Document Type : Original Article

Authors

• Shahla Tawana ¹
• Jalal Saba ²
• Farid Shekari ²

¹ MSc. Student, Dept of Agronomy and Plant Breeding, Faculty of Agriculture, Univeristy of Zanjan, Iran.

² Assoc Prof, Dept of Agronomy and Plant Breeding, Faculty of Agriculture, Univeristy of Zanjan, Iran.

Abstract

Introduction
With increasing the world population and need to provide food, the enhancement of crops yield has become very important. One of the most important actions to achieve this goal is to identify the factors affecting the enhancement of yield. based on studies conducted on balancing the yield components in so many crops was concluded that grain yield is a result of interaction between numerous genes and environment and for this reason direct selection has not proven so successful for that and does lead to remarkable increase in yield and so that the selection for yield components has been suggested as a solution for evermore progress in yield increase (Adams,1967). These results indicated that the number of spike/m² was the trait related to higher grain yield under irrigated and late season water stress conditions (Okuyama et al., 2004). The correlation between yield and its components alone is not sufficient to understand the importance of each one of these components in determining the grain yield. while, path analysis not only measures the direct influence of one variable upon another, but also provides means of partitioning both direct and indirect effects and effectively measuring the relative importance of causal factors which helps to build an effective selection program (Ali and Shakor, 2012). This experiment was conducted to determine the most effective traits on grain yield and its components in bread wheat under rainfed conditions.
 
Materials and methods
A field experiment was conducted at the research farm of agricultural faculty of University of Zanjan, Iran (North Longitude 36°41', East Latitude 48°27' and 1620 m Altitude). A square lattice experimental design in two replications was conducted in 2012-2013. Evaluated traits included grain yield, number of spike per plant, number of grain per spike, 1000-grain weight, relative water content, rate of water loss from excised leaves, canopy temperature, difference of canopy with its environment temperature, stem diameter and number of xylem vessels. MSTAT-C and SPSS-20 software were used to analyze the data and LSD test was used to compare the means of traits at 0.05 probability level. The stepwise regression analysis was also carried out to test the significance of the independent variables affecting the grain yield. Then, path analysis was calculated for the traits. For this purpose, a simple coefficient correlation was obtained between all traits and the partial coefficient regression (direct effects) of traits was calculated by SPSS. The indirect effects were also calculated by multiplying the direct effects in simple coefficient correlation.
 
 
 
Results and discussion
Number of spike per plant and number of grain per spike had positive and significant correlation with grain yield with values of r = 0.41^** and r = 0.36^**, respectively. Previous authors also reported similar results for relationships of grain yield and these traits (Aycicek and Yildirim, 2006). No significant correlation was found between 1000-grain weight, Relative water content, number of xylem vessels and stem diameter with grain yield. Number of xylem vessels had negative and significant correlation with 1000-grain weight (r= -0.39**).
Stepwise regression is a semi-automated process of building a model by successively adding or removing variables based solely on the t-statistics of their estimated coefficients. In order to remove effect of non-effective characteristics in regression model on grain yield, stepwise regression was used. Results of stepwise regression showed that the number of spike per plant, grain number per spike and 1000- grain weight with R square of 0.87, had justified the maximum of yield changes.
Path coefficient analysis helps to estimate the influence of each variable upon the resultant variable directly as well as indirectly by partitioning the genetic correlation coefficients. Grain yield per plant was selected as resultant variable and number of spike per plant, number of grain per spike and 1000-grain weight as causal variables. The direct effect of number of spike per plant on grain yield was positive (0.89). The indirect effects of number of grain per spike and 1000-grain weight had values of -0.58 and 0.10, respectively. On the other hand, the traits leaf relative water content and stem diameter had positive and significant correlation with number of grain per spike. On the other hand, direct effects of stem diameter and relative water content on grain number per spike were recorded positive with values of 0.42 and 0.28, respectively. In other words, the increase in stem diameter and RWC can be somewhat increased the number of grains per spike in the experimental conditions.
 
Conclusions
Results of correlation analysis showed that selecting lines with more effective spikes and less number of grains per spike can be recommended as approach of indirect selection for improving grain yield in wheat under rainfed conditions. As a second approach, the selection for more grain per spike in limited number of spike is recommendable. Selection for greater stem diameter also can indirectly lead to grain yield improvement by increasing number of grains per spike.

Keywords

• Path analysis
• Rainfed conditions
• Wheat
• Xylem vessels
• Yield components