آنالیز شاخص گزینش جهت معرفی ژنوتیپ‌های برتر و با عملکرد دانه بالا در کینوا (Chenopodium quinoa, Willd)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته دکتری، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

2 استاد، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

3 دانشجوی دکتری، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

4 استاد، گروه بیوتکنولوژی وبه نژادی گیاهی ، دانشکده علوم کشاورزی، دانشگاه فردوسی ، مشهد، ایران

5 استاد،گروه بانک ژن، مؤسسه تحقیقات ژنتیک گیاهی و گیاهان زراعی لایبنیز (IPK)، آلمان

چکیده

در برنامه‌های به‌نژادی گیاهان، انتخاب یکی از مهم‌ترین مراحل و کارآیی آن به میزان زیادی وابسته به تنوع ژنتیکی جمعیت و وراثت‌پذیری صفات است. با توجه به پیچیده بودن وراثت عملکرد، انتخاب مستقیم برای بهبود آن چندان موثر نمی‌باشد، بنابراین می‌توان با استفاده از روش‌های آماری چند متغیره اطلاعات لازم برای گزینش غیرمستقیم جهت بهبود عملکرد دانه را به‌دست آورد. هدف از این پژوهش بررسی روابط بین صفات مهم زراعی، ارزیابی شاخص‌های گزینش پایه و ارائه بهترین شاخص‌ها به‌منظور بهبود عملکرد دانه و شناسایی بهترین ژنوتیپ‌های کینوا جهت ادامه برنامه به‌نژادی به‌منظور معرفی رقم بود. بدین منظور 60 ژنوتیپ کینوا تهیه شده از موسسه IPK آلمان در قالب طرح بلوک‌های کامل تصادفی با 3 تکرار در سال 1401 در مزرعه تحقیقاتی واقع در شهرستان کوهدشت مورد ارزیابی قرار گرفتند. نتایج تجزیه علیت فنوتیپی و ژنوتیپی عملکرد دانه نشان داد که دو صفت وزن هزار دانه و تعداد خوشه در بوته دارای بیش‌ترین اثر مستقیم مثبت و معنی‌دار بر عملکرد دانه ژنوتیپ‌های مورد مطالعه بودند. همچنین استفاده از ضرایب همبستگی فنوتیپی و ژنوتیپی و صفات ردیف اول وارد شده در مدل تجزیه علیت عملکرد دانه به‌عنوان ارزش اقتصادی، بیش‌ترین بهره ژنتیکی صفات را به‌دنبال داشت و بنابراین می‌توانند شاخص‌های مطلوب و مناسبی برای گزینش ژنوتیپ‌های برتر کینوا باشند.

کلیدواژه‌ها

عنوان مقاله [English]

Analysis of the selection index to introduce superior genotypes with high grain yield in quinoa(Chenopodium quinoa Willd)

نویسندگان [English]

  • Ebrahim Sourilaki 1
  • Babak Rabiei 2
  • Vahid Jokarfard 3
  • Hassan Marashi 4
  • Andreas Börner 5
1 Ph.D. graduate, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
2 Professor, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3 Ph. D. Student, Department of Plant Production and Genetic Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
4 Professor, Department of Biotechnology and Plant Breeding, Faculty of Agricultural Sciences, University of Ferdowsi, Mashhad , Iran
5 Professor, Department of Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Leibniz, Germany
چکیده [English]

In plant breeding programs, selection is one of the most important steps, and its efficiency is highly depends on the genetic diversity of the population and the heritability of traits. Due to the complexity of grain yield inheritance, direct selection is not very effective to improve it, so it is possible to obtain the necessary information for indirect selection to improve selection for grain yield by using multivariate statistical methods. The purpose of this research was to investigate the relationships between important agricultural traits, evaluate basic selection indices and provide the best indices to improve grain yield and identify the best quinoa genotypes to continue the breeding program to introduce the cultivar. For this purpose, 60 quinoa genotypes received from IPK Institute of Germany and were evaluated in the frame of randomized complete block design with 3 replications in 2022 in the research farm located in Kohdasht city. The results of phenotypic and genotypic path analysis of grain yield showed that the two traits of 1000-grain weight and number of panicle per plant had the most positive and significant direct effect on the grain yield of the studied genotypes. Also, the use of phenotypic and genotypic correlation coefficients and the first row traits included in the path analysis model of grain yield as economic value led to the highest genetic benefit of the traits and therefore, they can be good and suitable indicators for the selection of superior quinoa genotypes.

کلیدواژه‌ها [English]

  • Genetic advance
  • genotypic correlation
  • path analysis
  • relative efficiency

مراجع

Ahmadpour, S., Darvishzadeh, R.,& Sofalian, O. (2018). Selection indices for yield improvement of sunflower under normal and salt stress conditions. Journal of Crop Breeding, 10(25), 91 -100. (In Persian).
Albayrak, S.,&Töngel, Ö. (2006). Path analyses of yield and yield-related traits of common vetch (Vicia sativa L.) under different rainfall conditions. Anadolu Tarım Bilimleri Dergisi, 21(1), 27-32.‏
Alipour, H., Abdi, H., &Bihamta, M. R. (2021). Path analysis of wheat grain yield with overcoming multi -collinearity of traits. Journal of Crop Breeding, 13(39), 122 -129. (In Persian).
Ariyo, O. J. (1995). Correlations and path-coefficient analysis of components of seed yield in soybeans. African Crop Science Journal, 3(1), 29-33.‏
Asghar, M.J.,& Mehdi, S.S. (2010). Selection indices for yield and quality traits in sweet corn. Pakistan Journalof Botany, 42, 775-789.
Bazile, D., Jacobsen, S. E.,& Verniau, A. (2016). The global expansion of quinoa: trends and limits. Frontiers in Plant Science, 7(622), 1-6
Beyrami, H., Rahimian, M. H., Salehi, M., Yazdani Biouki, R., Shiran-Tafti, M.,&Nikkhah, M. (2020). Effect of irrigation frequency on yield and yield components of quinoa (Chenopodium quinoa Willd) under saline condition. Journal of Agricultural Science and Sustainable Production, 30(3), 347–357. (In Persian).
Bhargava, A., Shukla, S.,& Ohri, D. (2006). Chenopodium quinoa an Indian perspective. Industrial crops and products, 23(1), 73-87.
Bhargava, A., Shukla, S.,&Ohri, D. (2007). Genetic variability and interrelationship among various morphological and quality traits in quinoa (Chenopodium quinoa Willd.). Field Crops Research, 101(1), 104-116.‏
Bhargava, A., Shukla, S.,&Ohri, D. (2008). Implications of direct and indirect selection parameters for improvement of grain yield and quality components in Chenopodium quinoa Willd. International Journal of Plant Production, 2(3), 183-192.‏
Bhatt, G. M. (1973). Significance of path coefficient analysis in determining the nature of character association. Euphytica, 22(2), 338-343.‏
Bos, I. and Caligari, P. 2007. Selection Methods in Plant Breeding. 2nd Edn. Springer, Berlin, DE.
De Santis, G., D’Ambrosio, T., Rinaldi, M. and Rascio, A. 2016. Heritabilities of morphological and quality traits and interrelationships with yield in quinoa (Chenopodium quinoa Willd.) genotypes in the Mediterranean environment. Journal of Cereal Science, 70: 177-185.‏
Esfandiyari, j.,& Fotokian, M. (2020). Investigating the diversity and evaluating the relationships between morphological traits of quinoa genotypes. The 7th National Congress on Biology and Natural Sciences of Iran,Tehran. (In Persian).
Esteki, M., Daneshmand Vaziri, M., Bagheri Todeshki, H.و&Manouchehri, H. (2014). Quinoa. Journal of Agriculture and Animal Husbandry, 41-43. (In Persian).
Garcia, M., Condori, B.,& Castillo, C. D. (2015). Agroecological and agronomic cultural practices of quinoa in South America. Quinoa: Improvement and Sustainable Production, 25-46.‏
Hazel, L.N. (1943). The genetic basis for constructing selection indexes. Genetics, 28(6), 476 -490.
Jokarfard, V.,& Rabiei, B. (2020). Selecting superior and high yielding recombinant inbred lines of an F11 rice population using index selection method. Cereal Research ,10(1), 19-32. (In Persian).
Karimi, S. H. (2018). Assessing adaptation and diversity of quinoa ecotypes by morphological SSR markers in different moisture conditions. Doctoral dissertation. MSc Thesis. Bu-Ali Sina University. Hamadan, Iran. (In Persian).
Kaya, E.,&Aydemir, S. K. (2020). Determining the forage yield, quality and nutritional element contents of quinoa cultivars and correlation analysis on these parameters. Pakistan Journal of Agricultural Sciences, 57(2), 311-317.‏
Khavari Khorasani, S.,& Mahdi poor, A. (2018). Genetic improvement of grain yield by determination of selection index in single cross hybrids of maize (Zea mays L.). Plant Genetic Researches, 5(1), 1 -18. (in Persian).
Mohammadi, R., Geravandi, M., Haghparast, R., Rajabi, R., Abdulahi, A., Malekhosseini, R., Yarkarami, K.,& Shahsavari, B. (2020). Study of grain yield and agro - physiological characteristics of some promising rainfed bread wheat genotypes under no -till condition. Journal of Crop Breeding, 11(32), 207-217. (In Persian).
Rabbani, B., Khoramivafa, M., Saeidi, M., Bagheri, M.,& Zarei, L. (2022). Study the relationship between agronomical traits and mineral elements of grain in three genotypes of quinoa (Chenopodium quinoa Willd) under effect of planting date and planting density. Cereal Biotechnology and Biochemistry, 1(3), 390-413. (In Persian).
Rabiei, B., Valizadeh, M., Ghareyazie, B.,& Moghaddam, M. (2004). Evaluation of selection indices for improving rice grain shape. Field Crops Research, 89(2 -3): 359–367.
Rahimi, M.,& Rabiei, B. (2011). The application of selection indices on improvement of grain yield in rice (Oryza sativa L.). Agronomy Journal, 90, 39-49. (In Persian).
Repo-Carrasco, R., Espinoza, C.,& Jacobsen, S. E. (2003). Nutritional value and use of the Andean crops’ quinoa (Chenopodium quinoa) and kañiwa (Chenopodium pallidicaule). Food Reviews International, 19(1-2), 179-189.‏
Rezai, A.M.,& Yousofi Azar, M. (2008). Comparison of direct and indirect selection methods based on selection indices in wheat lines in drought and non-drought conditions. Journal of Water and Soil Science, 12(45), 21-32. (In Persian).
Salehi, M.,& Saeidi, G. (2013). Selection indices for seed yield improvement in sesame (Sesamum indicum L.). Iranian Journal of Field Crops Research, 10(4), 667 -673. (In Persian).
Shah, S. S., Shi, L., Li, Z., Ren, G., Zhou, B.,& Qin, P. (2020). Yield, agronomic and forage quality traits of different quinoa (Chenopodium quinoa Willd.) genotypes in northeast China. Agronomy, 10(12), 1-15.‏
Smith, H.F.(1936). A discriminant function for plant selection. Annals of Eugenics, 7(3), 240 -250.
Souri Laki, E., Rabiei, B., Jokarfard, V., Marashi, H.,& Börner, A. (2022). Evaluation of important agronomic traits related to yield and identification of superior quinoa genotypes. Cereal Research, 12(1), 99-114.
Tahmasedi, A. K., Darvishzadeh, R., Fayaz Moghaddam, A., Gholinezhad, E.,& Abdi, H. (2021). Phenotypic variation of indigenous sesame landraces in Urmia climate. Journal of Crop Breeding, 12(36), 30 -38. (In Persian).
Tiwari, J. K.,& Ameen, G. (2022). Yield contributing traits of quinoa (Chenopodium quinoa) genotypes using multivariate statistics. The Journal of Research Angrau, 50(2), 20-27.
Yan, W. (2014). Crop Variety Trials: Data Management and Analysis. John Wiley and Sons Inc., New York, USA.
Yan, W., Frégeau-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.

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