انتخاب صفات موثر بر عملکرد دانه به‌عنوان شاخص‌های انتخاب در ژنوتیپ‌های در حال پیشرفت یک جمعیت F6 برنج (Oryza sativa L.)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته دکتری، گروه بیوتکنولوژی کشاورزی، پردیس دانشگاهی، دانشگاه گیلان، رشت، ایران

2 دانشیار، گروه بیوتکنولوژی کشاورزی، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

3 استادیار پژوهش، مؤسسه تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، رشت، ایران

4 استاد، گروه بیوتکنولوژی کشاورزی، دانشکده علوم کشاورزی، دانشگاه گیلان، رشت، ایران

چکیده

به­منظور بررسی روابط بین صفات مؤثر بر عملکرد دانه و نیز تعیین روابط علت و معلولی بین آن­ها، تعداد 137 لاین نوترکیب یک جمعیت F6 برنج در قالب طرح آگمنت به­همراه چهار رقم شاهد (طارمی دیلمانی، هاشمی، صالح و علی کاظمی) در قالب یک طرح بلوکی با چهار بلوک برای نه صفت مهم زراعی طی دو سال زراعی 1394 و  1395 ارزیابی شدند. نتایج حاصل از تجزیه واریانس (برای هر سال به‌طور جداگانه) اختلاف معنی­دار بین لاین­های مورد بررسی از نظر کلیه صفات مورد ارزیابی را نشان داد. اختلاف بین ارقام شاهد نیز برای کلیه صفات به­جز طول و عرض برگ معنی­دار بود. محاسبه ضرایب همبستگی ساده بین صفات برای هر سال به‌طور جداگانه نشان داد که صفات وزن صد دانه، تعداد پنجه بارور، تعداد دانه پر در خوشه، طول خوشه، طول برگ و عرض برگ همبستگی مثبتی را با عملکرد دانه داشتند. تجزیه رگرسیون گام به گام عملکرد دانه برای داده­های هر سال نیز نشان داد که در سال اول، دو صفت وزن صد دانه و تعداد دانه پر در خوشه و در سال دوم، سه صفت وزن صد دانه، تعداد دانه پر در خوشه و طول خوشه به­ترتیب وارد مدل رگرسیون شدند که 62 درصد و 73 درصد از تغییرات عملکرد دانه را به­ترتیب برای سال اول و دوم توجیه کردند. نتایج تجزیه علیت عملکرد دانه (برای هر سال و مجموع دو سال) نشان داد که بعد از صفت وزن صد دانه (926/0)، صفات تعداد پنجه در بوته (739/0) و تعداد دانه پر در خوشه (682/0) بیش­ترین اثر مستقیم مثبت را بر عملکرد دانه داشتند و می­توانند به­عنوان شاخص­های انتخاب جهت بهبود عملکرد دانه در برنج در نظر گرفته شوند. همچنین بر اساس این صفات، به­ترتیب لاین‌های 9، 132، 133، 24، 52، 83، 5، 40، 78 و 19 به‌عنوان لاین‌های پرمحصول انتخاب شدند و از این­رو این لاین­ها می‌توانند به‌عنوان لاین‌های پرمحصول و نوید‌بخش جهت مطالعات آتی به‌نژادی مورد استفاده قرار گیرند.

کلیدواژه‌ها


عنوان مقاله [English]

Choice of the effective traits on grain yield as selection indices in progressive F6 populations in rice (Oryza sativa L.)

نویسندگان [English]

  • Mohammad Ali Ahmadi Shad 1
  • Mohammad Mehdi Sohani 2
  • Ali Akbar Ebadi 3
  • Habibollah Samizadeh Lahiji 4
  • Maryam Hosseini Chaleshtori 3
1 Ph. D. Graduated, Dept. of Agricultural Biotechnology, Faculty of Campus, University of Guilan, Rasht, Iran
2 Assoc. Prof., Dept. of Agricultural Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
3 Research Assist. Prof., Rice Research Institute of Iran, Agricultural Research, Education and Extension Organization ‎‎(AREEO), Rasht, Iran
4 Prof., Dept. of Agricultural Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
چکیده [English]

To investigate the relationships among effective traits on grain yield and determination of and the relationships among them, 137 rice recombinant lines from F6 population along with four control cultivars (Tarom Deilamani, Hashemi, Saleh and Ali Kazmi) were evaluated for nine important agronomic traits and two crop seasons (2015-2016) in a augment design with four blocks. The results of analysis of variance indicated a significant difference among the lines for all evaluated traits. Also, the differences among control varieties were significant for all traits except for leaf length and width. Simple correlation coefficients were calculated for each year separately and showed that 100 seed weight, number of fertile tillers, number of filled grains, panicle length, leaf length and leaf width had a positive correlation with grain yield. Multiple regression analysis by stepwise method was calculated for each year separately and the results showed that for the first year, 100-grain weight and number of filled grain per panicle traits were entered into model, respectively, that explained 62 percent of grain yield variations. For the second year, 100-grain weight, number of filled grain per panicle and number of panicles traits were entered into model, respectively, that explained 73 percent of grain yield variations. Also based on path analysis results, after 100-grain weight (0.926), the number of tiller (0.739) and number of filled grain per panicle (0.682) traits have the most and positive direct effect with grain yield and thus, these traits could be considered as selection criteria for grain yield improvement in rice. The lines include 9, 132, 133, 24, 52, 83, 5, 40, 78 and 19 were selected as elite lines based on the above criteria. Due to the fact that these traits had a great effect on yield, the selected genotypes can effectively be used as high yielding lines for future studies based on these indices.

کلیدواژه‌ها [English]

  • Path analysis
  • Stepwise regression
  • Yield
  • Recombinant Lines
Agahi, K., Fotoukian,M. H. and Uneasy, Z. 2014. Genetic variation and correlation of agronomic traits in some varieties of rice (Oryza sativa L.) in Iran. Iranian Journal of Biology 25(1):97-110. (In Persian with English Abstract).##Aghazadeh, K., Nematzadeh,G. and Babaeian-Jelodar, N.A.2008. The genetic diversity of rice cultivars (Oryza sativa L.) using quantitative traits: New Agricultural Science3(9): 1-12. (In Persian with English Abstract).##Allard, R. W. 1960. Principles of plant breeding. John Willey and Sons Inc., New York. 485 p.##Aminpanah, H. and Sharifi,P. 2011. Sequential path analysis for determination of relationships between yields related characters with yield in rice (Oryza sativa L.). African Journal of Agricultural Research 6(28): 6100-6106.##Ariyo, O. J., Pkenova,M. E. and Fatokun,C. A. 1986. Plant character correlations and path analysis of pod yield in okra. Euphytica 36: 677-686.##Bagheri, N.A., Babaeian-Jelodar,N. A. and Pasha, A. 2011. Path coefficient analysis for yield and yield components in diverse rice (Oryzasativa L.) genotypes. Biharean Biologist 5(1): 32-35.##Blasubramanian, V., Ladha,J. K. and Dening, G. L.1999. Resource management in rice systems: Nutrient. Kluwer Academic Publishers, London.##Bluchzhi, A. B and Kiyani, G.2015. Determination of the selection criteria for improving rice (Oryzasativa L.) yield using path analysis. Journal of Crop Breeding 5(12): 75-84. (In Persian with English Abstract).##Dato Seri, Y. B. 2003. Modernizing the rice farming community to meet social and business needs: The way forward. 3-6. In: Modern rice farming. Proceedings of International Rice Conference. October 13-16, 2003, Alor, Setar, Kedah, Malaysia.##Dorosty, H., Motahar, Y. and Ghannadha, M. R. 2004. Genetic diversity based on agronomic traits of rice advanced lines and varieties. Seed and Plant Journal 20 (2): 137-147. (In Persian with English Abstract).##Gunasekaran, M., Nadarajan, N. and Netaji, S. V. S. R. K. 2010. Character association and path analysis in inter-racial hybrids in rice (OryzaSativa L.). Electronic Journal of Plant Breeding
1(2): 956- 960.##Honarnejad, R. 2003. Study of correlation between some quantitative traits and grain yield in rice (Oryza sativa L.) using path analysis. Iranian Journal of Crop Sciences 4(1):35-35. (In Persian with English Abstract).##SES. 2002. Standard evaluation system for rice. International Rice Research Institute, Manila, Philippines.##Moosavi, M., Ranjbar, G. A.,Zarrini,H. N. and Gilani, A. 2015. Correlation between morphological and physiological traits and path analysis of grain yield in rice genotypes under Khuzestan conditions. Biological Forum 7(1): 43-47.##Moumeni, A. 1995. Study of correlations and path analysis for some of the important agronomy traits related to yield in rice varieties and hybrids. M. Sc. Dissertation, Tehran University, Tehran, Iran. (In Persian).##Rahim Souroush, H., Mesbah, M. and Hossain Zadeh, A. H. 2004. A study of relationship between grain yield and yield components in rice. Iranian Journal of Agricultural Science 35 (4): 983-993. (In Persian with English Abstract).##Rahimi, M., Rabiei, B., Ramezani, M. and Movafegh, S. 2010.Assessment of agronomic traits and determination of variables for breeding yield in rice. Iranian Journal of Field Crop Researches 8 (1): 111-119.##Rahnemaie, T., Vaezi., S.,Mozafar,J. and Boushehri,S. N. 2008. Correlation and path analysis grain yield and its related traits in red kidney beans. Journal of research and development76:80-88. (In Persian with English Abstract).##Sabokdast, M. and Kheyalparast, F. 2008.Study the relationship between the yields on the 30 cultivars of common bean (phaseoulus vulgaris L.).Journal of Science and technologyof Agricultural and Natural Resources, Soil and water Sciences11 (42):123-134. (In Persian with English Abstract).##Sabori, H., Rezaei, A.,Mirmohammady Maibody,S. A. M. and Esfahani,M. 2005. Path analysis for rice grain yield and related traits in two planting patterns. Journal of Science and Technology of Agricultureand Natural Resources9(1): 113-129. (In Persian with English Abstract).##Sarkar, M. M., Hassan, M. M.,Islam Rashid,M. M. and Seraj,S. 2014. Correlation and path coefficient analysis of some exotic early maturing rice (Oryzasativa L.) lines. Journal of Bioscience and Agriculture Research 1(1): 1-7.##Satheeshkumar, P. and Saravanan,K. 2012. Genetic variability, correlation and path analysis in rice (Oryzasativa L.). International Journal of Current Research 4(9): 82-85.##Sweta, R.N. and Singh,S.K. 2010. Character association and path analysis in rice (Oryzasativa L.) genotypes. World Journal of Agricultural Sciences 6(2): 201-206.##Yashitola, J., Thirumurugan, T.,Sundaram, R. M.,Naseerullah, M. K., Ramesha., M. S.,Sarma,N. P. and Sonti,R. V. 2002. Assessment of purity of rice hybrids using microsatellite and STS markers. Crop Science 42: 1369-1373.