ارزیابی خصوصیات چند ژنوتیپ‌ گندم نان ایرانی با استفاده از روش حداکثر درست‌نمایی محدودشده تحت شرایط تنش و عدم تنش شوری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری اصلاح ‌نباتات، دانشکدۀ کشاورزی، دانشگاه تربیت مدرس

2 دانشیار گروه اصلاح نباتات، دانشکدۀ کشاورزی دانشگاه تربیت مدرس

3 استادیار پژوهش مرکز تحقیقات شوری یزد

4 مربی پژوهش بخش غلات، مؤسسه تحقیقات اصلاح و تهیه نهال و بذر

چکیده

به‌کارگیری روش تجزیۀ آماری مناسب می‌تواند مکمل اجرای یک طرح آزمایشی دقیق برای اصلاح نباتات و دام باشد. در این آزمایش 33 ِژنوتیپ گندم ایرانی نان در قالب طرح بلوک‌های کامل تصادفی با سه تکرار در دو شرایط عدم تنش و تنش شوری در مزرعۀ تحقیقاتی مرکز ملی شوری ایران واقع در استان یزد کشت شدند. از برآوردگر حداکثر درستنمایی محدودشده (Restricted Maximum Likelihood, REML) برای بررسی ساختارهای مختلف واریانس-کوواریانس ژنوتیپی و برآورد همبستگی‌های ژنوتیپی و فنوتیپی برخی از صفات در لاین‌های گندم ایرانی نان در شرایط عدم تنش و تنش شوری استفاده شد. برآوردهای مختلف به‌روش REML نشان داد که صفات عملکرد دانه، عملکرد زیست‌توده و شاخص برداشت دارای تنوع ژنتیکی در شرایط نرمال و تنش شوری بودند که از این تنوع می‌توان در برنامه‌‌های اصلاحی گندم برای تحمل به شوری استفاده کرد. همچنین با استفاده از روش REML اثر متقابل ژنتیک × محیط برای هیچ‌‌‌‌‌کدام از صفات به‌ویژه عملکرد که یکی از مهم‌ترین صفات برای ارزیابی تحمل به تنش شوری در گندم است، مشاهده نشد. با مقایسۀ میانگین عملکرد دانه، لاین‌های SALT22، SALT29، SALT28 بیشترین عملکرد و لاین شمارۀ 6، رقم شاه‌پسند و لاین شمارۀ 13 کمترین عملکرد را در دو شرایط تنش و نرمال داشتند. با استفاده از برآوردگر REML همبستگی ژنتیکی مثبت و معنی‌‌داری بین عملکرد دانه با زیست‌توده (97/0) و شاخص برداشت (94/0) در دو شرایط عدم تنش و تنش شوری و همبستگی منفی و معنی‌‌‌‌داری بین عملکرد دانه و تعداد روز تا رسیدگی (32/0-) در شرایط تنش شوری برآورد شد. ازاین‌رو امکان انتخاب ژنوتیپ‌های زودرس پرمحصول در شرایط تنش شوری به‌ویژه در محل اجرای آزمایش (یزد) وجود دارد و می‌توان گزینش برای بهبود عملکرد بیشتر در شرایط تنش شوری را انجام داد.

کلیدواژه‌ها

عنوان مقاله [English]

Evaluation of some properties of Iranian wheat genotypes in normal and salt-stressed conditions using Restricted Maximum Likelihood (REML)

نویسندگان [English]

  • Omid Ali Akbarpour 1
  • Hamid Dehghani 2
  • Mohammad Javad Rousta 3
  • Ashkbus Amini 4
1 Department of Plant Breeding, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran.
2 Faculty member of Iranian National Salinity Research Center, Yazd, Iran
3 Faculty member of Iranian National Salinity Research Center, Yazd, Iran.
4 Faculty member of Seed and Plant Improvement Institute, Karaj, Iran
چکیده [English]

Applying an appropriate statistical analysis is complementary for conducting a robust experimental design in plant and animal breeding. In these experiments 33 Iranian bread wheat genotypes, cultivated in a randomized complete blocks design with three replications in two normal and saline conditions were evaluated at the field of National Salinity Research Center located in Yazd province, Iran. The restricted maximum likelihood (REML) was used to evaluate the different genotypic variance-covariance structures and to estimate the genotypic and phenotypic correlations of some of Iranian wheat traits under two normal and salt-stressed conditions. The Using different estimation by REML method the traits of grain yield, biological yield and harvest index had different and significant values across two conditions, this genetic variability can be used for salinity tolerance of bread wheat in breeding programs.. In addition, genotype by environment interaction for all traits was not significant, especially for grain yield as important trait for evaluation of salinity tolerance in wheat. The means comparisons of genotypes showed that the SALT22, SALT29 and SALT28 had the highest values and line No. 6, Shahpasand and line No.13 had the lowest values for grain yield, respectively. There were significantly positive genetic correlation between yield with biological yield (0.97) and harvest index (0.94) in combined analysis and negative genetic correlation for days to maturity with grain yield (-0.32) in saline condition by REML estimator. So, the selection of early maturing genotypes with higher yield in the saline condition, especially in the location of conducted experiment (Yazd) is achievable and selection can be done to improve the performance of salinity stress.

کلیدواژه‌ها [English]

  • Restricted Restricted Maximum Likelihood
  • salt
  • Wheat
  • Mixed models

مراجع

Acevedo, E. (1991). Improvement of winter cereal crops in Mediterranean environments: use yield, morphological and physiological traits. In. Acevedo, E., Conesa, A. P., Monneveux, P. & Srivastava, P. (Eds.) Physiology breeding of winter cereals for stressed Mediterranean environments. (pp. 273-305). Montpellier, France, INRA.
Acevedo, E., Silva, P. & Silva, H. (2002). Wheat growth and physiology. http://www.fao.org/DOCREP/006/Y4011E/y4011e06.htm.
Ali, Y., Aslam, Z., Sarwar, G. & Hussain, F. (2005). Genotypic and environmental interaction in advanced lines of wheat under salt-affected soils environment of Punjab, International Journal of Environment Science and Technology, 2(3), 223-228.
Ashraf, M. (2004). Some important physiological selection criteria for salt tolerance in plants. Flora, 199, 361-376.
Bernardo, R. (1996). Best linear unbiased prediction of the performance of crosses between untested maize inbreds. Crop Science, 36, 872-876.
Botella, M. A., Rosado, A., Bressan, R. A. & Hasegawa, P. M. (2005). Plant adaptive responses to salinity stress. In: Jenks, M. A. & Hasegawa, P. M. (Eds.) Plant abiotic stress. (pp. 38–62). Blackwell Publishing, Oxford.
Burgueño, J., Cadena, A., Crossa, J., Banziger, M., Gilmour, A. & Cullis, B. (2000). User's guide for spatial analysis of field variety trials using ASREML. Cimmyt, Mexico.
Cockerham, C. C. (1963). Estimation of genetic variances. In: Hanson, W. D. & Robinson, H. F. (Eds.) Statistical genetics and plant breeding. (Vol. 982). (pp. 53-94). NAS - Natl. Res. Counc. Publ, Washington, DC.
Dixit, P.N. & Deli, C. (2010). Impact of spatially variable soil salinity on crop physiological properties, soil water content and yield of wheat in a semi arid environment. Australian Journal of Agricultural Engineering, 1, 93-100.
DeLacy, I.H., Cooper, M. & Basford, K.E. (1996). Relationships among analytical methods used to study genotype-by-environment interactions and evaluation of their impact on response to selection. In: M. S. Kang. & H. G. Jr. Gauch. (Eds.) Genotype-by- Environment Interaction. (pp. 51–84).CRC Press, Boca Raton, Florida.
FAO. (2005). Global network on integrated soil management for sustainable use of salt-affected soils. Rome, Italy: FAO Land and Plant Nutrition Management Service. http://www.fao.org/ag/agl/agll/spush.
Flowers, T. J. (2004). Improving crop salt tolerance. Journal of Experimental Botany, 55, 307-319.
Hasegawa, P. M., Bressan, R. A., Zhu, J.-K. & Bohnert, H. J. (2000). Plant cellular and molecular responses to high salinity. Annual Review of Plant Physiology and Plant Molecular Biology, 51, 463–499.
Henderson, C. R. (1984). Applications of Linear Models in Animal Breeding. Guelph, Ont.: University of Guelph.
Holland, J. B., Nyquist, W. E. & Cervantes-Martínez, C. T. (2003). Estimating and interpreting heritability for plant breeding: An update. In: Plant breeding reviews (Vol. 22). (pp. 9-112).Wiley, New York.
Holloway, R. & Alston, A. (1992). The effects of salt and boron on growth of wheat. Crop and Pasture Science, 43, 987-1001.
Holland, J. B. (2006). Estimating genotypic correlations and their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop Science 46, 642-654.
Läuchli, A. & Epstein, E. (1990). Plant responses to saline and sodic conditions. In: K.K.Tanji (Ed.). Agricultural salinity assessment and management. (pp. 113–137). ASCE manuals and reports on engineering practice, ASCE New York. No: 71.
Littell, R., Milliken, G., Stroup, W. & Wolfinger, R. (2006) SAS System for Mixed Models. Second edition. Cary, NC: SAS Institute.
Liu, B. H., Knapp S. & Birkes, D. (1997). Sampling distributions, biases, variances, and confidence intervals for genetic correlations. Theoretical and Applied Genetics, 94, 8-19.
Mode, C. J. & Robinson, H. F. (1959). Pleiotropism and the genetic variance and covariance. Biometrics, 15, 518-537.
Munns, R. (1993). Physiological processes limiting plant growth in saline soils-some dogmas and hypotheses. Plant Cell and Environment, 16, 15-24.
Munns, R., Husain, S., Rivelli, A. R., James, R., Condon, A. G., Lindsay, M., Lagudah, E., Schachtman, D. & Hare, R. (2002). Avenues for increasing salt tolerance of crops, and the role of physiologically-based selection traits. Plant Soil, 247, 93-105.
Narjesi V., Majidi Hervan, E., Zali A., Mardi, M. &  Naghavi, M. R. (2010). Effect of salinity stress on grain yield and plant characteristics in bread wheat recombinant inbred lines. Iranian Journal of Crop Sciences, 12, 291 - 304.
Pessarakli, M. & Szabolcs, I. (2011). Soil salinity and sodicity as particular plant/crop stress factors. In: Pessarakli, M. (Ed.), Handbook of Plant and Crop Stress. (pp. 3-21).3rd Edition, Revised and Expanded. Taylor and Francis, Florida, CRC Press.
Poustini, K. & Siosemardeh, A. (2004). Ion distribution in wheat cultivars in response to salinity stress. Field Crop Research, 85, 125-133.
Qureshi, R. H., Rashid, A. & Ahmad, N. (1990). A procedure for quick screening of wheat cultivars for salt tolerance. In. El Bassam, N., Dambroth, M. & Loughman, B. C. (Eds.) Genetic Aspects of Plant Mineral Nutrition. (pp. 315–324), Kluwer.
Rasch, D. & Masata, O. (2006). Methods of variance component estimation. Czech Journal of Animal Science. 51 (6), 227–235.
Rashid, A. (1986). Mechanism of salt tolerance in wheat (Triticum aestivum L.). PhD Thesis, Department of Soil Science, University of Agriculture, Faisalabad, Pakistan.
Reynolds, M. P., Ortiz-Monasterio, J. I. & McNab, A. (2001). Application of Physiology in WheatBreeding. Mexico, D. F. CIMMYT.
Saboora, A., Kiarostami, K., Behroozbayati, F. & Hajihashemi, S. (2006). Salinity (NaCl) tolerance of wheat genotypes at germination and early seedling growth. Pakistan Journal of Biological Sciences, 9(11), 2009-2021.
Rezvani Moghaddam, P. & Koocheki, A. (2001). Research history on salt affected lands of Iran: Present and future prospects – Halophytic ecosystem. International Symposium on Prospects of Saline Agriculture in the GCC countries, Dubai, UAE.
Richards, R. A. (1987). Physiology and the breeding of winter-grown cereals of dry areas. In. Srivastava, J. P., Porceddu, E., Acevedo, E. & Varma, S. (Eds.) Drought tolerance in winter cereals. (pp. 133-150). Chichester, UK, Willey.
Sardouie-Nasab, S., Mohammadi-Nejad, G. & Nakhoda, B. (2014). Field screening of salinity tolerance in Iranian bread wheat lines. Crop Science, 54, 1489-1496.
SAS/STAT (2008). SAS/STAT® 9.2 Users Guide. SAS Institute Inc., Cary, NC, USA.
Satterthwaite, F. E. (1946). An approximate distribution of estimates of variance components. Biometrics Bulletin, 2, 110-114.
Searle, S.R, Casella, G. & McCulloch, C. (1992). Variance components. Wiley, New York.
Singh, R.K. (2006). Breeding for salt tolerance in rice. IRRI, Philippines.
Snedecor, G. W. (1956). Statistical Methods. Iowa State University Press, Ames, IA.
Tester, M. & Davenport, R. J. (2003). Na+ tolerance and Na+ transport in higher plants. Annals Botany, 91, 503-527.
Yang, R. C. (2002). Likelihood-based analysis of genotype–environment interactions. Crop Science, 42, 1434-1440.
Yang, R. C. (2010). Towards understanding and use of mixed-model analysis of agricultural experiments. Canadian Journal of Plant Science, 90, 605-627.
Yang, R. C. & Baker, R. J. (1991). Genotype-environment interactions in two wheat crosses. Crop Science,31, 83-87.
Yang, R. C. (2010). Towards understanding and use of mixed-model analysis of agricultural experiments. Canadian Journal of Plant Science, 90, 605-627.
Zhu, J. K. (2001). Plant salt tolerance. Trends in Plant Science, 6, 66-71.

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  • تاریخ دریافت: 31 خرداد 1393
  • تاریخ بازنگری: 20 دی 1393
  • تاریخ پذیرش: 21 دی 1393

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