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pgr 2022, 8(2): 69-82 Back to browse issues page
Valuations of Variables as Selection Index for Improving Grain Yield in Bread Wheat
Kaveh Sadeghi, Mohammadhadi Pahlevani *, Mohsen Esmeilzadeh Moghaddam, Khalil Zaynali Nezhad
Abstract:   (2139 Views)
Identifying selection indices is the most important step of a breeding project that aims to improve grain yield. The definition of the selection index is usually done by evaluating the variables in multivariate statistical methods. In the present study, the relationship between grain yield and its components in bread wheat genotypes was determined by multivariate statistical methods. The experiment was conducted in a randomized complete block design with 3 replications in the research farm of Gorgan University of Agricultural Sciences and Natural Resources in the 2018-19 crop years. Ten commercial cultivars of bread wheat along with their offspring from direct and inverse crosses in a dialysis arrangement were evaluated for morphological and phenological traits, especially grain yield and its components. The results of genotypic and phenotypic correlation coefficients showed a positive and significant correlation (at 1% probability level) between grain yield and spike length, spike weight, number of fertile tillers, number of seeds per spike, number of spikes per spike, 1000-seed weight, biological yield and harvest index. Based on the results of stepwise regression analysis, biological yield, harvest index, number of grains per main spike and main spike weight were entered into the regression model, respectively, and explained a total of 98% of the variation in grain yield. Based on the results of path analysis, biological yield had the highest direct effect on grain yield. After biological yield, the most direct effect on grain yield was related to the weight of main spike. Also, by considering eigenvalues greater than one in factor analysis, 8 hidden factors were identified that explained a total of 75.18% of the data changes. In general, it can be concluded that biological yield, harvest index, number of seeds per spike and weight of spike compared to other traits can be used as appropriate indicators in breeding programs to select high-yield genotypes in field conditions. Genotypes Alo, Ehsan♂ × Gonbad♀ and Ehsan had the highest value for the studied traits, which can be used in future breeding researches.
Keywords: Path analysis, Stepwise regression, Genotypic correlation, GGE biplot
Full-Text [PDF 1390 kb]   (260 Downloads)    
Type of Study: Research | Subject: Population genetics
Received: 2022/01/26 | Accepted: 2022/03/9
1. Abedini, S,. Mohammadi-Nejad, G. and Nakhoda, B. (2016). Evaluation of agronomic traits and yield potential diversity inbreed wheat inbred lines Triticum aestivum L. derived from Roshan×Falat cultivar. Journal of Crop Breeding, 8: 1-10 (In Persian).
2. Ahmad, T., Kumar, A., Pandey, D. and Prasad, B. (2018). Correlation and path coefficient analysis for yield and its attributing traits in bread wheat (Triticum aestivum L. em Thell). Journal of Applied and Natural Science, 10: 1078-1084. [DOI:10.31018/jans.v10i4.1867]
3. Ahmadi, A,. Pourghasemi, R. and Hosseinpour, T. (2014). Relationship between grain yield and yield components of barley genotypes by multivariate statistical methods. Agroecology Journal, 10: 1-13 (In Persian).
4. Aklilu, E., Dejene, T. and Worede, F. (2020). Genotypic and phenotypic correlation and path coefficient analysis for yield and yield related traits in barley (Hordeum vulgare L.) landraces in North Gondar, Ethiopia. Indian Journal of Pure & Applied Biosciences, 8: 24-36. [DOI:10.18782/2582-2845.8082]
5. Baye, A., Berihun, B., Bantayehu, M. and Derebe, B. (2020). Genotypic and phenotypic correlation and path coefficient analysis for yield and yield-related traits in advanced bread wheat (Triticum aestivum L.) lines. Cogent Food & Agriculture, 6: 1-17. [DOI:10.1080/23311932.2020.1752603]
6. Chalish, L. and Houshmand, S. (2011). Estimate of Heritability and relationship of some durum wheat characters using recombinant inbred lines. Electronic journal of crop Production, 2: 223-238.
7. Dabi, A., Mekbib, F. and Desalegn, T. (2016). Estimation of genetic and phenotypic correlation coefficients and path analysis of yield and yield contributing traits of bread wheat (Triticum aestivum L.) genotypes. International Journal Natural Resource Ecology Management, 1: 145-154.
8. Dabiri, M., Bahramnejad, M. and Baghbanzadeh, M. (2009). Ammonium salt catalyzed multicomponent transformation: simple route to functionalized spirochromenes and spiroacridines. Tetrahedron, 65: 9443-9447. [DOI:10.1016/j.tet.2009.08.070]
9. Dashtaki, M., Bihamta, M.H., Majidi, E. and Azizinejad, R. (2022). Effect of end-of-season drought stress on yield, yield components and some morphological and phenological characteristics of bread wheat (Triticum aestivum L.). Journal of Plant Research (Iranian Journal of Biology), 1: 34-47 (In Persian).
10. Dawari, N.H. and Luthra, O.P. (1991). Character association studies under high and low environments in wheat. Indian Journal of Agricultural Research, 25: 515-518.
11. Dofing, S. and Knight, C. (1992). Alternative model for path analysis of small-grain yield. Crop Science, 32: 487-489. [DOI:10.2135/cropsci1992.0011183X003200020040x]
12. Dorrani-Nejad, M,. Mohammadi-Nejad, G. and Nakhoda, B. (2016). Assessment of relationship between agronomic traits and grain yield in recombinant inbred lines derived from roshan × falat wheat varieties under drought stress. Journal of Crop Breeding, 8: 52-59 (In Persian).
13. Farahani, A. and Arzani, A. (2006). Investigating genetic variation of cultivars and F1 hybrids of durum wheat using agronomic and morphologic characters. Journal of Sciences and Technology of Agriculture and Natural Resources, 10: 341-354.
14. Gholizadeh, A., Dehghani, H., Amini, A. and Akbarpour, O. (2018). Study on trait relations of wheat genotypes using the Biplot method. Iranian Journal of Field Crop Science, 3: 121-136 (In Persian).
15. Golparvar, A.R., Ghanadha, M.R., Zali, A.A. and Ahmadi, A. (2002). Evaluation of morphological traits as selection criteria in breeding of wheat. Iranian Journal of Crop Sciences, 4: 202-205 (In Persian).
16. Hamza, H., Asghari, A., Mohammadi, S.A., Sofalian, O. and Mohammadi, S. (2017). Grouping of spring wheat recombinant inbred lines base some agronomic traits. Journal of Agronomy and Plant Breeding, 13: 43-54 (In Persian).
17. Holland, J.B. (2006). Estimating genotypic correlations and their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop Science, 46: 642-654. [DOI:10.2135/cropsci2005.0191]
18. Islam, M.A., Raffi, S.A., Hossain, M.A. and Hasan, A.K. (2015). Character association and path coefficient analysis of grain yield and yield related traits in some promising early to medium duration rice advanced lines. International Journal of Experimental Agriculture, 5: 8-12.
19. Janmohammadi, M., Sabaghnia, N. and Nouraein, M. (2014). Path analysis of grain yield and yield components and some agronomic traits in bread wheat. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 62: 945-952. [DOI:10.11118/actaun201462050945]
20. Joseph, J. and Santhosh Kumar, A. (1999). Character association and cause effect analysis in some F2 population of green gram. Legume Research, 22: 99-103.
21. Keshavarznia, R., Mohammadi Nargesi, B. and Abassi, A.R. (2013). Study of genetic diversity of common bean based on morphological traits under both normal and drought stress conditions. Iranian Journal of Field Crop Science, 44: 305-315 (In Persian).
22. Khodadadi, M., Dehghani, H. and Fotokian, M.H. (2011). Study of heritability, path and factor analysis in winter wheat (Triticum aestivum L.) genotypes. Journal of Agronomy Sciences, 4: 67-78 (In Persian).
23. Mohammadi, R. and Amri, A. (2011). Analysis of genotype × environment interaction in rain-fed durum wheat of Iran using GGE-biplot and non-parametric methods. Canadian Journal of Plant Science, 92: 757-770. [DOI:10.4141/cjps2011-133]
24. Motamedi, M. and safari, P. (2018). Biplot Analysis of diallel data for water deficit stress tolerance in wheat. Plant Genetic Researches, 4: 61-74 (In Persian). [DOI:10.29252/pgr.4.2.61]
25. Nayebi Aghbolag, K.H., Sabaghnia, N., Asandi Somehsofla, M. and Janmohammadi, M. (2019). Study of Correlation Coefficients of Agronomic Traits and Path Analysis of Seed Yield in Rye. Journal of Plant Productions, 42: 31-46 (In Persian).
26. Neyestani, E., Makarian, H., Ameri, A.A. and Haydari, M. (2020). Evaluation of yield relationship with yield components in different dry land wheat genotypes. Journal of Plant Ecophysiology (Arsanjan Branch), 40: 82-90 (In Persian).
27. Okuyama, L.A., Ferizzi, L.C. and Neto, J.F.B. (2004). Correlation and path analysis of yield and its components and plant traits in wheat. Ciencica Rural, Santa Maria, 34: 1701-1708. [DOI:10.1590/S0103-84782004000600006]
28. Radaei Alamoli, Z., Jahansouz, M., Soufizadeh, S. and Hosseini, S.M. (2020). Evaluation the growth characteristics, yield and yield components of wheat and barley under water and nitrogen stress conditions. Iranian Journal of Field Crop Science, 2: 87-104 (In Persian).
29. Rahmati, M., Hosseinpour, T. and Ahmadi, A. (2020). Assessment of interrelationship between agronomic traits of wheat genotypes under rain-fed conditions using double and triple biplots of genotype, trait and yield. Journal Iranian Dryland Agronomy, 1: 1-20 (In Persian).
30. Rakshit, S., Ganapathy, K., Gomashe, S., Rathore, A., Ghorade, R., Kumar. M.N., Ganesmurthy, K., Jain, S., Kamtar, M. and Sachan, J. (2012). GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data. Euphytica, 185: 465-479. [DOI:10.1007/s10681-012-0648-6]
31. Roohi, E., Pezeskpour, P. and Fatehi, S. (2019). Grouping of Kabuli chickpea (Cicer arietinum L.) genotypes in Entezary planting using multivariate statistical methods. Journal Iranian Dryland Agronomy, 2: 203-218 (In Persian).
32. Sabaghnia, N., Mohebodini, M. and Janmohammadi, M. (2016). Biplot analysis of trait relations of spinach (Spinacia oleracea L.) landraces. Genetika, 48: 675-690. [DOI:10.2298/GENSR1602675S]
33. Sadeghi, F. and Rotbeh, J. (2016). Evaluation of grain yield and yield components using descriptive and multivariate statistics. Journal of Crop Breeding. 8: 212-221 (In Persian). [DOI:10.29252/jcb.8.18.212]
34. Saraei, M., Sam Daliri, M., Mohadesi, A. and Moradkhani, M. (2018). Correlation analysis between grain yield and some important traits related to rice lines using path analysis. Journal of Crop Breeding, 10: 49-56 (In Persian). [DOI:10.29252/jcb.10.27.49]
35. Saremi-Rad, A., Seyed Hassan Pour, S.M., Mostafavi, K. and Sadeghi Give, H. (2018). Assessment of relationship between grain yield and some related traits in oilseed sunflower genotypes. Iranian Journal of Agronomy & Plant Breeding. 1: 1-9 (In Persian).
36. Semnaninejad, H., Nourmohammadi, G., Rameeh, V. and Cherati, A. (2021). Correlation and path coefficient analyses of phenological traits, yield components and quality traits in wheat. Brazilian Journal of Agricultural and Environmental Engineering, 9: 597-603. [DOI:10.1590/1807-1929/agriambi.v25n9p597-603]
37. Shahbazian, N., Dadi, A. and Iran Nejad, H. (2007). Reaction of winter wheat response to previous culture (fallow, wheat, soybeans and alfalfa) and manure application in Qazvin region. Agricultural Sciences, 13: 125-135 (In Persian).
38. Singh, S. and Singh, T. (2001). Correlation and path analysis in common wheat (Triticum aestivum L.) under light texture soil. Resources on Crops, 2: 99-101.
39. Soleymani, A. and Naseri, R. (2020). Evaluation of relationships between grain yield and agro-physiological traits of bread wheat genotypes under rainfed conditions. Journal of Environmental Stresses in Crop Sciences. 13: 701-714 (In Persian).
40. Subhashchandra, B., Lohithaswa, H.C., Desai, A.S. and Hanchinal, R.R. (2009). Assessment of genetic variability and relationship between genetic diversity and transgressive segregation in tetraploid wheat. Karnataka Journal of Agricultural Sciences, 22: 36-38.
41. Valizadeh, S., Ismaili, A., Ahmadi, H., Akbarpour, O.A., Bajalan, B. and Amini, A. (2020). Use of restricted maximum likelihood approach for estimation of genotypic correlation and heritability in bread wheat (Triticum aestivum L.) under water deficit stress. Plant Genetic Researches, 6: 183-200 (In Persian).
42. Xu, N., Fok, M., Li, J., Yang, X. and Yan, W. (2017). Optimization of cotton variety registration criteria aided with a genotype- by-trait biplot analysis. Scientific Reports, 7: 17237. [DOI:10.1038/s41598-017-17631-4]
43. Yan, W. and Fregeau-Reid, J. (2018). Genotype by yield×trait (GYT) Biplot: a novel approach for genotype selection based on multiple traits. Scientific Reports, 8: 8242. [DOI:10.1038/s41598-018-26688-8]
44. Yin, X., Chasalow, S.D., Stam, P.M., Kropff, J., Dourleijn, C.J., Bos, I. and Bindraban, P.S. (2002). Use of component analysis in QTL mapping of complex crop traits: a case study on yield in barley. Plant Breeding, 121: 314-319. [DOI:10.1046/j.1439-0523.2002.729117.x]
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Sadeghi K, Pahlevani M, Esmeilzadeh Moghaddam M, Zaynali Nezhad K. Valuations of Variables as Selection Index for Improving Grain Yield in Bread Wheat. pgr 2022; 8 (2) :69-82
URL: http://pgr.lu.ac.ir/article-1-233-en.html

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