crop Science 47: 643–53