عنوان مقاله [English]
Background and objectives. Given the shortcomings regarding lentil cultivars compatible with temperate and semi-temperate rainfed regions of the country, identifying genotypes with potential to be introduced as cultivars is very important. Due to genotype × environment interaction, selection of genotypes with wide adaptation to different environments is difficult. In addition to high yield, these genotypes must have yield stability in different regions, in other words, general stability. In GGE model (G+GE), the selection of stable genotypes is based on both genotype (G) and genotype × environment (GE) interaction effects.
Materials and methods. in order to evaluate yield stability of rain-fed lentil genotypes, the present study was conducted based on randomized complete block design with three replications with 14 advanced genotypes along with two local cultivars including G15 and G16 (Gachsaran and Sepehr respectively) over two years (since 2018). The experiment’s locations were Gachsaran, Khormeh Abad, Ilam and Moghan. After collecting data from eight environments, the genotype × environment interaction for grain yield was evaluated by using GGE biplot method.
Results. Principal component analysis in the GGE biplot model showed that 47.1% of the variations caused by G and GE is justified by the first two components (PC1, PC2). The mosaic plot revealed that the contribution of diversity due to genotype × environment interaction was significantly higher than the diversity caused by genotype (G) alone. Using GGE biplot model and based on representativeness and discriminating ability, Gachsaran region was identified as a desirable environment to identify variation among genotypes. G11 was the closest genotype to the ideal genotype in terms of grain yield. This genotype had the highest yield among genotypes and was in a moderate position in terms of stability. Genotype 9 was in the second place in terms of yield but had high yield stability since was the closest genotype to the ideal genotype in terms of stability. Genotypes 10 and 1 were also in the next ranks considering both yield and stability. These four genotypes had considerable advantage in terms of both average yield and yield stability compated to control cultivars (G15 and G16). In addition, G5 showed the least yield stability among all genotypes. G15 and G16 as local cultivars showed relatively low grain yield and stability compared to the most of advanced genotypes.
Conclusion. G9, G11, G10, G1 were considered as genotypes with potential to be introduced as new cultivar(s) following further experiments in private farm lands.
1.Gurmu, F., Lire, E.A., Asfaw, A., Alemayehu, F., Rezene, Y. and Ambachew, D. 2012. GGE- biplot analysis of grain yield of faba bean genotypes in Southern Ethiopia. Electron J. Plant Breed. 3: 3. 898-907.
2.Moreno-Gonzalez, J., Crossa J. and Cornelius, P.L. 2004. Genotype × environment interaction in multi-environment trials using shrinkage factors for AMMI models. Euphytica. 137: 119-127.
5.Yan, W., Cornelius.,P.L., Crossa. J. and Hunt, L.A. 2001. Two types of GGE biplots for analyzing multi environment trial data. Crop Sci. 41: 656-663.
6.Yan, W., Fregeau-Reid, J.A., Pageau, D.R.A., Mitchell Fetch, J.W., Etienne, M., Rowsell, J., Scott, P., Price, M., De Haan., B., Cummiskey., A., Lajeunesse, J., Durand, J. and Sparry, E. 2010. Identifying essential test locations for oat breeding in eastern Canada. Crop Sci. 50: 504-515.
8.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 Sci. 47: 643-655.
9.Sabaghnia, N., Dehghani, H. and Sabaghpour, S.H. 2008. Graphic analysis of genotype and environment interaction for lentil (Lens culinaris Medik) yield in Iran. Agron J. 100: 760-764. (In Persian)
10.Laffont, J.L., Hanafi. M. and Wright. K. 2007. Numerical and graphical measures to facilitate the interpretation of GGE biplots. Crop Sci. 47: 990-996.
11.Barati, A., Lakzadeh, I., Jabbari, M., Poodineh, O., Jafarbby, J., Shahbazihomonlo, K., Gholipour, A. and Tabatabaei Fard, N.A. 2020. Evaluation of grain yield stability of irrigated barley (Hordeum vulgare L.) promising lines in warm regions of Iran using GGE biplot analysis. Ir. J. Crop Sci. 22: 212-224. (In Persian)
12.Pourdad, S. and Jamshidi Moghaddam, M. 2013. Study on genotype and environment interaction through GGE biplot for seed yield in spring rapeseed (Brassica napus L.) in rain-Fed condition. J. Crop Breed. 5: 12. 12-23.
13.Donoso-Ñanculao, G., Paredes, M., Becerra, V., Arrepol, C. and Balzarini, C. 2018. GGE- Biplot analysis of multienvironment yield trials of rice produced in a temperate climate. Chil J Agric Res. 76: 2. 152-157
14.Mohammadi, R., Armion, M., Zadhassan, E. and Eskandari, M. 2014. Analysis of genotype and environment interaction for grain yield in rain-fed durum wheat. J. Dryland Agric Ir. 1: 4. 23-32. (In Persian)
15.Mohammadi, M., Karimizadeh, R., Hosseinpour, T., Ghojogh, H., Shahbazi, K. and Sharifi, P. 2018. Use of parametric and non-parametric methods for genotype ×environment interaction analysis in bread wheat genotypes. Plant Genet Res. 4: 2. 75-88.
16.Yan, W. and Tinker, N.A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can J. Plant Sci. 86: 623-645.
17.Farayedi, Y., Asadi, A., Ahakpaz, F., Saeed, F., Kanoni. H. and Ehsan nosrati, A. 2020. Evaluation of genotype-environment interaction for grain yield of chickpea genotypes (Cicer arietinum L.) in cold agro-climate zone of Iran by GGE biplot method. J Crop Breed. 12 : 36. 66-76. (In Persian)
18.Farshadfar, E. 2013. Simultaneous selection of yield and yield stability in chickpea genotypes using the GGEBiplot technique. Acta Biol Hung. 61: 185-194.
19.Mohamed, N.E. and Ahmed. A.A. 2013. Additive main effects and multiplicative interaction (AMMI) and GGE-biplot analysis of genotype × environment interaction for grain yield in bread wheat (Triticum aestivum). Afr J. Agric Res. 8: 5197-5203.
20.Blanche, S.B. and Myers, G.O. 2006. Identifying discriminating locations for cultivar selection in Louisiana. Crop Sci. 46: 946-949.
21.Yan, W., Hunt, L.A., Sheng, Q. and Szlavnics, Z. 2000. Cultivar evaluation and mega environment investigations based on the GGE- biplot. Crop Sci. 40: 597-605.
22.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. J Crop Prod Process (JCPP). 11: 3. 85-99. (In Persian)
23.Amira, J.O., Ojo, D.K., Ariyo, O.J., Oduwaye, O.A. and Ayo-Vaughan, M.A. 2013. Relative discriminating powers of GGE and AMMI models in the selection of tropical soybean genotypes. Afr Crop Sci. J. 21: 1- 67-73.
24.Bhartiya, A., Aditya, J.P., Singh, K., Purwar, J.P. and Agarwal. A. 2017. AMMI & GGE biplot analysis of multi environment yield trial of soybean in North Western Himalayan state Uttarahand of India. Legume Res. 40: 2. 306-312.