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Five statistical procedures were used to study the relationship between the sugar yield and its components using the data collected over the two successive seasons of (2012/2013 and 2013/2014) at Mallawy Research Station, Menia Governorate. The five methods of analysis namely, simple correlation coefficient, path analysis, full model regression, stepwise multiple linear regression and factor analysis that have different mathematical concepts. Highly significant and positive correlation coefficients were detected between sugar yield and each of number of internodes/stalk, number of millable stalks/m, total soluble solids % and sucrose %. The results of path analysis revealed that the number of millable stalks/m was the most important character with the highest direct and indirect effects on sugar yield followed by sucrose % and stalk weight. The same three traits were also responsible for the most sugar yield variability using full model regression and stepwise multiple linear regression with goodness of fit. Factor analysis grouped the studied eight traits as sugar yield components into three main factors accounting for 85.3% of the total variability in the dependence structure. Factor I was responsible for 34.89% of the total variation and included stalk weight, stalk thickness and number of millable stalks/m. Factor II contained total soluble solids % and sucrose and contributed at 28.17% of the total variation. Stalk height, number of internodes/stalk and reducing sugar % were the components of the last factor and explained 22.25 % of the total variation. Based on the previous results, it could be concluded that the high sugar yield of sugarcane crop would be obtained by selecting breeding materials that have heavy weight of stalk, large number of millable stalks/m and high percent of sucrose.

ESTIMATING THE RELATIONSHIP BETWEEN SUGAR YIELD AND ITS COMPONENTS USING VARIOUS STATISTICAL METHODS IN SUGAR CANE