Non-Parametric Stability Analysis of Yield in Lentil Genotypes

Document Type : Research Paper

Authors

1 Assistant Professor, Dryland Agricultural Research Institute,Zanjan Agricultural and Natural Resourses Research and Education Center, Agricultural Reaearch,Education and Extention Organization(AREEO), Zanjan,Iran

2 Research Assistant Professor, Deem Kishore Agricultural Research Institute, Lorestan Agriculture and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Khorramabad, IranKhorramabad, Iran

3 98 / 5,000 Translation results Translation result Associate Professor, Country Rainfed Agricultural Research Institute, Agricultural Research, Education and Extension Organization, Maragheh, Iran.Maragheh,Iran

Abstract

Background and objectives: Lentils are one of the most important crop plants in rotation.Lentil seed yield is strongly influenced by environments and breeders often determine the stability of high yield genotypes across environments before recommending a stable cultivar for release. Genotypial adaptability to environmental fluctuations is important for the stabilization of crop production over regions and years.Identification of high- yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. The challenge of the interaction of genotype × environment is one of the main issues in plant breeding. Various statistical methods to estimate the interaction of genotype × environment and choice the stable and productive genotype(s) have been introduced. One of the applications of Non-Parametric methods is determination of genotypes rank in different environments, which is also used as a measuring stability. A stable genotype shows similar ranks across different environments and has minimum rank variance in different environments. Non-Parametric Stability Statistics require no statistical assumptions about the distribution of the phenotypic values and are easy to use.
Materials and methods: This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with 3 replications.
Results: The combined analysis of variance indicated that the main effects of genotype (G), environment (E) and their interactions genotype and environmen (G×E) were highly significant (p < . ). The principal component analysis (PCA) based on rank correlation matrix indicated that the first two PCAs explained . of the variance of original variables. Based on bi-plot analysis, the stability parameters were classified into four groups. Clustering of the genotypes according to the mean yield and nonparametric stability statistics showed that there were two main clusters. Overall, according to mean rank of nonparametric stability parameters, G17 , G3 , G9 and G2 had the lowest variations and were recognized as the most stable genotypes. Genotypes G7 , G11 and G13 had the highest values of mean rank of parameters and therefore, would be considered to be the most unstable. According to the present study, the stability measures Ysi, and TOP were associated with mean yield (MY) and the dynamic concept of stability. Therefore, these procedures were suitable for selecting stable and high yielding genotypes
Conclusion: Therefore, these procedures were suitable for selecting stable and high yielding genotypes. Based on these parameters, genotypes G13 (340 t/ha) and G11 (305 t/ha) were identified as high yield stable genotypes.

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Main Subjects


  1.  Singh, B., Padhy, A. K., Ambreen, H., Yadav, M., Bhardwaj, S., Singh, G. & Bhatia, S. (2022). Understanding Abiotic Stress Responses in Lentil under Changing Climate Regimes. In Developing Climate Resilient Grain and Forage Legumes (pp. 179-204). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-16-9848-4_9

    1. (2019). Agricultural Data: agriculture and food trade.In Food and Agriculture Organization of the united statistics Division(http://faostst.fao.org.
    2. Zaccardelli, M. Sonnante, G., Lupo, F., Branca, F., & de Falco, E. (2010). Leguminose minori (cece, lenticchia, cicerchia, fava); Consiglio per Ricerca Sperimentazione Agricoltura: Rome, Italy, 73 P.
    3. Karimizadeh, R., Safikhani Nasimi, M., Mohammadi, M., Seyyedi, F., Mahmoodi, A. A., & Rostami, B. (2008). Determining rank and stability of lentil genotypes in rainfed condition by nonparametric statistics. JWSS-Isfahan University of Technology, 12(43), 93-102. [In Persian].
    4. Sohrabi, S. S., Dehghani, H., & Alizadeh, B. (2014). Grouping of promising winter rapeseed (Brassica napus) lines based on genotype× environment interaction. Seed and Plant Improvement Journal, 30(4). ,( 8), 152-158 [In Persian].
    5. Safavi, S. M., & Bahraminejad, S. (2017). The evaluation of genotype× environment interactions for grain yield of oat genotypes using AMMI model. Journal of Crop Breeding, 922, 125-132. [In Persian].
    6. Pourdad, S. S., Moghaddam, M. J., Faraji, A., & Naraki, H. (2014). Study on different non-parametric stability methods on seed yield of spring rapeseed varieties and hybrids. Iranian Journal of Field Crop Science, 44(4). [In Persian].
    7. Movahhedi, Z., Dehghani, H. A. M. I. D., & Mofidian, M. (2010). A study of yield stability in cold region ecotypes of alfalfa (Medicago sativa) through non-parametric measures. Iranian Journal of Field Crop Science, 40(4), 103-111. [In Persian].
    8. Moghaddaszadeh, M., Asghari Zakaria, R., Hassanpanah, D., & Zare, N. (2019). Nonparametric stability analysis of tuber yield in potato (Solanum tuberosum ) genotype. Journal of Crop Breeding.,( 28): 50-63 [In Persian].
    9. Yan, W., & Kang, M. S. (2002). GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. CRC press. Boca Raton, FL, USA.
    10. Akbarpour, O., & Pezeshkpour, P. (2022). Evaluation of Grain Yield Stability of Lentil Genotypes using Parametric Methods in Rainfed Conditions of Khorramabad. Journal of Crop Breeding, 14(44), 227-238.
    11. Pezeshkpour, P., Karimizadeh, R., Mirzaei, A., & Barzali, M. (2021). Analysis of Yield Stability of lentil Genotypes using AMMI Method. Journal of Crop Breeding, 13(37), 132-145. [In Persian].
    12. Huehn, M. (1990). Nonparametric measures of phenotypic stability. Part 1: Theory. Euphytica, 47, 189-194.
    13. Hühn, M. (1996). Nonparametric analysis of genotype x environment interactions by ranks. Genotype-by-environment interaction, 235-271.
    14. Sabaghnia, N., Dehghani, H., & Sabaghpour, S. H. (2006). Nonparametric methods for interpreting genotype× environment interaction of lentil genotypes. Crop science, 46(3), 1100-1106.
    15. Segherloo, A. E., Sabaghpour, S. H., Dehghani, H., & Kamrani, M. (2008). Non-parametric measures of phenotypic stability in chickpea genotypes (Cicer arietinum). Euphytica, 162, 221-229.
    16. Mortazavian, S. M., & Azizi-Nia, S. (2014). Nonparametric stability analysis in multi-environment trial of canola. Turkish Journal of Field Crops, 19(1), 108-117.
    17. Dehghani, M. R., Majidi, M. M., Mirlohi, A., & Saeidi, G. (2016). Integrating parametric and non-parametric measures to investigate genotype× environment interactions in tall fescue. Euphytica, 208, 583-596.
    18. Vaezi, B., Pour-Aboughadareh, A., Mehraban, A., Hossein-Pour, T., Mohammadi, R., Armion, M., & Dorri, M. (2018). The use of parametric and non-parametric measures for selecting stable and adapted barley lines. Archives of Agronomy and Soil Science, 64(5), 597-611.
    19. Vaezi, B., Pour-Aboughadareh, A., Mohammadi, R., Mehraban, A., Hossein-Pour, T., Koohkan, E. & Siddique, K. H. (2019). Integrating different stability models to investigate genotype× environment interactions and identify stable and high-yielding barley genotypes. Euphytica, 215, 1-18.
    20. Khalili, M., & POUR, A. A. (2016). Parametric and non-parametric measures for evaluating yield stability and adaptability in barley doubled haploid lines. Journal of Agricultural Science. (18), 789-803.
    21. Huehn, M. 1979. Beitrage zur Erfassung der phänotypischen Stabilitä t. I. Vorschlag einiger auf Ranginformationen beruhenden Stabilitä tsparameter. EDV in Medizin ünd Biologie, (10), 112–117.
    22. Nassar, R., & Huhn, M.(1987). Studies on estimation of phenotypicstability: Tests of significance for non-parametric measures of phenotypic stability. Biometrics,(43), 45-53.
    23. Ketata, H. (1988). Genotype× environment interaction. Proceedings of Biometrical Techniques for Cereal Breeders. ICARDA, Aleppo, Syria, 16-32.
    24. Ketata, H., Yau, S. K., & Nachit, M. (1989). Relative consistency performance across environments. In International symposium on physiology and breeding of winter cereals for stressed mediterranean environments. Montpellier. July, 3-6.
    25. Kang, M. S. (1988). A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Research Communications, 16(1/2), 113-115.
    26. Fox, P. N., Skovmand, B., Thompson, B. K., Braun, H. J., & Cormier, R. (1990). Yield and adaptation of hexaploid spring triticale. Euphytica, 47, 57-64.
    27. Thennarasu, K. (1995). On Certain Non-parametric Procedures for Studying Genotype-Environment Inertactions and Yield Stability (Doctoral dissertation, IARI, Division of Agricultural Statistics, New Delhi). 255 pp.diverse environments.Australian Journal of Crop Science,( 6), 514-524.
    28. Bose, L. K., Jambhulkar, N. N., Pande, K., & Singh, O. N. (2014). Use of AMMI and other stability statistics in the simultaneous selection of rice genotypes for yield and stability under direct-seeded conditions. Chilean journal of agricultural research, 74(1), 3-9.
    29. Farshadfar, E., Sabaghpour, S. H., & Zali, H. (2012). Comparison of parametric and non-parametric stability statistics for selecting stable chickpea ('Cicer arietinum'L.) genotypes under diverse environments. Australian Journal of Crop Science, 6(3), 514-524.
    30. Farshadfar, E. (2008). Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pakistan Journal of biological sciences, 11(14), 1791.
    31. Tumuhimbise, R., Melis, R., Shanahan, P., & Kawuki, R. (2014). Genotype× environment interaction effects on early fresh storage root yield and related traits in cassava. The Crop Journal, 2(5), 329-337.
    32. Shukla, G. K. (1972). Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29(2), 237-245.
    33. Zali, H., Farshadfar, E., & Sabaghpour, S. H. (2011). Non-parametric analysis of phenotypic stability in chickpea (Cicer arietinum) genotypes in Iran. Crop Breed. J., (1), 89-100.
    34. Roostaei, M., Mohammadi, R., & Amri, A. (2014). Rank correlation among different statistical models in ranking of winter wheat genotypes. The crop journal, 2(2-3), 154-163.
    35. Noruzi, E., & Ebadi, A. (2015). Comparison of parametric and non-parametric methods for analysing genotype× environment interactions in sunflower (Helianthus annuus L.) inbred lines. Jordan Journal of Agricultural Sciences, 11(4). 959-979.
    36. Solomon, K. F., Smit, H. A., Malan, E., & Du Toit, W. J. (2007). Comparison study using rank based nonparametric stability statistics of durum wheat. World J. Agric. Sci, 3(4), 444-450.
    37. LIU, Y. J., Chuan, D. U. A. N., TIAN, M. L., HU, E. L., & HUANG, Y. B. (2010). Yield stability of maize hybrids evaluated in maize regional trials in southwestern china using nonparametric methods. Agricultural Sciences in China, 9(10), 1413-1422.
    38. Mut, Z., Gülümser, A., & Sirat, A. (2010). Comparison of stability statistics for yield in barley (Hordeum vulgare L.). African Journal of Biotechnology, 9(11), 1610-1618.
    39. Mohammadi, R., & Amri, A. (2008). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159, 419-432.
    40. Kaya, Y., & Turkoz, M.( 2016). Evaluation of genotype by environment
      interaction for grain yield in durum wheat using non-parametric stability statistics. Turk. Journal of Field Crops., (21), 51-59.
    41. Tadege, M. B., Utta, H. Z., & Aga, A. A. (2014). Association of statistical methods used to explore genotype environment interaction (GEI) and cultivar stability. African journal of agricultural research, 9(29), 2231-2237.
    42. Mohammadi, R., Abdulahi, A., Haghparast, R., & Armion, M. (2007). Interpreting genotype× environment interactions for durum wheat grain yields using nonparametric methods. Euphytica, 157(1-2), 239-251.
    43. Syukur, M., Sujiprihati, S., Yunianti, R., & Kusumah, D. A. (2014). Non paramectric stability analysis for yield of hybrid chili pepper (Capsicum annuum L.) across six different environments. Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy), 42(1), 32-38.
    44. Soughi, H. A., Jelodar, N. B., Ranjbar, G. A., & Pahlevani, M. H. (2016). Simultaneous selection based on yield and yield stability in bread wheat genotypes. Journal of Crop Breeding, 8(18), 119-125. [In Persian].