Multivariate Statistical Analysis to Yield of Canola under Drought Stress and Spraying of Gibberellin and Salicylic Acid

Subject Areas : Journal of Crop Nutrition Science

Abbas Maleki ¹ , Amin Fathi ²

1 - Assistant Professor, Department of Agronomy and Plant Breeding, Ilam Branch, Islamic Azad University, Ilam. Iran.
2 - Ph.D. Students of Agronomy, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran.

Received: 2019-06-22 Accepted : 2019-08-25 Published : 2019-09-01

Keywords: Irrigation, Hormone, Growth Regulator, <i>Correlation, Regression</i>,

Abstract :

BACKGROUND: Drought stress is one of the most critical factors in the reduction of yield among plant growth factors. Salicylic acid is a regulator that plays a vital role in the physiological processes of the plant. Gibberellin is one of the plant growth-regulating hormones that have different effects on the growth and development of many plants during growth stages. OBJECTIVES: The purpose of this research is to identify the traits that have a strong and productive relationship with the performance of canola under conditions of drought stress and levels of Gibberellin acid and salicylic acid application. METHODS: An experiment was conducted as a split-split plot based on randomized complete block design (RCBD) with three replications during the cultivation season of 2017-2018 in Darreh-Shahr city, Ilam Province. The experimental factors were four levels of irrigation, including normal irrigation, cut of irrigation in stem elongation, cut of irrigation at the start of flowering. The cut of Irrigation at the beginning of the pod were allocated as main plots. Sub factors and sub-sub factors were two levels of spraying and non-spraying of Gibberellin hormone and salicylic acid, respectively. RESULT: Based on the results of correlation coefficients between the traits, it was determined that all of the studied traits had a significant correlation with grain yield. Investigation of regression coefficients using t-test showed that only the effects of three traits such as the number of flowering branches, 1000-seed weight, and harvest index were significant, but other characteristics in the model had a feeble impact on grain yield prediction. The number of flowering branches and harvest index has a more substantial contribution than other characters in predicting grain yield because one unit of increase causes the grain yield to increase by 42% in the standard deviation scale. CONCLUSION: According to the results, to improve the yield of rapeseed, three at-tributes of 1000 seed weight and number of flowering branches and harvest index have to be emphasized that directly or indirectly affect this trait.

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