نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرم‌آباد، ایران،
2 کارشناس‌ارشد، مدیریت جهاد کشاورزی کوهدشت، کوهدشت، ایران
3 کارشناس‌ارشد، مدیریت جهاد کشاورزی خرم آباد، خرم‌آباد، ایران
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
Background and objectives:
Chickpea is one of the most important legumes in Iran and accounts for almost 84% of dietary legumes. Chickpea seed yield is strongly influenced by environments, and breeders often determine the stability of high-yielding genotypes across different environments before being introduced as a cultivar. Accurate study of the nature of genotype × environment allows breeders to identify stable and compatible genotypes and has always been one of the important issues in the production and release of new stable and high-yielding cultivars in breeding programs. . Adaptation of chickpea genotypes to environmental conditions is important for crop production stability in different years and places. Existence of the interaction of genotype and environment affects the value of genotypes in different places. The present study was conducted to investigate the effect of genotype by environment interaction on grain yield of chickpea genotypes and cultivars in four environments and to identify stable and high-yielding genotypes under rainfed conditions as autumn planting.
Materials and Methods:
In this study, twelve cultivars and advanced genotype of chickpea were planted during two cropping years (2016-2018) in a randomized complete block design with three replications in semi-warm (Kuhdasht) and temperate (Khorramabad) areas of Lorestan province. Various nonparametric methods such as non-parametric statistics of Si (1), Si (2), Si (3) and Si (6), Thennarasus statistics of NPi (1), NPi (2), NPi (3) and NPi (4), mean rank stability statistics (R), stability statistics of Ketata et al (σr, σmy), Kang stability statistics (Ysi), Fox stability statistics (TOP, MID and LOW) and Genotype Stability Index (GSI) were used for estimating the stability of genotypes. the principal component analysis method was used to better understand the relationships between different statistics..
Results
The results of combined analysis of variance showed that the main effects of environment (including location, year and location ×year) and genotype ×environment were significant at the 1% probability level and the main effects of genotype, location × genotype and year × genotype were significant at the 5% probability level. The effects of genotype, environment and the genotype by environment interaction accounted for 6.48, 77.4 and 13.03% of the total squares, respectively.The biplot of the first principal component (PC1) versus the second principal component (PC2) classified the studied nonparametric stability statistics into three groups.Based on the statistics of NPi (1), NPi (2), NPi (3) and NPi (4), the genotypes with the lowest values are considered as stable genotypes. According to NPi (1) statistics, G1, G6 and G9 genotypes were identified as the most stable and G3 and G5 genotypes as the most unstable genotypes. Based on NPi (2) and NPi (4) parameters, G1, G10 and G9 genotypes were the most stable and G5, G12 and G4 genotypes were the most unstable. Based on the results, the first two principal components explained 68% (42% and 26%, respectively), of the variance of the main variables). Cluster analysis using mean seed yield and non-parametric statistics, placed chickpea genotypes in two main groups. The first cluster included mean seed yield, TOP, MID, σr and σmy. The second cluster consisted of four sub-clusters .
Conclusion:
Based on Si (1), Si (2), Si (3) and Si (6) statistics, G1, G10 and G9 genotypes with the lowest values were identified as the most stable genotypes. G1 and G9 genotypes with the lowest GSI were recognized as the best genotypes in terms of grain yield and stability. Based on the parameters with the dynamics concept of stability, genotypes G1, G10 and G9 were identified as stable genotypes with high yield.
کلیدواژه‌ها [English]
1.Becker, H.C. and Leon, J. 1988. Stability analysis in plant breeding. Plant breed. 101: 1. 1-23.
2.Cobos, M.J., Winter, P., Kharrat, M., Cubero, J.I., Gil, J., Millan, T. and Rubio, J. 2009. Genetic analysis of agronomic traits in a wide cross of chickpea. Field Crops Res. 111: 1-2. 130-136.
3.Segherloo, A.E., Sabaghpour, S.H., Dehghani, H. and Kamrani, M. 2008. Non-parametric measures of phenotypic stability in chickpea genotypes (Cicer arietinum L.). Euphytica. 162: 2. 221-229.
4.Farshadfar, E., Farshadfar, M. and Sutka, J.1999. Genetic Analysis of phenotypic stability parameter in wheat. Acta Agron. Hung. 47: 27-32.
5.Farshadfar, E., Sabaghpour, S.H. and Zali, H. 2012. Comparison of parametric and non-parametric stability statistics for selecting stable chickpea ('Cicer arietinum'L.) genotypes under diverse environments. Aust J. Crop. Sci. 6: 3. 514-524.
6.Fox, P.N., Skovmand, B., Thompson, B.K., Braun, H.J. and Cormier, R. 1990. Yield and adaptation of hexaploid spring triticale. Euphytica. 47: 1. 57-64.
7.Huehn, M. 1979. Beitrage zur erfassung der phanotypischen stabilitat. EDV Med. Biol. 10: 112-117.
8.Huehn, M. 1990. Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica. 47: 3. 189-194.
9.Huehn, M. 1996. Non-parametric analysis of genotype x environment interactions by ranks. P. 213-228. In: Kang, M.S., Gauch, H.G. (eds) Genotype by environment interaction. CRC Press. Boca Raton. FL.
10.Kang, M.S. 1988. A rank–sum method for selecting highyielding, stable corn genotypes. Cereal Res. Commun. 19: 361-364.
11.Kaya, Y., Taner, S .2002. Estimating genotypes ranks by nonparametric stability analysis in bread wheat (Triticum aestivum L.). J Cent Europ Agric. 4: 47-53.
12.Kaya, Y., Akçura, M. and Taner, S. 2006. GGE-biplot analysis of multi-environment yield trials in bread wheat. Turk J. Agric. Forest. 30: 5. 325-337.
13.Ketata, H. 1988. Genotype× environment interaction. Proceedings of Biometrical Techniques for Cereal Breeders. ICARDA. Aleppo. Syria. Pp: 16-32.
14.Ketata, H., Yau, S.K. and Nachit, M. 1989. Relative consistency performance across environments. P. 391-400. In: International symposium on physiology and breeding of winter cereals for stressed Mediterranean environments’. Montpellier, France.
15.Khalili, M. and Pour-Aboughadareh, A. 2016. Parametric and non-parametric measures for evaluating yield stability and adaptability in barley doubled haploid lines. J. Agr. Sci. Tech-Iran. 18: 789-803.
16.Kumar, S., Singh, O., Van Rheenen, H.A. and Rao, K.V.S. 1998. Repeatability of different stability parameters for grain yield in chickpea. Plant breed. 117: 2. 143-146.
17.Kumar Bose, L., Namdeorao Jambhulkar, N., Pande, K. and Nath Singh, O. 2014. Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions. Chilean. J. Agric. Res. 74: 1. 3- 9.
18.Mahtabi, E., Farshadfar, E. and Jowkar, M.M. 2013. Non parametric estimation of phenotypic stability in Chickpea (Cicer arietinum L.). Int J. Agric Crop Sci. 5: 8. 888.
19.Mohammadi, R. and Amri, A. 2008. Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica. 159: 3. 419-432.
20.Nassar, R. and Huehn, M. 1987. Studies on estimation of phenotypic stability: Tests of significance for nonparametric measures of phenotypic stability. Biometrics. 1: 45-53.
21.Raina, A., Khan, S., Wani, M.R., Laskar, R.A. and Mushtaq, W. 2019. Chickpea (Cicer arietinum L.) Cytogenetics, Genetic Diversity and Breeding. In: Al-Khayri, J., Jain, S., Johnson, D. (eds) Advances in Plant Breeding Strategies: Legumes. Springer, Cham. Pp: 53-112.
22.Sabaghnia, N., Dehghani, H. and Sabaghpour, S.H. 2006. Nonparametric methods for interpreting genotype × environment interaction of lentil genotypes. Crop Sci. 46: 3. 1100-1106.
24.Segherloo, A.E., Sabaghpour, S.H.,Dehghani, H. and Kamrani, M. 2008. Non-parametric measures of phenotypic stability in chickpea genotypes (Cicer arietinum L.). Euphytica. 162: 2. 221-229.
25.Shukla, G.K. 1972. Some statistical aspects of partitioning genotype environmental components of variability. Heredity. 29: 2. 237-245.
26.Sohrabi, S.S., Dehghani, H. and Alizadeh, B. 2016. Evaluation of seed yield stability of promising winter rapeseed (Brassica napus L.) lines using principal coordinates analysis. J. Crop Breed. 8: 152-158. (In Persian)
27.Syukur, M., Sujiprihati, S., Yunianti, R. and Kusumah, D.A. 2014. Non paramectric stability analysis for yield of hybrid chili pepper (Capsicum annuum L.) across six different environments. J Agron Indones. 42: 1. 32-38.
28.Thennarasu, K. 1995. On certain non-parametric procedures for studying genotype environment interactions and yield stability. PhD Theses, P.J. School, IARI., New Delhi, 255 p.
29.Tuba, B.B. and Dogan, S. 2006. Stability parameters in lentil. J. Cent. Eur. Agric. 7: 439-444.
30.Varshney, R.K., Thudi, M. and Muehlbauer, F.J. 2017. The Chickpea Genome. Springer International Publishing. DOI 10.1007/978-3-319-66117-9.
31.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: 2. 643-653.
32.Yuksel, K.A.Y.A. and Turkoz, M. 2016. Evaluation of genotype by environment interaction for grain yield in durum wheat using non-parametric stability statistics. Turk. J. Field Crop. 21: 1. 51-59.
33.Zali, H., Farshadfar, E. and Sabaghpour, S.H. 2011. Non-parametric analysis of phenotypic Stability in chickpea (Cicer arietinum L.) genotypes in Iran. Crop Breed. J. 1: 89-100.
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