| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شماره‌ها | 3,262 |
| تعداد مقالات | 36,058 |
| تعداد مشاهده مقاله | 55,184,399 |
| تعداد دریافت فایل اصل مقاله | 94,183,860 |
تجزیه و تحلیل گرافیکی پایداری عملکرد دانه ژنوتیپ‌های کم تانن باقلا (.Vicia faba L) با استفاده از روش GGE بای‌پلات | ||
| نهال و بذر | ||
| دوره 40، شماره 2، تیر 1403، صفحه 293-271 اصل مقاله (694.29 K) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/spj.2025.368726.1409 | ||
| نویسندگان | ||
| فاطمه شیخ* 1؛ خالد میری2؛ رضا سخاوت3؛ حسین آسترکی4؛ محمدتقی فیض بخش1 | ||
| 1دانشیار، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان گلستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، گرگان، ایران. | ||
| 2استادیار، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی بلوچستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایرانشهر، ایران. | ||
| 3مربی، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی صفی آباد دزفول، سازمان تحقیقات، آموزش و ترویج کشاورزی، دزفول، ایران. | ||
| 4پژوهشگر، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، بروجرد، ایران. | ||
| چکیده | ||
| باقلا (.Vicia faba L) یکی از حبوبات چند منظوره با دامنه سازگاری وسیع، ارزش غذایی بالا و با داشتن قابلیت تثبیت بیولوژیک نیتروژن در تناوب زراعی به پایداری تولید و نظام‌های زراعی کمک می‌کند. یکی از مهمترین صفات تعیین کننده کیفیت در ارقام باقلا محتوای تانن دانه می‌باشد. به منظور مطالعه اثر متقابل ژنوتیپ × محیط و انتخاب ژنوتیپ‌های برتر باقلا بر اساس عملکرد دانه و پایداری آن و رابطه صفات زراعی مطلوب با عملکرد دانه، 12 ژنوتیپ کمتانن باقلا درقالب طرح بلوک های کامل تصادفی با سه تکرار در چهار ایستگاه تحقیقاتی، گرگان، دزفول، بروجرد و ایرانشهر، در دو سال زراعی (01-1400 و 02-1401) ارزیابی شدند. تجزیه واریانس مرکب داده‌ها نشان داد که اثر ساده، برهمکنش دوگانه و سه گانه ژنوتیپ × سال × مکان بر عملکرد دانه باقلا در سطح احتمال یک درصد معنی‌دار بود. بر اساس روش GGE-Biplot، دو مولفه اول در مجموع 60/9درصد (مولفه اول 34/5درصد و مولفه دوم 26/4درصد) از تغییرات برهمکنش ژنوتیپ × محیط عملکرد دانه را توجیه کردند. بر اساس نمودار چند ضلعی، در گرگان و بروجرد، ژنوتیپ‌های G6 Leofrontu×WRB 1-5)) و G4 (Icarus×WRB 1-5) و در ایرانشهر ژنوتیپ G11 (FLIP03-34FB×WRB 1-5) و در دزفول ژنوتیپ هایG3 (12TER-099-S2008, 034-3) وG10 (ILB 1270 × WRB 1-4) سازگار بودند. محیط آزمایشی دزفول از قدرت تمایز خوبی برخوردار بود و بهعنوان مکان مناسب جهت گزینش ژنوتیپ‌های برتر شناخته شد. تجزیه و تحلیل گرافیکی ژنوتیپ × صفت رابطه مثبت بین عملکرد دانه با ارتفاع گیاه، تعداد غلاف در گیاه، تعداد دانه در غلاف، وزن صد دانه و طول غلاف را نشان داد. از این‌رو، این صفات را می‌توان بهعنوان معیار گزینش در فرآیند انتخاب با هدف اصلاح ژنوتیپ‌های باقلا با عملکرد دانه بالا در نظر گرفت. ژنوتیپ‌هایG3 (12TER-099-S2008, 034-3)، (Icarus×WRB 1-5) G4،G6 Leofrontu×WRB 1-5)) و G10 (ILB 1270 × WRB 1-4) با دارا بودن عملکرد دانه بالاتر و پایداری آن برای بررسی‌های بیشتر و آزادسازی رقم جدید برای مناطق هدف انتخاب شدند. | ||
| کلیدواژه‌ها | ||
| باقلا؛ برهمکنش ژنوتیپ × صفت؛ برهمکنش ژنوتیپ × محیط؛ ژنوتیپ ایده‌ال؛ عملکرد دانه | ||
| عنوان مقاله [English] | ||
| Graphical Analysis of Seed Yield Stability of Low Tannin Faba Bean (Vicia faba L.) Genotypes Using GGE Biplot Method | ||
| نویسندگان [English] | ||
| F. Sheikh1؛ Kh. Miri2؛ R. Sekhavat3؛ H. Asteraki4؛ M. T. Feyzbakhsh1 | ||
| 1Associate Professor, Field and Horticultural Crops Science Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Gorgan, Iran. | ||
| 2Assistant Professor, Field and Horticultural Crops Science Research Department, Baluchestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Iranshahr, Iran. | ||
| 3Researcher, Field and Horticultural Crops Science Research Department, Safiabad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Dezful, Iran. | ||
| 4Researcher, Field and Horticultural Crops Science Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Broujerd, Iran. | ||
| چکیده [English] | ||
| Faba bean (Vicia faba L.) is an important nitrogen-fixing crop with significant benefits for soil health, sustainability, and crop rotation. One of the most important quality-determining traits in faba bean cultivars is their tannin content. To study the magnitude of G × E interaction, to identify faba bean genotypes with high seed yield with yield stability, and wide adaption to specific to target environment(s), 12 low tannin faba bean genotypes were evaluated using randomized complete bloch design wqith three replications at four agricultural research field stations, Gorgan, Dezful, Broujerd and Iranshahr, in two cropping seasons (2021-22 and 2022-23). Faba bean genotypes were evaluated using multiple traits and genotype × trait interactions. Combined analysis of variance revealed that simple, double, and triple interaction effects of genotype× year× location was significant (p≤ 0.01) on seed yield. GGE biplot analysis showed that the PC1 (26.4%) and PC2 (34.5%) explained 60.9% of the total variation for seed yield. Adapted faba bean genotypes were determined for each mega-environment. Furthermore, Dezful environment demonstrated excellent differentiation ability. Results of the GGE biplot and genotype × trait (GT) biplot indicated that G3 (12TER-099-S2008,034-3), G4 (Icarus × WRB1-5), G6 (Leofrontu × WRB1-5) and G10 (ILB1270 × WRB1-4) genotypes with high seed yield and yield stability can be considered for being released as new cultivar release for target environments. Keywords: Faba bean, genotype ×environment interaction, genotype × trait interaction, ideal genotype, seed yield. Introduction Faba bean (Vicia faba L.) is an important nitrogen-fixing crop with significant benefits for crop rotation. However, their market value depends on their tannin content (Sheikh et al., 2023). The presence of low-tannin or zero-tannin genotypes in the faba bean gene pool has provided suitable conditions for the introduction of low-tannin cultivars in Iran. Faba bean as a cost-effective protein source can be considered as a substitute for soybean (a rich source of amino acids) and corn (a major energy supplier) in feeding livestock and poultry (Angell et al., 2016). One of the major limitations of traditional faba bean varieties for feeding poultry is high tannin content. Considering the importance of using faba bean in poultry diet and diverse climatic conditions of Iran, relying on one or two limited cultivars would not be sufficient. The aim of this study was to compare different low tannin faba bean genotypes for several traits and analyze the correlation between their different traits as well as to select the superior genotypes based on the combination of agronomic traits and seed yield using biplot GGE and GT biplot methods. The GGE In recent years, biplot analysis has evolved into an important technique in crop improvement and agricultural research (Rezene et al., 2019). Materials and Methods To understand the magnitude genotype × environment interactions and to compare genotypes performance over growing seasons and locations, 12 low tannin genotypes To study the magnitude of G × E interactions, and to identify faba bean genotypes with high seed yield with yield stability, wide and specific adaptibilty to target environment(s), 12 low tannin faba bean genotypes were evaluated using randomized complete bloch design with three replications at four agricultural research field stations, Gorgan, Dezful, Broujerd and Iranshahr, in two cropping seasons (2021-22 and 2022-23). Faba bean genotypes were evaluated using multiple traits and genotype × trait (GT) interactions. Plant height, pod no. plant-1, seed no. pod-1, pod no. plant-1, 100 seed weight (100SW), and seed yield were measured. Combined analysis of variance was performed were analyzed using SAS software. The Duncan’s multiple range test, at the 5% probability level, was used for mean comparison. GGE-biplot was employed to analyze G × E interaction (GE) and assessment of yield stability of faba bean genotypes. The GT biplot method was used to show the genotype × trait interactions. All biplots presented in this study were generated using the GGE biplot software package. Results and Discussion Combined analysis of variance indicated significant (p≤ 0.01) differences among genotypes for all traits. The analysis also demonstrated that the test environments, genotype, and GE interaction significantly contributed by 49.4%, 22.6%, and 22.7% of the total variation of seed yield, respectively. When the expression of the genetic potential of the genotype is influenced by the environmental factors, screening of genotypes with high yield and higher yield stability is a very important breeding strategy (Sheikh et al., 203). The yield stability was assessed using the GGE biplot method across two growing season and four locations (eight environments). The determination of seed yield stability of genotypes enables breeders for cultivar selection and recommendations despite the variable environmental conditions (Yan et al., 2007). GGE biplot analysis revealed that the PC1 and PC2 explained 60.9% of the total variation of seed yield. Based on polygon view of biplot adapted genotypes were determined for each mega-environment (Rezene et al., 2019). In Gorgan and Broujerd, G6 (Leofrontu × WRB 1-5) and G4 (Icarus × WRB 1-5) genotypes were adapted. The GT biplot showed that PC1 (52.2%) and PC2 (22%) explained 74.2% of total variation of the standardized data. The biplot vector view indicated that there was a strong positive correlation between seed yield and plant height, pods no. plant-1, seed no. pod-1, and 100 seed weight. Therefore, these traits can be used as selection criteria for improving of seed yield in faba bean breeding programs. Results of the GGE biplot and genotype × trait (GT) biplot indicated that G3 (12TER-099-S2008,034-3), G4 (Icarus × WRB1-5), G6 (Leofrontu × WRB1-5) and G10 (ILB1270 × WRB1-4) genotypes with high seed yield and yield stability can be considered for being released as new cultivar for target environments. References Angell, A.R., Angell, S.F., de Nys, R. and Paul, N. 2016. Seaweed as a protein source for mono-gastric livestock. Trends food science technology, 54, pp.74–84. DOI: 10.1016/j.tifs.2016.05.014l Rezene, Y. 2019. GGE-Biplot analysis of multi-environment yield trials of common bean (Phaseolus vulgaris L.) in the southern Ethiopia. Journal of Plant Studies, 8(1), pp.35-44. DOI: 10.5539/jps.v8n1p35 Sheikh, F., Miri, K., Sekhavat, R. and Asteraki, H. 2023. Graphical analysis of grain yield stability for selection of superior faba bean (Vicia faba L.) genotypes. Iranian Journal of Field Crop Science, 54(3), pp.41-52 (in Persian). DOI: 10.22059/ijfcs.2023.353171.654968 Yan, W., Kang, M.S., Ma, B., Woods, S. and Cornelius, P.L. 2007. GGE biplot vs. AMMI analysis of genotype-by environment data. Crop Scicence, 47(4), pp.643-655. DOI: org/10.2135/cropsci2006 | ||
| کلیدواژه‌ها [English] | ||
| : Faba bean, genotype ×environment interaction, genotype × trait interaction, ideal genotype, seed yield | ||
| مراجع | ||
|
Akinyosoye, S.T., Agbeleye, O.A., Adetumbi, J.A., Ukachukwu, P.C. and Amusa, O.D. 2023. Genotype–genotype× environment (GGE) biplot analysis of winged bean for grain yield. Acta Horticulturae et Regiotecturae, 26, pp.53-63. DOI: 10.2478/ahr-2023-0009
Angell, A.R., Angell, S.F., de Nys, R. and Paul, N. 2016. Seaweed as a protein source for mono-gastric livestock. Trends food science technology, 54, pp.74–84. DOI: 10.1016/j.tifs.2016.05.014l
Bangar, S.P. and Kajla, P. 2022. Introduction: global status and production of faba bean. Pp. 1-15. In: Bangar, S. P. and Dhull, S. B. (eds) Faba Bean: Chemistry, Properties and Functionality. Springer, Cham. DOI: 10.1007/978-3-031-14587-2_1 Barilli, E., Luna, P., Flores, F. and Rubiales, D. 2025. Agronomic performance of faba bean in Mediterranean environments. Agronomy, 15, 412. DOI: 10.3390/ agronomy15020412
Firew, A.M., Amsalu, B. and Tsegaye, D. 2019. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype by environment interaction (GGE) biplot analysis of large white bean (Phaseolus vulgaris L.) genotypes across environments in Ethiopia. African Journal of Agricultural Research, 14(35), pp.2135-2145. DOI: 10.5897/Ajar2019.14180
Flores, F., Hybl, M, Knudsen, J.C., Marget, P., Muel, F., Nadal, S., Narits, L., Raffiot, B., Sass, O., Solis, I., Winkler, J., Stoddard, F.L. and Rubiales, D. 2013. Adaptation of spring faba bean types across European climates. Field Crops Research, 145(3), pp.1-9. DOI: 10.1016/j.fcr.2013.01.022
Ghaffar, M., Asghar, M.J. and Shahid, M. 2023. Estimation of G × E interaction of lentil genotypes for yield using AMMI and GGE biplot in Pakistan. Journal of Soil Science and Plant Nutrition, 23(1), pp.2316–2330. DOI: 10.1007/s42729-023-01182-x
Greveniotis, V., Bouloumpasi, E., Zotis, S., Korkovelos, A., Kantas, D. and Ipsilandis, C.G. 2023. Genotype-by-environment interaction analysis for quantity and quality traits in faba beans using AMMI, GGE models, and stability indices. Plants, 12(2), pp.3769. DOI: 10.3390/plants12213769
Hirpa, L., Nigussie, D., Setegn, G., Geremew, B. and Firew, M. 2013. Multivariate analysis as a tool for indirect selection of common bean genotypes (Phaseolus vulgaris L) for soil acidity tolerance under field conditions. Science Technology and Arts Research Journal, 2(3), pp.7-15. DOI: 10.2298/GENSR1202279G
Khan, M.M.H., Rafii, M.Y., Ramlee, S.I., Jusoh, M. and Mamun, A.M. 2021. AMMI and GGE biplot analysis for yield performance and stability assessment of selected Bambara groundnut (Vigna subterranean L. Verdc.) genotypes under the multi-environmental trials (METs). Scientific Reports, 11(3), pp.22791. DOI: 10.1038/s41598-021-01411-2
Koc, S., Orak, A., Tenikecier, H.S. and Saglam, N. 2018. Relationship between seed yield and yield characteristics in faba bean (Vicia faba L.) by GGE-biplot analysis. Journal of Life Sciences, 12(1), pp.105-110. DOI: 10.17265/1934-7391/2018.02.005
Mayer Labba, I.C., Frøkiær, H. and Sandberg, A.S. 2021. Nutritional and antinutritional composition of fava bean (Vicia faba L., var. minor) cultivars. Food Research International, 140(2), pp.11-38. DOI: 10.1016/j.foodres.2020.110038
Oliveira, T.R., Gravina, G.A., Ferreira de Oliveira, G.H., Cordeiro Araújo, K., Cordeiro de Araujo, L., Figueiredo Daher, R. and Vivas, M. 2018. The GT biplot analysis of green bean traits. Ciencia Rural, Santa Maria, 48(6), e20170757. DOI: 10.1590/0103-8478cr20170757
Oluyinka, O., Robin, A., Walker, L. and Houdijk, J.G. 2019. Evaluation of the nutritive value of legume alternatives to soybean meal for broiler chickens. Poultry Sciences, 98(1), pp.5778-5788. DOI: 10.3382/ps/pez374
Rezene, Y. 2019. GGE-Biplot analysis of multi-environment yield trials of common bean (Phaseolus vulgaris L.) in the southern Ethiopia. Journal of Plant Studies, 8(1), pp.35-44. DOI: 10.5539/jps.v8n1p35
Sabaghnia, N., Dehghani, H. and Sabaghpour, S.H. 2008. Graphic analysis of genotype by environment interaction for lentil yield in Iran. Agronomy Journal, 100(2), pp.760-764 (in Persian). DOI: 10.2134/agronj2006.0282
Sheikh, F., Miri, K., Sekhavat, R. and Asteraki, H. 2023. Graphical analysis of grain yield stability for selection of superior faba bean (Vicia faba L.) genotypes. Iranian Journal of Field Crop Science, 54(3), pp.41-52 (in Persian). DOI: 10.22059/ijfcs.2023.353171.654968
Sheikh, F., Nazari, H. and Fanaei, H. 2022a. Graphic analysis of trait relations and stability of faba bean genotypes using the biplot method. Journal of Crop Production, 15(2), pp. 117-135 (in Persian). DOI: 10.22069/ejcp.2022.19563.2457
Sheikh, F., Sekhavat, R., Asteraki, H., Parkasi, A. and Aghajani, M.A. 2021. Evaluation of seed yield stability of faba bean (Vicia faba L.) genotypes using GGE biplot analysis. Journal of Crop Production and Processing, 11(3), pp.85-99 (in Persian). DOI: 10.47176/jcpp.11.3.36412
Sheikh, F., Sekhavat. R. and Aghajani, M. 2022b. Evaluation of resistance to leaf spot diseases and yield characteristics in faba bean genotypes through cluster analysis and genotype by trait biplot. Journal of Crop Breeding, 14(44), pp.131-147 (in Persian). DOI: 10.52547/jcb.14.44.131
Skylas, D.J., Paull, J.G., Hughes, D.G.D., Gogel, B., Long, H., Williams, B., Mundree, S., Blanchard, C.L. and Quail, K.J. 2019. Nutritional and anti-nutritional seed-quality traits of faba bean (Vicia faba) grown in South Australia. Crop Pasture Sciences, 70(2), pp.463–472. DOI: 10.1071/CP19017
Tadele, M., Mohammed, W. and Jarso, M. 2020. Yield stability and genotype × environment interaction of faba bean (Vicia faba L.). International Journal of Plant Breeding and Crop Science, 7(2), pp.833-846. DOI: 10.1002/agj2.21268
Temesgen, T., Keneni, G., Sefera, T. and Jarso, M. 2015. Yield stability and relationships among stability parameters in faba bean (Vicia faba L.) genotypes. The Crop Journal, 3(3), pp.258-268. DOI: 10.1016/j.cj.2015.03.004
Tolessa, T., Gemechu, K., Tadesse, G., Jarso, M. and Bekele, Y. 2013. Genotype × environment interaction and performance stability for grain yield in field pea (Pisum sativum L.) genotypes. International Journal of Plant Breeding, 7(1), pp.116-123. DOI: 10.1002/agj2.21268
Wondaferew, D., Mullualem, D., Bitewlgn, W., Kassa, Z., Abebaw, Y., Ali, H., Kebede, K. and Astatkie, T. 2024. Cultivating sustainable futures: multi-environment evaluation and seed yield stability of faba bean (Vicia faba L.) genotypes by using different stability parameters in Ethiopia. BMC Plant Biology, 24(1), pp.1108-1121. DOI: 10.1186/s12870-024-05829-4
Yan, W. and Fregeau-Reid, J. 2008. Breeding line selection based on multiple traits. Crop Science, 48(3), pp.417-423. DOI: 10.2135/cropsci2007.05.0254
Yan, W. and Kang, M.S. 2003. GGE biplot analysis: a graphical tool for breeders, geneticists and agronomists, CRC Press LLC., Boca Raton, Florida, USA. 286 pp.
Yan, W. and Rajcan, I. 2002. Biplot analysis of test sites and trait relations of soybean in Ontario. Crop Science, 42(1), pp.11-20. DOI: 10.2135/cropsci2002.1100
Yan, W., Kang, M.S., Ma, B., Woods, S. and Cornelius, P.L. 2007. GGE biplot vs. AMMI analysis of genotype-by environment data. Crop Scicence, 47(4), pp.643-655. DOI: 10.2135/cropsci2006
| ||
|
آمار تعداد مشاهده مقاله: 379 تعداد دریافت فایل اصل مقاله: 213 |
||