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

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.

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Publication Details

Journal
Journal of Crop Nutrition Science
Published
2024-09-07
DOI
https://doi.org/10.71874/jcns.2024.16575
Primary Topic
Plant Pathogens and Resistance
Type
article
Field-Weighted Citation Impact
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article

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

Journal of Crop Nutrition Science
Plant Pathogens and Resistance
article

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

article en

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.

Journal of Crop Nutrition Science
Islamic Azad University, Ahvaz Branch (IR)
Openalex Percentile: Top 41%
Plant Pathogens and Resistance
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