Study of Ecotype and Sowing Date Interaction in Cumin (Cuminum cyminum L.) using Different Univariate Stability Parameters

Document Type : Research Article

Authors

• J Ghanbari
• Gh. R Khajoei-nejad
• Gh Mohammadinejad

Shahid Bahonar University, Kerman

10.22067/gsc.v15i1.43232

Abstract

Introduction
Cumin is one of the most important medicinal plants in Iran and today, it is in the second level of popularity between spices in the world after black pepper. Cumin is an aromatic plant used as flavoring and seasoning agent in foods. Cumin seeds have been found to possess significant biological and have been used for treatment of toothache, dyspepsia, diarrhoea, epilepsy and jaundice. Knowledge of GEI is advantageous to have a cultivar that gives consistently high yield in a broad range of environments and to increase efficiency of breeding program and selection of best genotypes. A genotype that has stable trait expression across environments contributes little to GEI and its performance should be more predictable from the main several statistical methods have been proposed for stability analysis, with the aim of explaining the information contained in the GEI. Regression technique was proposed by Finlay and Wilkinson (1963) and was improved by Eberhart and Russell (1966). Generally, genotype stability was estimated by the slope of and deviation from the regression line for each of the genotypes. This is a popular method in stability analysis and has been applied in many crops. Non-parametric methods (rank mean (R), standard deviation rank (SDR) and yield index ratio (YIR)), environmental variance (S2i) and genotypic variation coefficient (CVi) Wricke's ecovalence and Shukla's stability variance (Shukla, 1972) have been used to determine genotype-by-environment interaction in many studies. This study was aimed to evaluate the ecotype × sowing date interaction in cumin and to evaluation of genotypic response of cumin to different sowing dates using univariate stability parameters.

Materials and Methods
In order to study of ecotype × sowing date interaction, different cumin ecotypes: Semnan, Fars, Yazd, Golestan, Khorasan-Razavi, Khorasan-Shomali, Khorasan-Jonoubi, Isfahan and Kerman in 5 different sowing dates (26th December, 10th January, 25th January, 9th February and 24th February) were studied. The experiment was conducted during growing season of 2011-2012 in Agricultural Research field of Shahid Bahonar University of Kerman, Iran; and grain yield was measured in the end of the growing season. Combined ANOVA, Bartlett test and mean comparison (Duncan's multiple range test) was performed using SAS 9.1 software. Considering the significant interaction between ecotypes and sowing dates, non-parametric methods (rank mean (R), standard deviation rank (SDR) and yield index ratio (YIR)), and different methods of univariate stability parameters include: environmental variance (S2i), genotypic variation coefficient (CVi), Wricke's ecovalence, Shukla's stability variance, and Regression technique (Eberhart and Russell parameters) was applied to study Ecotype × Sowing date interaction. Calculation of different stability parameters were done by S116 and Excel softwares. In order to investigate the relationship between stability statistics, the Spearman's rank correlation coefficient was calculated by using SPSS 17.0 software.

Results and Discussion
Combined ANOVA revealed that significant differences among sowing dates, ecotypes and ecotype by sowing date interaction. More than 46 percent of variation in yield was devoted to the ecotype by sowing date interaction; on this basis, stability and adaptability studies were performed based on non-parametric methods, Eberhart and Russell regression method and univariate parameters. Based on non-parametric methods (rank mean (R), standard deviation rank (SDR) and yield index ratio (YIR)) Kerman and Khorasan-Shomali were identified as stable ecotypes, and based on environmental variance (S2i) and genotypic variation coefficient (CVi) parameters Khorasan-Razavi and Semnan ecotypes were diagnosed as stable while Kerman and Yazd ecotypes were categorized as unstable ecotypes. According to the results from Eberhart and Russell, Wricke's ecovalence and Shukla's stability variance parameters Isfahan and Golestan ecotypes were categorized as relatively stable ecotypes. Kerman ecotype showed specific adaptability to 24th February sowing date (favorable environment) while Semnan had specific adaptability reaction to 26th December sowing date (unfavorable environment). Khorasan-Shomali showed highest sensitivity reaction to different environments (sowing dates). According to the Spearman correlation the regression coefficient (bi) showed moderate correlation coefficient with Wi and σ2i statistics (rs = 0.567) and with other statistics in this study showed little correlation. Similar results in the study of Becker and Leon (1988) have been reported. Correlation between the deviation from regression (S2di) with Wi, σ2i, S2i and CVi statistics was positive and significant at 5% probability level. YIR and R statistics showed negative rank correlation and coefficient of determination (ri2) and SDR don’t show any significant correlation coefficient with other parametric statistics. Therefore, in this study, the results of these statistics did not match with parametric methods to introduce stable ecotypes.

Conclusions
Isfahan and Golestan ecotypes were categorized as relatively stable ecotypes. Kerman and Semnan ecotype showed specific adaptability reaction to 24th February sowing date (favorable environment) and 26th December sowing date (unfavorable environment) respectively. Khorasan-Shomali showed highest sensitivity reaction to different sowing dates.

Keywords

• Adaptability
• Cumin
• Ecotype
• Rank correlation
• Stability

20.1001.1.20081472.1396.15.1.8.2

---

References

1. Anandaraj, M. D., Prasath, K., Kandiannan, T., John Zachariah, V., Srinivasan, A. K. Jha, B. K., Singh, A. K., Singh, V. P., Pandey, S. P., Singh, N., Shoba, J. C., Jana K., Kumar R., and Uma Maheswari, K. 2014. Genotype by environment interaction effects on yield and curcumin in turmeric (Curcuma longa L.). Industrial Crops and Products 53: 358-364.

2. Asadi, Z. 2010. Evaluation of genotype×environment interaction in different cumin ecotypes at Kerman. MSc thesis, Graduate University of Advance Technology, Kerman, Iran. 132 pp.

3. Becker, H. C., and Leon, J. 1988. Stability analysis in plant breeding. Plant Breeding 101:1-23.

4. Bettaieb, R. I., Jabri-Karoui, I., Hamrouni-Sellami, I., Bourgou, S., Limam, F., and Marzouk, B. 2012. Effect of drought on the biochemical composition and antioxidant activities of cumin (Cuminum cyminum L.) seeds. Industrial Crops and Products 36:238-245.

5. Crossa, J. 1990. Statistical analysis of multilocation trials. Advances in Agronomy 44:55-85.

6. de la Vega, A. J., and Hall, A. J. 2002. Effect of planting date, genotype, and their interaction on sunflower yield. II. Components of oil yield. Crop Science 42:1202-1210.

7. de la Vega, A. J., Hall, A. J., and Kroonenberg, P. M. 2002. Investigating the physiological bases of predictable and unpredictable genotype by environment interactions using three-model pattern analysis. Field Crops Research 78:165-183.

8. Eberhart, S. A., and Russell, W. A. 1966. Stability parameters for comparing varieties. Crop Science 6:36-40.

9. Esmaeilzadeh Moghaddam, M., Zakizadeh, M., Akbari Moghaddam, H., Abedini Esfahlani, M., Sayahfar, M., Nikzad, A.R., Tabib Ghaffari, S.M., and Aeineh, A. L. 2000. Study of grain yield stability and genotype – environment interaction in 20 bread wheat lines in warm and dry areas of south of Iran. Electronic Journal of Crop Production 3(3): 179-200. (in Persian with English abstract)

10. Finlay, K. W., and Wilkinson, G. N. 1963. The analysis of adaptation in a plant breeding program. Australian Journal of Agriculture Research 14:742-754.

11. Fox, D. N., and Rosielle, A. 1982. Reducing the influence of environmental main effects of plant breeding environments. Euphytica 31:645-656.

12. Freeman, G. H., and Dowker, B. D. 1973. Statistical methods for the analysis of genotype-environments. Heredity 33:339-354.

13. Gomez, K. A., and Gomez, A. A. 1984. Statistical procedures for agricultural research, second ed. Wiley, New York.

14. Haufe, W., and Geidel, H. 1978. Zur Beurteilung der Ertragssicherheit von Sorten und Zuchtstämmen. I. Definitionen, Stabilitätsparameter und deren Interpretationsmöglichkeiten. Zeitschrift fur Pflanzenzüchtung 80: 24-37.

15. Huhn, M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. I. Vorschlag einiger auf Ranginformationnen beruhenden stabilitatsparameter. EDV in Medizin Und Biologie 10:112-117.

16. Kafi, M. 2002. Cumin (Cuminum cyminum): Production Technology and Processing. Mashhad: Ferdowsi University Press, pp 195.

17. Kang M.S. 1988. A rank-sum method for selecting high yielding, stable corn genotypes. Cereal Research Communication, 16:113-115.

18. Ketata, H. 1988. Genotype environment interaction, ICARDA, Proceeding of Biometrical technique for Cereal Breeders 16-32 pp.

19. Lin, C. S., and Binns, M. R. 1991. Assessment of a method for cultivar selection based on regional trial data. Theoretical and applied genetics 82: 505-509.

20. Mohammadinejad, G., and Rezai, A. M. 2005. Analysis of Genotype × Environment Interaction and Study of Oat (Avena sativa L.) Genotypes Pattern. JWSS - Isfahan University of Technology 9 (2):77-89.

21. Mohebodini, M., Dehghani, H., and Sabaghpour, S. H. 2006. Stability of performance in lentil (Lens culinaris Medik) genotypes in Iran. Euphytica 149:343-352.

22. Najafi Mirak, T. 2011. Study of grain yield stability of bread wheat genotypes in cold agro-climatic zone of Iran. Iranian Journal of Crop Sciences 13(2): 380-394. (in Persian with English abstract).

23. Rasamivelona, A., Gravois, K. A., and Dilday, R. H. 1995. Heritability and genotype_environment interactions for straithead in rice. Crop Science 35:1365-1368.

24. Pinthus, J. M. 1973. Estimate of genotype value: a proposed method. Euphytica 22:121-123.

25. Roostaei, M., Mohammadi, R., and Amri, A. 2014. Rank correlation among different statistical models in ranking of winter wheat genotypes. The crop journal 2:154-163.

26. Roy, D. 2000. Plant breeding analysis and exploitation of variation. Alpha Science International, Ltd. U. K.

27. SAS Institute. 2004. Base SAS 9.1 procedures guide. Cary (NC): SAS Institute Inc.

28. Shukla, G. K. 1972. Some statistical aspects of partitioning genotype-environmental components of variability. Heredity 29:237-245.

29. Soleimani, B., Khosh-Khui, M., and Ramezani, S. 2011. Planting date effects on growth, seed yield essential oil content and chemical composition of ajowan. Journal of Applied Biological Sciences 5 (3): 7-11.

30. Ullah, I., Ayub, M., Khan, M. R., Ashraf, M., Mirza, M. Y., and Yousef, M. 2007. Graphical analysis of multi-environment trial (MET) data in sunflower (Helianthus annuus L.) through clustering and GGE biplot technique. Pakistan Journal of Botany 39:1639-1646.

31. Vassilevska-Ivanova, R., and Naidenova, N. 2006. Assessment of the stability and adaptability of waxbloom and waxless pea (Pisum sativum L.) mutant lines. Scientia Horticulturae 109:15-20.

32. Wricks, G. 1962. Ube Eien method Zut Erfussung Der Okologischen streubreite in feldversuchen. Z. Pflanzenzuecht 47:92-96.

33. Yan, W., Kang, M. S., Ma, B., Woods, S., and Cornelius P. L. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Science 47:643-655.

34. Yates, F., and Cochran, W. G. 1938. The analysis of groups of experiments. The Journal of Agricultural Science 28:556-580.

35. Zaman, U., and Abbasi, A. 2009. Isolation, purification and characterization of a nonspecific lipid transfer protein from Cuminum cyminum. Phytochemistry 70:979-987.

36. Zewdie, Y., and Bosland, P. W. 2000. Evaluation of genotype, environment, and genotype-by-environment interaction for capsaicinoids in Capsicum annuum L. Euphytica 111:185-190.