Sequential Path Analysis for Determination of Relationship Between Yield and Yield Components in Bread Wheat (<i>Triticum aestivum</i>.L.)

</p><p>An experiment was conducted to evaluate 295 wheat genotypes in Alpha-Lattice design with two replications. The arithmetic mean and standard deviation of grain yield was 2706 and 950 (kg/ha),respectively. The results of correlation coefficients indicated that grain yield had signif...

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Bibliographic Details
Main Authors: Mohtasham MOHAMMADI, Peyman SHARIFI, Rahmatollah KARIMIZADEH
Format: Article
Language:English
Published: University of Agricultural Sciences and Veterinary Medicine, Cluj-Napoca 2014-03-01
Series:Notulae Scientia Biologicae
Online Access:http://notulaebiologicae.ro/index.php/nsb/article/view/9105
Description
Summary:</p><p>An experiment was conducted to evaluate 295 wheat genotypes in Alpha-Lattice design with two replications. The arithmetic mean and standard deviation of grain yield was 2706 and 950 (kg/ha),respectively. The results of correlation coefficients indicated that grain yield had significant and positive association with plant height, spike length, early growth vigor and agronomic score. Whereas there were negative correlation coefficients between grain yield and days to physiological maturity and canopy temperature before and during anthesis. Path analysis indicated agronomic score and plant height had high positive direct effects on grain yield, while canopy temperature before and during anthesis, and days to maturity, wes another trait having negative direct effect on grain yield. The results of sequential path analysis showed the traits that accounted as a criteria variable for high grain yield were agronomic score, plant height, canopy temperature, spike length, chlorophyll content and early growth vigor, which were determined as first, second and third order variables and had strong effects on grain yield via one or more paths. More important, as canopy temperature, agronomic score and early growth vigor can be evaluated quickly and easily, these traits may be used for evaluation of large populations.</p>
ISSN:2067-3205
2067-3264