تنوع صفات زراعی لاین‌های سویای حاصل از تلاقی ارقام کاربین و فورا
محورهای موضوعی : بوم شناسی گیاهان زراعی
محمد حسنوند
1
(گروه اصلاح نباتات، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران)
شهاب خاقانی
2
(دانشیار گروه اصلاح نباتات، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران)
مهدی چنگیزی
3
(استادیار گروه اصلاح نباتات، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران.)
مسعود گماریان
4
(استادیار گروه اصلاح نباتات، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران.)
عزت اله صداقت فر
5
(استادیار گروه گیاهپزشکی، واحد اراک، دانشگاه آزاد اسلامی، اراک، ایران.)
کلید واژه: تنوع ژنتیکی, مدلسازی, همبستگی ژنتیکی, همبستگی فنوتیپی,
چکیده مقاله :
به منظور بررسی تنوع ژنتیکی اینبرد لاین های سویا، مدل سازی عملکرد دانه و انتخاب ژنوتیپ های برتر، 80 لاین سویا حاصل از تلاقی ارقام کاربین در فورا به همراه رقم شاهد رقم L.17 در مزرعه تحقیقاتی سراب چنگایی خرم آباد در قالب طرح لاتیس 9 × 9 ارزیابی گردید. اختلاف معنی داری در صفات مورد مطالعه بین رقم شاهد و لاین های مورد بررسی مشاهده شد. بین عملکرد دانه و اکثر صفات مورد ارزیابی از جمله تعداد غلاف در بوته، درصد جوانه زنی، ارتفاع بوته، تعداد دانه در غلاف و تعداد دانه در بوته همبستگی مثبت و معنی داری وجود داشت. صفات ارتفاع بوته، تعداد غلاف در بوته، تعداد دانه در غلاف و وزن صد دانه 82% عملکرد را توجیه کردند. با استفاده از تجزیه به عامل ها، 17 صفت مورد مطالعه در قالب چهار مولفه حدود 62% از تغییرات کل را توجیه نمودند. صفات عملکرد دانه در کرت و عملکرد دانه در بوته که در عامل اول قرار داشتند، مهمترین صفات مورد ارزیابی بودند. بنابراین، صفات ارتفاع بوته، تعداد غلاف در بوته، تعداد دانه در غلاف، وزن صد دانه را می توان به عنوان معیارهایی برای گزینش لاین های برتر در جهت بهبود عملکرد دانه در سویا در نظر گرفت.
To study the genetic diversity of soybean inbred lines, grain yield modeling and selection of superior genotypes, 80 lines of soybean obtained from crosses of Karbin × Fora cultivars along with L.17 soybean cultivar as control were studied in research farm of Agriculture Khorram Abad Sarab Chenghaey in 9 ×9lattice design. Significant differences were observed between control and studied soybean lines. There was a positive and significant correlation between seed yield and most of the traits evaluated, including the number of pods per plant, percentage of germination, plant height, number of seeds per pod, and number of seeds per plant. Stepwise regression analysis showed that plant height, number of pods per plant, number of seeds per pod and 100-seed weight explained 82% of yield. Using factor analysis, 17 traits in four components explained about 62% of the total variation. Therefore, plant height trait, number of pods per plant, number of seeds per pod, 100-seed weight can be considered as criteria for selection of superior lines to improve grain yield in soybean.
1. Adeboye OB, Schultz B, Adekalu KO, Prasad KC (2019) Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rainfed soybeans (Glycine max L.) in Ile-Ife, Nigeria.
Agricultural Water Management 213: 1130-1146.
2. Agarwal DK, Billore SD, Sharma AN, Dupare BU, Srivastava SK (2013) Soybean: introduction, improvement, and utilization in India problems and prospects. Agricultural Research 2(4): 293-300.
3. Amaranath KCN, Viswanatha SR (1990) Path coefficient analysis for some quantitative characters in soybean. Mysore Journal of Agricultural Sciences 24(3): 312-315.
4. Babaei Zarch MJ, Fotokian MH, Mahmoodi S (2014) Evaluation of genetic diversity of wheat (Triticum aestivum L.) genotypes for morphological traits using multivarite analysis methods. Journal of Crop Breeding 6(14) :1-14. [in Persian with English abstract]
5. Chalish L, Houshmand S (2011) Estimate of heritability and relationship of some durum wheat characters using recombinant inbred lines. Journal of Crop Production 4(2): 223-238. [in Persian with English abstract]
6. Das ML, Rahman A, Miah AJ (1989) Correlation, path-coefficient and regression studies in soybean. Bangladesh Journal of Agricultural Research 14(1): 27-29.
7. Diaz C, Velaquz MO, Garcia O, Lopez MT, Garua JL (1987) Evaluation of soybeans in the dry seasons in Cuba. Ciencies de lar Agriculture 32: 159-161.
8. FAO (2009) Food Outlook - Global Market Analysis. Available on-line as <ww.fao.org/3/ai482e/ai482e00.htm> on 25 July 2009.
9. FAO (2019) Food Outlook - Biannual Report on Global Food Markets. Rome. Licence: CC BY-NC-SA 3.0 IGO. Available on-line as <http://www.fao.org/3/ca4526en/ca4526en.pdf> on 31 April 2019.
10. FAOSTAT (2017) Visualize Data of Crops. Available on-line as <http://www.fao.org/faostat/en/?#data/QC> on 05 March 2017.
11. Faraji A (2016) Evaluation of some soybean genotypes (Glycine max) under salt stress. Journal of Crop Breeding 8(18): 30–36. [in Persian with English abstract]
12. Ghanbari S, Nooshkam A, Fakheri BA, Mahdinezhad N (2018) Assessment of yield and yield component of soybean genotypes (Glycine max L.) in North of Khuzestan. Journal of Crop Science and Biotechnology 21(5): 435-441.
13. Mishra AK, Ali SA, Tiwari RC, Raghuwanshi RS (1994) Correlation and path analysis in segregating populations of soybean. International Journal of Tropical Agriculture 12(3-4): 278-281.
14. Pandey JP, Torrie JH (1973) Path Coefficient analysis of seed yield components in soybeans (Glycine max L.). Crop Science 13(5): 505-507.
15. Rahimi MH, Houshmand S, Khodambashi M, Shiran B, Mohammadi S (2017) Evaluation of recombinant pure lines of lentil under drought stress. Journal of Crop Breeding 9(22): 82–97. [in Persian with English abstract]
16. Rajput MA, Sarwan G, Tahir KH (1986) Path coefficient analysis development and yield components in soybean. Soybean Genetics Newsletter 13(1): 87-91.
17. Sengupta K, Sen S (1972) Path-coefficient analysis of some characters influencing seed yield of soybeans (Glycine max.L.). Indian Agriculturist 16: 149-154.
18. Soukhtehsaraei M, Dadashi MR, Soltani A (2018) Investigation of the role of pod abnormality incidence on yield and yield components of soybean (a case study in Golestan Province, Iran). Applied Ecology and Environmental Research 16(6): 7759-7775.
19. Sulistyo A, Sari KP (2018) Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean. Proceedings of the International Symposium on Food and Agro-biodiversity, Semarang, Indonesia.
20. Tousi MM, Ghanadha MR, Khodarahmi M, Shahabi S (2005) Factor analysis for grain yield and other attributes in bread wheat. Pajouhesh Va Sazandegi 18(67): 9-16. [in Persian with English abstract]
21. Van Eeuwijk FA, Bustos-Korts D, Millet EJ, Boer MP, Kruijer W, Thompson A, Muller O (2019) Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. Plant Science 282: 23-39.
1. Adeboye OB, Schultz B, Adekalu KO, Prasad KC (2019) Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rainfed soybeans (Glycine max L.) in Ile-Ife, Nigeria.
Agricultural Water Management 213: 1130-1146.
2. Agarwal DK, Billore SD, Sharma AN, Dupare BU, Srivastava SK (2013) Soybean: introduction, improvement, and utilization in India problems and prospects. Agricultural Research 2(4): 293-300.
3. Amaranath KCN, Viswanatha SR (1990) Path coefficient analysis for some quantitative characters in soybean. Mysore Journal of Agricultural Sciences 24(3): 312-315.
4. Babaei Zarch MJ, Fotokian MH, Mahmoodi S (2014) Evaluation of genetic diversity of wheat (Triticum aestivum L.) genotypes for morphological traits using multivarite analysis methods. Journal of Crop Breeding 6(14) :1-14. [in Persian with English abstract]
5. Chalish L, Houshmand S (2011) Estimate of heritability and relationship of some durum wheat characters using recombinant inbred lines. Journal of Crop Production 4(2): 223-238. [in Persian with English abstract]
6. Das ML, Rahman A, Miah AJ (1989) Correlation, path-coefficient and regression studies in soybean. Bangladesh Journal of Agricultural Research 14(1): 27-29.
7. Diaz C, Velaquz MO, Garcia O, Lopez MT, Garua JL (1987) Evaluation of soybeans in the dry seasons in Cuba. Ciencies de lar Agriculture 32: 159-161.
8. FAO (2009) Food Outlook - Global Market Analysis. Available on-line as <ww.fao.org/3/ai482e/ai482e00.htm> on 25 July 2009.
9. FAO (2019) Food Outlook - Biannual Report on Global Food Markets. Rome. Licence: CC BY-NC-SA 3.0 IGO. Available on-line as <http://www.fao.org/3/ca4526en/ca4526en.pdf> on 31 April 2019.
10. FAOSTAT (2017) Visualize Data of Crops. Available on-line as <http://www.fao.org/faostat/en/?#data/QC> on 05 March 2017.
11. Faraji A (2016) Evaluation of some soybean genotypes (Glycine max) under salt stress. Journal of Crop Breeding 8(18): 30–36. [in Persian with English abstract]
12. Ghanbari S, Nooshkam A, Fakheri BA, Mahdinezhad N (2018) Assessment of yield and yield component of soybean genotypes (Glycine max L.) in North of Khuzestan. Journal of Crop Science and Biotechnology 21(5): 435-441.
13. Mishra AK, Ali SA, Tiwari RC, Raghuwanshi RS (1994) Correlation and path analysis in segregating populations of soybean. International Journal of Tropical Agriculture 12(3-4): 278-281.
14. Pandey JP, Torrie JH (1973) Path Coefficient analysis of seed yield components in soybeans (Glycine max L.). Crop Science 13(5): 505-507.
15. Rahimi MH, Houshmand S, Khodambashi M, Shiran B, Mohammadi S (2017) Evaluation of recombinant pure lines of lentil under drought stress. Journal of Crop Breeding 9(22): 82–97. [in Persian with English abstract]
16. Rajput MA, Sarwan G, Tahir KH (1986) Path coefficient analysis development and yield components in soybean. Soybean Genetics Newsletter 13(1): 87-91.
17. Sengupta K, Sen S (1972) Path-coefficient analysis of some characters influencing seed yield of soybeans (Glycine max.L.). Indian Agriculturist 16: 149-154.
18. Soukhtehsaraei M, Dadashi MR, Soltani A (2018) Investigation of the role of pod abnormality incidence on yield and yield components of soybean (a case study in Golestan Province, Iran). Applied Ecology and Environmental Research 16(6): 7759-7775.
19. Sulistyo A, Sari KP (2018) Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean. Proceedings of the International Symposium on Food and Agro-biodiversity, Semarang, Indonesia.
20. Tousi MM, Ghanadha MR, Khodarahmi M, Shahabi S (2005) Factor analysis for grain yield and other attributes in bread wheat. Pajouhesh Va Sazandegi 18(67): 9-16. [in Persian with English abstract]
21. Van Eeuwijk FA, Bustos-Korts D, Millet EJ, Boer MP, Kruijer W, Thompson A, Muller O (2019) Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding. Plant Science 282: 23-39.