Related Links
Assessment of Seed Yield Stability and Genotype × Environment Interaction of Faba Bean (Vicia faba L.) Promising Lines Using AMMI Analysis | ||
| نهال و بذر | ||
| Volume 37, Issue 1, April 2021, Pages 1-22 PDF (991.75 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/sppi.2021.124602 | ||
| Authors | ||
| F. Sheikh* 1; R. Sekhavat2; H. Asteraki3; A. Parkasi4 | ||
| 1Assistant Professor, Field and Horticultural Crops Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Gorgan, Iran. | ||
| 2Researcher, Field and Horticultural Crops Research Department, Safiabad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Dezful, Iran. | ||
| 3Researcher, Field and Horticultural Crops Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Borujerd, Iran. | ||
| 4Researcher, Field and Horticultural Crops Research Department, Baluchistan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization), Iranshahr, Iran. | ||
| Abstract | ||
| This study was carried to assess seed yield stability and genotype × environment interaction of 15 faba bean promising lines together with four control cultivars using randomized complete block design with three replications in four experimental field stations; Gorgan (rainfed), Dezful (irrigated), Borujerd (rainfed), Iranshahr (irrigated), in two cropping seasons (2015 -17). Combined analysis of variance showed that genotypes differed significantly for days to 50% flowering, plant height, number of pods per plant, number of seeds per pod, 100-seed weight and seed yield. FLIP03-069FB, ILB1266 × ILB1814 and WRB2-7 × Giza Blanca promising lines had the highest seed yield, respectively. Environment main effect accounted for 76.43% of total observed variation in seed yield, whereas genotype and genotype × environment interaction effect accounted for 6.31% and 17%, respectively. The multivariate analysis using additive main effects and multiplicative interaction (AMMI) showed that the six first principal components had significant effect in explaining genotype × environment interaction effect, and explained 99.69% of the total of observed variation. The AMMI stability value (ASV) discriminated WRB2-7 × Giza Blanca, ILB 3626, Barkat × BPL 465 promising lines and cv. Barkat with high seed yield stability, respectively. Barkat × New Mammoth promising line and cv. Zereshki had low seed yield stability, respectively. Also, Gorgan and Borujerd environments, due to their high interaction, were identified as the ideal environments for discriminating faba bean genotypes. In conclusion, WRB2-7 × Giza Blanca promising line with average seed yield of 3285 kg ha-1, high yield stability and wide adaptation was identified as the superior genotype for being released as new commercial faba bean cultivar for target regions. | ||
| Keywords | ||
| Faba bean; additive main effect and multiplicative interaction; AMMI stability value; seed yield and ideal environment | ||
| References | ||
|
Ammar, M. H., Alghamdi, S. S., Migdadi, H. M., Khan, H. M., El-Harty, E. H., and Al-Faifi, S. A. 2015. Assessment of genetic diversity among faba bean genotypes using agro-morphological and molecular markers. Saudi Journal of Biological Sciences 22: 340-350.
Asnakech, T., Julia Derera, S., and Asnake, F. 2017. Analysis of genotype environment interaction and stability for grain yield and chocolate spot (Botrytis fabae) disease resistance in faba bean (Vicia faba). Australian Journal of Crop Science 11: 1228-1238.
Bocianowskia, J., Lierschb, A., and Nowosad, K. 2020. Genotype by environment interaction for alkenyl glucosinolates content in winter oilseed rape (Brassica napus L.) using additive main effects and multiplicative interaction model. Current Plant Biology 21. https://doi.org/10.1016/j.cpb.2020.100137.
Brankovic-Radojcic, D., Babic, V., Girek, Z., Ţivanovic, T., Radojcic, A., Filipovic, M., and Srdic, J. 2018. Evaluation of maize grain yield and yield stability by AMMI analysis. Genetika 50: 1067-1080.
Ciric, M., Curcic, Z., Mirosavljevic, M., Marjanovic Jeromela, A., Jacimovic, G., Prodanovic, S., and Zivanovic, T. 2017. Assessment of sugar beet root yield by AMMI analysis. Genetika 49: 663 - 675.
FAO. 2017. FAOSTAT Database. Food and Agriculture Organization of the United Nations. Available at: www.fao.org/faostat/
Farshadfar, E., Mahmodi, N., and Yaghotipoor, A. 2011. AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Australian Journal of Crop Science 5 (13):1837-1844.
Fikere, M., Tadesse, T., Suso, M. J., and Legesse, T. 2008. Analysis of Multi-environment yield performance of faba bean (Vacia faba L.) genotypes using AMMI model. Journal of Genetic and Breeding 62: 25-30.
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): 2135-2145.
Flores, F., Moreno, M. T., Martinez, A., and Cubero, J. I. 1996. Genotype-environment interaction in faba bean: comparison of AMMI and principal coordinate models. Field Crops Research 47: 117-127.
Gauch, H. G. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Science 46: 1488-1500.
Kang, M. S., Prabhakaran, V. T., and Mehra, R. B. 2004. Genotype-by-environment interaction in crop improvement. pp. 535-572. In: Jain H. K. and Kharkwal M. C. (eds.). Plant breeding: Mendelian to molecular approaches. Springer Netherlands, Dordrecht.
Karkanis, A., Ntatsi, G., Lepse, L., Fernandez, J. A., Vagen, I. M., Rewald, B., Alsiņa, I., Kronberga, A., Balliu, A., Olle, M., Bodner, G., Dubova, L., Rosa, E., and Savvas, D. 2018. Faba bean cultivation – revealing novel managing practices for more sustainable and competitive European cropping systems. Frontier in Plant Science 9:1115. doi: 10.3389/fpls.2018.01115.
Katerj, N., Hoorn, J. W., Hamdy, A., Mastrorilli, M., and Oweis, T. 2009. Salt tolerance analysis of chickpea, faba bean and durum wheat varieties I. Chickpea and faba bean. Agriculture Water Management 72: 177-194.
Khomari, A., and Mohammadi, A. 2017. Stability study of yield in sunflower (Helianthus annuus L.) cultivars using AMMI method. Journal of Crop Breeding 9 (23):117-124 (in Persian).
Kooshki, M. H., Ghaedrahmati, M., Asadi, B., Kamel, M., Khorshidi Benam, M. B., and Dorri, H. R. 2016. Analysis of yield stability of some white bean (Phaseolus vulgaris L.) genotypes using AMMI method. Seed and Plant Improvement Journal 32-1: 557-573 (in Persian).
Liu, Z., Fan, X., Huang, W., Yang, J., Zheng, Y., Wang, Sh., and Qiu, L. 2017. Stability analysis of seven agronomic traits for soybean [(Glycine max (L.) Merr.] Tokachi nagaha and its derived cultivars using the AMMI model. Plant Production Science 20 (4): 499-506.
Maniruzzaman, M. Z., Islam, F., Begum, M. A. A., Khan, M., Amiruzzaman, B., and Hossain., A. 2019. Evaluation of yield stability of seven barley (Hordeum vulgare L.) genotypes in multiple environments using GGE biplot and AMMI model. Open Agriculture 4: 284-293.
Minitab, INC. 2005. Minitab user’s guide, vers. 14. Minitab Inc. Harrisburg, Pennsylvania, USA Moghaddam, M., Mohammadi, S. A., and Aghaee-Sarbarzeh, M. 1995. Introduction to multivariate statistical methods. 281 pp. (in Persian).
Mohammadi, M., Sharifi, P., and Karimizadeh, R. 2016. Stability analysis of seed yield of safflower genotypes (Carthamus tinctorius L.). Journal of Crop Breeding 7 (16): 104-114 (in Persian).
Nasir Mousavi, S. M., Hejazi, P., and Kanani Zadegan Khalkhali, S. 2016. Study on stability of grain yield sunflower cultivars by AMMI and GGE bi plot in Iran. Molecular Plant Breeding 7 (2): 1-6.
Pereira, H. S., Bueno, L. G., Peloso, M. J. D., Abreu, A. D. F. B., Moreira, J. A. A., Martins, M., Wendland, A., Faria, L. C. D., de Souza, T. L. P. O., and Melo, L.C. 2014. Agronomic performance and stability of Andean common bean lines with white grains in Brazil. Bragantia 73: 130-137.
Purchase, J., Hatting, H., and Van Deventer, C. 2000. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil 17: 101-107.
Rabiei, M., and Khodambashi, M. 2020. Assessment of yield stability in common bean cultivars based on univariate and multivariate methods. Journal of Crop Production and Processing 9 (4): 33-45 (in Persian).
Sabaghpour, S. H., Razavi, F., Danyali, S. F., Tobe, D., and Ebadi, A. 2012. Additive main effect and multiplicative interaction analysis for grain yield of chickpea (Cicer arietinum L.) in Iran. International Scholarly Research Network. DOI:10.5402/2012/639381.
Sadeghi, S. M., Samizadeh, H., Amiri, E., and Ashouri, M. 2011. Additive main effects and multiplicative interactions (AMMI) analysis of dry leaf yield in tobacco hybrids across environments. African Journal of Biotechnology 10 (21): 4358-4364.
Safavi, M., and Bahraminejad, S. 2017. The evaluation of genotype × environment interactions for grain yield of oat genotypes using AMMI model. Journal of Crop Breeding 9 (22): 125-132 (in Persian).
SAS. 2011. Base SAS 9.1 procedures guide. SAS Institute Inc, Cary.
Sharifi, P., Aminpanaha, H., Erfani, R., Mohaddesi, A., and Abbasian, A. 2018. Evaluation of genotype × environment interaction in rice based on AMMI model in Iran. Rice Science 24: 173-180.
Sheikh, F., and Feyzbakhsh, M. T. 2019. Faba bean: cultivation, crop husbandry and harvest. Nashr-e-Amoozesh-e-Keshavarzi. Agricultural Research, Education and Extension Organization, Iran. 94 pp. (in Persian).
Shiri, M. R., and Bahrampour, T. 2016. Genotype × environment interaction analysis using GGE biplot in grain maize (Zea mays L.) hybrids under different irrigation conditions. Cereal Research 5: 83-94.
Tadele, M. 2019. Breeding achievements of faba bean (Vicia faba L.) and its impact in the livelihood of Ethiopian farmers. International Journal of Agriculture and Biosciences 8 (5): 263-269.
Tadele, T., Amanuel, T., Behailu, M., and Gashaw, S. 2018. Evaluation of the effect of genotype, environment and genotype × environment interaction on white common bean varieties using additive main effect and multiplicative interaction (AMMI) analysis in the mid-altitude of Bale zone, Southeastern Ethiopia. African Journal of Agricultural Research 13 (7): 338-344.
Tadesse, T., Mulugeta, B., Sefera, G., and Tekalign, A. 2016. Genotypes by environment interaction of faba bean (Vicia faba L.). Grain yield in the highland of Bale zone, southeastern Ethiopia. Plant 5: 13-17.
Tekalign, A., Sibiya, J., Derera, J., and Fikre, A. 2017. Analysis of genotype × environment interaction and stability for grain yield and chocolate spot (Botrytis fabae) disease resistance in faba bean (Vicia faba L.). Australian Journal of Crop Science 11(10): 1228-1235.
Tekdal, S., and Kendal, E. 2018. AMMI Model to assess durum wheat genotypes in multi-environment trials. Journal of Agricultural Science and Technology 20: 153-166.
Temesgena, T., Kenenib, G., Seferaa, T., and Jarsob, M. 2015. Yield stability and relationships among stability parameters in faba bean (Vicia faba L.) genotypes. The Crop Journal 3: 258-268.
Tolessa, T. T. 2015. Application of AMMI and Tai’s stability statistics for yield stability analysis in faba bean (Vicia faba L.) cultivars grown in central highlands of Ethiopia. Journal of Plant Sciences 3 (4): 197-206.
Tolessa, T. T., Gemechu, K., Mohammed, H., and Ahmed, S. K. 2019. Decades of faba bean (Vicia faba L.) breeding for better grain yield and seed size has inadvertently reduced G × E interaction and increased inter-temporal performance stability. Journal of Crop Science and Biotechnology 22 (3): 265-274.
Vargas, M., Crossa, J., van Eeuwijk, F.A., Ramirez, M. E., and Sayre, K. 1999. Using partial least squares regression, factorial regression, and AMMI models for interpreting genotype × environment interaction. Crop Science 39: 955-967.
Yan, W., Hunt, L. A., Sheng, Q., and Szlavnics, Z. 2000. Cultivar evaluation and mega environment investigations based on the GGE biplot. Crop Science 40: 597-605.
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 Science 47: 643-655.
Zali, H., Sabaghpour, S., Farshadfar, E., Pezeshkpour, P., Safikhani, M., Sarparast, R., and Hashem Beygi, A. 2009. Stability analysis of chickpea genotypes using ASV parameter compare to other stability methods. Iranian Journal of Field Crop Science 40 (2): 21-29 (in Persian).
| ||
|
Statistics Article View: 337 PDF Download: 350 |
||
Journal management system. designed by sinaweb