ارزیابی اثر متقابل ژنوتیپ × محیط عملکرد و محتوی روغن ژنوتیپ‌های گلرنگ دیم از طریق روش رگرسیون و GGE بای‌پلات

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیأت علمی از مؤسسه تحقیقات کشاورزی دیم کشور (معاونت سرارود)، سازمان تحقیقات، آموزش و ترویج کشاورزی

2 عضو هیأت علمی از مؤسسه تحقیقات کشاورزی دیم کشور (معاونت سرارود)، سازمان تحقیقات، آموزش و ترویج کشاورزی،

چکیده

به‌منظور تجزیه اثرات متقابل ژنوتیپ × محیط برای صفات عملکرد و مقدار روغن دانه گلرنگ، آزمایش چندمحیطی با 15 ژنوتیپ (شامل 8 لاین اصلاحی، 6 رقم و یک شاهد) برای سه زمان کشت (پاییزه، انتظاری و بهاره) در چهار ایستگاه تحقیقات کشاورزی دیم شامل کرمانشاه، مراغه، کردستان و زنجان (در مجموع 21 محیط) طی سال‌های‌ زراعی 92-1390 انجام شد.از دو مدل رگرسیونی-عملکرد و نمودار دوبعدی (ژنوتیپ + ژنوتیپ×محیط) استفاده شد. نتایج تجزیه واریانس مرکب نشان داد که عامل‌های ژنوتیپ، محیط و اثر متقابل آنها برای دو صفت در سطح 1% معنی‌دار است. سهم ژنوتیپ، محیط و اثر متقابل آنها برای عملکرد به‌ترتیب 5، 62 و 24 و مقدار روغن 25، 45 و 22 درصد از تغییرات کل بود. با تجزیه رگرسیونی اختلاف معنی‌داری بین اجزای رگرسیون دو صفت مشاهده شد. بیشترین شاخص رگرسیون-عملکرد به ژنوتیپ‌های G5، G1 و G6 و رگرسیون-روغن به G5، G3 و G11 تعلق داشت. نمایش چندضلعی نمودار دوبعدی برای دو صفت سه گروه محیطی شناسایی کرد. دو محیط از مراغه برای عملکرد دانه، شش محیط کردستان برای میزان روغن، محیط‌های مطلوب بودند. بر اساس نمودار دوبعدی، ژنوتیپ‌های G10 و G5 برای عملکرد و پایداری و G11، G4 و G5 برای روغن و پایداری، برتر بودند. ضریب همبستگی، با رتبه بالایی بین مدل‌‌های رگرسیون و نمودار دوبعدی (ژنوتیپ + ژنوتیپ×محیط) در دو صفت به‌دست آمد. بر اساس نتایج حاصل از دو مدل تجزیه پایداری، ژنوتیپ G5 (رقم پدیده) از لحاظ عملکرد و میزان روغن، رقم برتر و پایداری شناخته شد که می‌توان آن را برای همه محیط‌های دیم توصیه کرد

کلیدواژه‌ها


عنوان مقاله [English]

Evaluation of genotype × environment interaction on yield and oil content of rainfed safflower genotypes by regression and GGE Biplot

نویسندگان [English]

  • Mehdi Jamshidmoghaddam 1
  • Sayyed Saeid Pourdad 2
1 OilsScientific member of Dry-land Agricultural Research Institute (Sararood Branch), Agricultural Research, Education and Extension Organization (AREEO),
2 ScieScientific member of Dry-land Agricultural Research Institute (Sararood Branch), Agricultural Research,
چکیده [English]

To analyze genotype × environment interactions (GEI) on yield and seed oil content of 15 safflower genotypes (including 8 breeding lines, 6 cultivars and one landrace), multi-environment trials were conducted in three sowing times (fall, entezari and spring) at four dryland agricultural research stations including Kermanshah, Maragheh, Kurdistan and Zanjan (totally 21 environments) during 2011-2013. The two models combined index (regression analysis + yield) and GGE biplot were used for stability analysis. The combined ANOVA revealed that genotype, environment, and GEI were highly significant for the two traits (P < 0.01). The sum of squares of genotype, environment, and GEI were accounted 5, 62 and 24% for yield, and 25, 45 and 22% for oil content.The result of regression analysis indicated that the regression components were significant in both traits. According to combined index, G5, G1, and G6 for yield, and G5, G3 and G4 for oil content were superior genotypes. The polygon view of the GGE biplot showed that all test environments were divided into 3 environmental groups for both traits. Two environments of Maragheh for yield and six environments of Kurdistan for oil content were favorable. Based on GGE biplot, G10 and G5 for yield and G11, G4 and G5 for oil content had a high combination of yield (or oil content) and stability. High rank correlation coefficients were obtained between regression and GGE biplot models in both traits. Based on the results of two models, G5 (Padideh) is superior in terms of yield and oil content and is recommended for all rainfed environments.

کلیدواژه‌ها [English]

  • Cold regions
  • (G + G × E) biplot
  • regression analysis
  • safflower
  • stability
  1. REFERENCES:

     

    1. Ada, R. (2012). Effects of winter and spring sowing on yield components of safflower genotypes. World Academy of Science, Engineering and Technology, 66, 622 - 626.
    2. Akbarpour, O. A., Dehghani, H. & Sorkhi-Lalehloo, B. )2012(. Study of grain yield stability of barley (Hordeum vulgare L.) promising lines in cold regions of Iran using regression methods. Iranian Journal of Crop Sciences, 14,155-170. (In Farsi).
    3. Dehghani, H., Sabaghpour, S. H., & Ebadi, A. )2010(. Study of genotype × environment interaction for chickpea yield in Iran. Agronomy Journal, 102, 1 – 8.
    4. Dia, M., Wehner, T. C., Hassell, R., Price, D. S., Boyhan, G. E., Olson, S., King, S., Davis, A. R., Tolla, G. E., Bernier, J., & Juarez, B. (2016). Value of locations for representing mega-environments and for discriminating yield of watermelon in the U.S. Crop Science, 56, 1726-1735.
    5. Eberhart, S. A. & Russell, W. A. (1966). Stability parameters for comparing varieties. Crop Science, 6, 36-40.
    6. Ebrahimi, F., Majidi, M. M., & Arzani, A. (2016). Oil and seed yield stability in a worldwide collection of safflower under arid environments of Iran. Euphytica, 212, 131 - 144.
    7. Elfadi, E., Reinbrecht, C., Frick, C., Von, S., Rudolphi, S. (2005). Genotype by environment interaction in safflower grown under organic farming system. Proceedings of 6th International Safflower Conference, June 6–10, Istanbul, Turkey.
    8. Esendal, E., Arslan, B., & Paşa, C. (2008). Effect of winter and spring sowing on yield and plant traits of safflower (Carthamus tinctorius L.). Proceedings of 7th International Safflower Conference, November 3-7, Wagga Wagga, Australia.
    9. Eskridge, K. M. (1990). Selection of stable cultivars using a safety-first rule. Crop Science, 30, 369 - 374.
    10. Eskridge, K. M. (1997). Evaluation of corn hybrids using the probability of outperforming a check based on strip-test data. Journal of Agricultural, Biological, and Environmental Statistics 2, 245 – 254.
    11. Eskridge, K. M., & Mumm, R. F. (1992). Choosing plant cultivars based on the probability of outperforming a check. Theoretical and Applied Genetics, 84, 494-500.
    12. Eskridge, K. M., Byrne, P. F., & Crossa, J. (1991). Selection of stable varieties by minimizing the probability of disaster. Field Crops Research, 27, 169-181.
    13. Flores, F., Moreno, M. T., Cubero, J. I. (1998). A comparison of univariate and multivariate methods to analyze environments. Field Crop Research, 56, 271-286.
    14. Gauch, H. G., & Zobel, R. W. (1996). AMMI analysis of yield trials. In M. S. Kang & H. G. Gauch (eds.) Genotype by environment interaction. (pp. 85-122) CRC Press, Boca Raton, FL.
    15. Grausgruber, H., Oberforster, M., Werteker, M., Ruckenbauer, P., & Vollmann, J. (2000). Stability of quality traits in Austrian-grown winter wheats. Field Crops Research, 66, 257-267.
    16. Hamdan, Y. A. S., Perez-Vich, B., Fernandez-Martinez, J. M. & Velasco, L. (2009). Novel safflower germplasm with increased saturated fatty acid content. Crop Science, 49, 127-132.
    17. Hühn, M. (1990). Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica, 47, 189-194.
    18. Jafari, M., Asghari Zakarya, R., Alizadeh, B., Sofalyan, O. & Zare, N. (2015). Study of seed yield stability in winter rapeseed (Brassica napus) genotypes using Eberhart and Russell’s method. Iranian Journal of Field Crop Sciences, 45, 585-592. (In Farsi).
    19. Jamshidmoghaddam, M. & Pourdad, S. S. (2013). Genotype×environment interactions for seed yield in rainfed winter safflower (Carthamus tinctorius L.) multi-environment trials in Iran. Euphytica, 190, 357-369.
    20. Johnson, R. C., and Dajue, L. (2008). Safflower winter survival and selection response relate to fall growth morphology and acclimation capacity. Crop Science, 48, 1872 - 1880. 
    21. Johnson, R. C., Petrie, S. E., Franchini, M. C., & Evans, M. (2012). Yield and yield components of winter-type safflower. Crop Science, 52, 2358-2364.
    22.  Knowles, P. F. (1989). Safflower. In G. Robbclen et al. (Eds.), Oilseed Crops of the World. (pp. 336-363). Their breeding & utilization. McCrow Hill Pub. Company. New York.
    23. Koutroubas, S. D., Papakosta, D. K., & Doitsinis, A. (2004). Cultivar and seasonal effects on the contribution of pre-anthesis assimilate to safflower yield. Field Crops Research, 90, 263 - 274.
    24. Laffont, G. L., Wright, K., & Hanafi, M. (2013). Genotype plus genotype × block of environments biplots. Crop Science, 53, 2332 - 2341.
    25. Mgonja, M. A., Mamuya, N. I., & Maeda, E. J. (1994). Use of safety rule in selecting stable barley cultivars. African Crop Science Journal, 2, 23 - 27.
    26. Mohammadi, R., & Amri, A. (2013). Genotype×environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica, 192, 227 - 249.
    27. Omidi, A. H., Shahsavari, M. R., Alhani, A., & Jahanbin, A. (2011). Selection of new safflower (Carthamus tintorius L.) genotypes for different climatic conditions using some stability parameters. Seed and Plant Improvement Journal, 27 (3), 287-303. (In Farsi).
    28. Pourdad, S. S. (2006). Safflower, Carthamus tinctorius L. In. L., Dajue & H. H. Mündel (eds.) Promoting the conservation and use of underutilized and neglected crops.7. (pp-83). Institute of Plant Genetics and Crop Plant Research, Gatersleben/International Plant Genetic Resources Institute, Rome Italy. (In Farsi).
    29. Pourdad, S. S., Jamshid Moghaddam, M. (2013). Study on genotype×environment interaction through GGE Biplot in spring safflower (Carthamus tinctorius L.). Journal of Crop Production and Processing, 2, 99-108. (In Farsi).
    30. Shukla, G. K. (1972). Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29, 237-245.
    31. Yan, W. (2006). Exploring multi-environment trial data using biplots. Retrieved October 11, 2011, from http://www.ggebiplot.com/workshop.htm.
    32. Yan, W. (2016). Analysis and handling of G × E in a practical breeding program. Crop Science, 56, 1-13.
    33. Yan, W., & Kang, M. (2003). GGE Biplot Analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press. Boca Raton, F. L., pp. 271.
    34. Yan, W., & Tinker, N. A. (2005). An integrated biplot system for displaying, interpreting, and exploring genotype x environment interaction. Crop Science, 45, 1004-1016.
    35. Yan, W., Frégeau-Reid, J., Pageau, D., & Martin, R. (2016). Genotype-by-environment interaction and trait associations in two genetic populations of oat. Crop Science, 56, 11-1145.
    36. Yan, W., Pageau, D., Frégeau-Reid, J. & Durand, J. (2011). Assessing the representativeness and repeatability of test locations for genotype evaluation. Crop Science, 51, 1603-1610.
    37. Yau, S. K. (2007). Winter versus spring sowing of rain-fed safflower in a semi-arid, high-elevation Mediterranean environment. European Journal Agronomy, 26, 249-256.
    38. Yue, G., Perng, S. K., Walter, T. L., Wassom, C. E., & Li, G. H. (1990). Stability analysis of yield in maize, wheat and sorghum and its implications in breeding programs. Plant Breeding, 104, 72-80.