Acta Scientific Agriculture (ASAG)(ISSN: 2581-365X)

Research Article Volume 4 Issue 10

Stability and Scrutiny Using (Ammi): Model of Bread Wheat Over the Years in Cold Arid Harsh Conditions of Kargil and Zanaskar (Ladakh)- India

Mushtaq Ahmad1*, Faizan Ahmad1, Ejaz Ahmad Dar2, Rizwan Rashid3, Shahnowaz Ahmad4, MH Khan5, Rohie Hassan6 and NR Sofi7

1Mountain Agriculture Research and Extension, India
2Krishi Vigyan Kenner, Kargil, India
3Faculty of Horticulture, Shalimar-SKUAST-Kashmir, India
4Krishi Vigyan Kenner, Znaskar, India
5Saffron Research Station, Pampore-SKUAST-Kashmir, India
6Ph, D Scholar, OPGS University Churu, Rajasthan, India

*Corresponding Author: Mushtaq Ahmad, Mountain Agriculture Research and Extension, India.

Received: August 14, 2020; Published: September 23, 2020



  Field experiments were carried out using 20 genotypes for 3 consecutive years (2017-2019) under two randomly completed conditions (Zanaskar Kargil or irrigation rainfall) to identify high-grain infarct-able wheat genotypes obtained by a single parameter. RBD with three copies in each environment. Combination testing of variation showed significant differences for the GE (genotype-environment) cardinal. The results of AMMI (additive main effect and multiplicative interaction) show that the first two AMMI (AMMI 1 - AMMI 2) are symbolic (P < 0.01). It became clear that the division of whole squares was a major source of environmental impact variability, followed by interplay and genetic type effect. The GE cardinal genotype is three times greater than the effect, indicating the presence of different environmental groups. The AMMI Invisibility Value (ASV) lost the G12, G18, G13, G14 and G11 genotypes, respectively. Differentiation to SE is not a physical selection criterion because most incomplete genotypes do not provide the best yield performance and, therefore, grain yield and ASV can be considered simultaneously in a single parameter-free index. Depending on the rainfall and irrigation conditions, the G1 and G18 genes and the High Grain Genome Type Selection Index (GSI) were matched to the results of the biplot observation.

Keywords: Wheat; AMMI; SAV; Dry Cold Zone; Conflict; Observation; Genetics; Cargill; Reform



  1. Ahmad M., et al. “Variability, Heritability and Genetic Advances in Wheat (Triticum aestivum) under Cold Arid Conditions of Kargil”. International Journal of Current Microbiology and Applied Sciences 7.11 (2018): 1456-1461.
  2. Vergas M., et al. “Interpreting treatment ×environment interaction in agronomy trials”. Agronomy Journals 93 (2001): 949-960.
  3. Thamson WE and SB Philips. “Methods to evaluate wheat cultivar testing environment and improve cultivar selection protocols”. Field Crops Research 99 (2016): 87-95.
  4. Saleem N., et al. “Genotype-environment interaction and stability analysis in Wheat (Triticum aestivum) for protein and gluten contents”. Scientific Research and Essays 10.7 (2015a): 260-265.
  5. Kılıç H. “Additive main effects and multiplicative interactions (AMMI) analysis of grain yield in barley genotypes across environments”. Tarım Bilimleri Dergisi 4 (2014): 337-344.
  6. Gabriel KR. “The biplot graphic display of matrices with application to principal component analysis”. Biometrika 58 (1971): 453-467.
  7. Hossain A., et al. “Biplot yield analysis of heat-tolerant spring wheat genotypes (Triticum aestivum) in multiple growing environments”. Open Agriculture 3.1 (2018): 404-413.
  8. Ezatollah Farshadfar., et al. “AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum)”. Australian Journal of Crop Science 5.13 (2019): 1837-1844.
  9. Farshadfar E. “Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat”. Pakistan Journal of Biological Sciences 14 (2000a): 1791-1796.
  10. Annicchiarico P. “Additive main effects and multiplicative interaction (AMMI) analysis of genotype location interaction in variety trials repeated over years”. Theoretical and Applied Genetics 94 (1997): 1072-1077.
  11. Babarmanzoor A., et al. “Genotype × environment interaction for seed yield in Kabuli Chickpea (Cicer arietinum L.) genotypes developed through mutation breeding”. Pakistan Journal of Botany 4 (2009): 1883-1890.
  12. Bajpai PK and Prabhakaran VT. “A new procedure of simultaneous selection for high yielding and stable crop genotypes”. The Indian Journal of Genetics 60 (2000): 141-146.
  13. Noorul Saleem., et al. “Stability analysis in Wheat: An application of additive main effects and multiplicative interaction”. African Journal of Agriculture Research4 (2015b): 295-300.
  14. Eajaz Ahmad Dar., et al. “Declining Yield of Saffron in Kashmir-Can Environmental Changes Be Held Responsible: An Opinion. 1.2 (2018): 1-2.
  15. Barah BC., et al. “The use of risk aversion in plant breeding; concept and application”. Euphytica 30 (2001): 451-456.
  16. Crossa J. “Statistical analysis of multilocation trials”. Advances in Agronomy 44 (1990): 55-85.
  17. Farshadfar E and Sutka J. “Biplot analysis of genotype environment interaction in durum wheat using the AMMI model”. Acta Agronomica Hungarica 4 (2006): 459-467.
  18. Fatemeh Bavandpori., et al. “Yield Stability Analysis of Bread Wheat Lines using Ammi Model”. Agricultural Communications1 (2016): 8-15.
  19. Mohammadi R., et al. “Interpreting genotype- environment interactions for durum wheat grain yields using non-parametric methods (2007).
  20. Pinthus MJ. “Estimate of genotypic value: A proposed method”. Euphytica 22 (1973): 121-123.
  21. Bajpai PK and Prabhakaran VT. “A new procedure of simultaneous selection for high yielding and stable crop genotypes”. The Indian Journal of Genetics 60 (2000): 141-146.
  22. Gauch HG. “Model selection and validation for yield trials with interaction”. Biometrics 44 (1988): 705-715.
  23. Gauch HG and Zobel RW. “AMMI analysis of yield trials”. In: Kang MS, Gauch HG (editions) Genotype by environment interaction. CRC Press. Boca Raton, FL (1996).
  24. Mohammadi R and Amri A. “Comparison of parametric and non-parametric methods for selecting stable and references adapted durum wheat genotypes in variable environments”. Euphytica 159 (2008): 419-432.
  25. Farshadfar E., et al. “Combining ability analysis of drought tolerance in wheat over different water regimes”. Acta Agronomica Hungarica 4 (2020b): 353-361.
  26. Maniruzzaman MZ Islam., et al. “Evaluation of yield stability of seven barley (Hordeum vulgare) genotypes in multiple environments using GGE biplot and AMMI model”. Open Agriculture 24 (2019): 284-293.
  27. Koutis K., et al. “Multi-environmental evaluation of wheat landraces by GGE biplot analysis for organic breeding”. Agricultural Science 1 (2012): 66-74.
  28. Zobel RW., et al. “Statistical analysis of a yield trial”. Agronomy Journal 80 (1988): 388-393.
  29. Freeman GH. “Modern statistical methods for analyzing genotype-environment interactions”. In: M.S. Kang (edition.), Genotype × Environment Interaction and Plant Breeding, Louisiana State University Agricultural Center, Baton Rouge, LA (1990): 118-125.




Citation: Mushtaq Ahmad., et al. “Stability and Scrutiny Using (Ammi): Model of Bread Wheat Over the Years in Cold Arid Harsh Conditions of Kargil and Zanaskar (Ladakh)- India". Acta Scientific Agriculture 4.10 (2020): 02-09.


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