Assess Correlation, Stepwise Regression and Path Coefficient Analysis of Characteris-tics Affecting Seed Yield of Canola (Brassica napus L.) Genotypes

Subject Areas : Journal of Crop Nutrition Science

Somayeh Ghalandari ¹ (PhD. Student, Department of Agronomy, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. )
Tayeb Sakinezhad ² (Assistant Professor, Department of Agronomy, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. )
Mani Mojaddam ³ (Associate Professor, Department of Agronomy, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. )
Shahram Lak ⁴ (Professor, Department of Agronomy, Ahvaz Branch, Islamic Azad University, Ahvaz, Iran. )
Mojtaba Alavifazel ⁵ (Department of Agronomy, Ahvaz Branch, Islamic Azad University, Iran.)

Received: 2024-06-26 Accepted : 2024-08-27 Published : 2024-09-07

Keywords: Gibberellin, Morphology, Nitrogen, Oil, Protein, Rapeseed,

Abstract :

BACKGROUND: Correlation and path coefficient analysis could be used as an important tool to evaluate relation between traits, propose most effective trait on seed yield and determine direct and indirect effects of selected traits on dependent variable. OBJECTIVES: Evaluate correlation between traits and selected effective traits those had the highest effect on seed yield by stepwise regression and determine direct and indirect effect of selected traits on seed yield by path analysis. METHODS: This research was done via combined analysis split plot factorial experiment based on randomized complete blocks design (RCBD) with three replications along 2015-16 and 2016-17. The main factor included different level of canola genotype (Hyola401, RGS003, Jerry) and sub factors consisted different concentration of gibberellin hormone (0, 50 and 100 mg.l-1) and different times of application of gibberellin hormone (Planting, vegetative phase before flowering, flowering until pod emergence). RESULT: Correlation between traits revealed the most positive and significant relation between biologic yield (r=0.960**), number of pod per plant (r=0.931**), number of seed per pod (r=0.905**), 1000-seed weight (r= 0.834**), pod length (r= 0.824**), harvest index (r= 0.690**) and seed yield was observed. Also the traits of leaf dry weight (r=0.550*), stem dry weight (r=0.530*) and plant height (r=0.510*) had significant correlation with the seed yield at 5 percent probability level. Stepwise regression analysis introduced five selected traits (biologic yield, number of pod per plant, number of seed per pod, 1000-seed weight and pod length determines) that covered 93.5 percent of variation related to seed yield. Variable of the biological yield with a positive direct effect (0.785) on seed yield with indirect effects of number of pods per plant (0.130), number of seed per pods (0.025), 1000-seed weight (-0.030) and pod length (0.05) caused a positive correlation between this trait and seed yield. So breeders can use selected traits for achieve optimum genotypes instead of direct selection for seed yield. CONCLUSION: Among studied traits, biologic yield had the most direct positive effect (0.785) on seed yield and had an important role to explain seed yield variation.

References:

Ali, N., F. Javidfar, J. Y. Elmira. and M. Y. Mirza. 2003. Relationship among yield components and selection criteria for yield improvement in winter rapeseed (Brassica napus L.). Pak. J. Bot. 35(2): 167-174.
Ali, N., F. Javidfar. and A. A. Attary. 2002. Genetic variability, correlation and path analysis of yield and its components in winter rapeseed (Brassica napus L.). Pak. J. Bot. 34(2): 145-150.
Aguado, A., B. De Los Santos, D. Gamane, L. F. Garcia del Moral. and F. Romero. 2010. Gene effects for cotton-fiber traits in cotton plant (Gossypium hirsutum L.) under Verticillium conditions. Field Crops Res. 116: 209–217.
Amini, F. 2009. Determine correlation between Rice quantitative traits and seed yield through path analysis. MS Thesis. Faculty of Agriculture. Birjand Univ. 101 p. (Abstract in English)
Amor, T. 2018. Correlation and path-coefficient analysis for some yield-related traits in rape seed genotypes. J. Agron. Res. 5(3): 11-20.
Ana, M. J., K. S. Ankica, S. Dejana, M. Radovan. and H. Nikola. 2009. Phenotypic and molecular evaluation of genetic diversity of rapeseed (Brassica napus L.) geno-types. Afr. J. Biotech. 8(19): 4835-4844.
Artin, W. 2015. Recognize effective traits on seed yield of canola genotypes by path analysis. MS Thesis. Faculty of Agriculture. Tarikal Univ. 115 p.
Baradaran, R., A. Majidi harvan, F. Darvish. and M. Azizi. 2006. Relationship be-tween correlation and path coefficient analysis of yield in Canola. J. Agric. Sci. 12 (4): 127-139.
Gardner, F. P., R. B. Pearce. and R. L. Mitchell. 1985. Physiology of crop plants. Ames, IA: Iowa State Univ. Press. USA. 121 pp.
Golkar, P., A. Arzani. and A. M. Rezaei. 2011. Determining relationships among seed yield, yield components and morpho-phenological traits using multivariate analyses in safflower (Carthamus tinctorious L.). Ann. Biol. Res. 2: 162-169.
Hashemi, S. Z., A. R. Golparvar. and M. Rasouli. 2008. Canola, correlation analysis, stepwise regression, path analysis, indirect selection. New Findings in Agri. 2(4): 411-419. (Abstract in English)
Ismaili, A., S. S. Sohrabi, S. Z. Hosseini, R. Namdarian. and D. Godarzi. 2017. Gen-otypic correlation and path analysis of some traits related to oil yield and grain yield in Canola (Brassica napus L.) under non-stress and water deficit stress conditions. Iranian J. Field Crops Res. 14(4): 646-664. (Abstract in English)
Mahasi, M. J. and J. W. Kamundia. 2007. Cluster analysis in rapeseed (Brassica na-pus L.), Afr. J. Agri. Res. 2(9): 409-411.
Mardin, Sh. 2017. Compare crop production of canola genotypes under rainfed condi-tion. Proc. Intl. Crop Sci. Cong. pp: 17-20.
Marjanovic-Jeromela, A., A. Kondic-Spika, D. Saftic-Pankovic, R. Marinkovic. and N. Hristov. 2009. Phenotypic and molecular evaluation of genetic diversity of rape-seed (Brassica napus L.) genotypes. Afr. J. Biotech. 8(19): 4835-4844.
Naderi, R. and Y. Emam. 2010. Interrelationships among grain yield and related char-acters of four oilseed rape (Brassica napus L.) cultivars under drought stress conditions. Desert. 15(2): 133–138.
Ofori, I. 1996. Correlation and path-coefficient analysis of components of seed yield in bambara groundnut (Vigna subterranea). Euphytica. J. 91(1): 103–107.
Rahnamaee tak, A., Sh. Vaeezi, J. Masafari. and A. A. Boshehri. 2007. Correlation and causality analysis and yield-related traits in red beans. Iranian J. Res. Develop. 80(2): 95-102. (Abstract in English)
Sabaghnia, N., H. Dehghani, B. Alizadeh. and M. Mohghaddam. 2010. Interrelation-ships between seed yield and 20 related traits of 49 canola (Brassica napus L.) geno-types in non-stressed and water-stressed environments. Spanish J. Agri. Res. 8(2): 356-370.
Sato, T. 2002. New estimation method for fatty acid composition in oil using near infra-red spectroscopy. Biosci. Biotech. Biochem. J. 66: 2543-2548.
Semahegn Belete, Y. 2011. Genetic variability, correlation and path analysis studies in Ethiopian mustard (Brassica carinata A. Brun) genotypes. Intl. J. Plant Breed. Genetics. 5(4): 328–338.
Shahraki, M., R. Salimbek, M. Galavi. and H. R. Fanaei. 2013. Multivariate analysis for canola varieties in Sistan region of Iran. Archives Appl. Sci. Res. 5(1): 308-311.
Sharma, S. 1996. Applied Multivariate Techniques. John Wiley Sons. 1st Edition. New York. NY. USA.
Siadat, S. A. and S. S. Hemayati. 2009. Effect of sowing date on yield and yield com-ponents of three oilseed rape varieties. Plant Eco-physiology. 1: 31-35. (Abstract in Eng-lish)
Soltani Howyzeh, M., M. Moradi, T. Saki nezhad, S. Zaker nezhad. and A. Etaa. 2018. Evaluation of the relationships among yield and related traits in spring Canola cul-tivars using path analysis. J. Crop Breed. 10(27): 125-134. (Abstract in English)
Sosulski, F. W. and G. I. Imafidon. 1990. Amino acid composition and nitrogen-to-protein conversion factors for animal and plant foods. J. Agric. Food. Chem. 38: 1351-1356.
Tian, Z. 2017. Comparative growth and seed yield of Canola under dry land condi-tions. Proc. Intl. Crop Sci. Cong. pp: 45-50.
Xianc, A. 2018. Assess correlations with seed yield and agronomic traits of rapeseed cultivar and determine regression and path analysis. 2th Cong. Approach to Achieve Sust. Agric. pp: 109-120.