Sequential path analysis of some yield and quality components in sugar beet grown in normal and drought conditions

• Main Authors: Mehdi Baradaran Firouzabadi, Naser Farrokhi, Mahdieh Parsaeyan
• Format: Article
• Language: English
• Published: PAGEPress Publications 2012-01-01
• Series: Italian Journal of Agronomy
• Subjects: Correlation; Drought; Sequential path model; stepwise regression; Sugar beet
• Online Access: https://www.agronomy.it/index.php/agro/article/view/382
• ISSN: 1125-4718; 2039-6805

Through biometrical analyses of yield and its components selection indices can be generated and be used in future breeding programs. Sugar yield components were considered as the first order variables (FOV) in previous path analyses studies, while white sugar yield (WSY) and its related traits were the FOV here. Three lines of sugar beet (7219-P.69, BP-Karaj, 7112) were evaluated in drought and non-drought conditions. Two sequential path models were used for analysis of associations among WSY and its related traits by arraying the various variables in first-, second-, and third-order paths on the basis of their maximum direct effects and minimal collinearity. Four first-order variables, namely root diameter, sugar yield, molasses content and sugar content, revealed highest direct effects on WSY at normal condition, while root length, α-amino-N, root yield, crown dry weight, water use efficiency and Na+ were found to fit as second-order variables. Three first-order variables, namely sugar content, sugar yield and molasses content, revealed highest direct effects on white sugar yield at drought-stress condition. In this case, sugar yield had the highest direct effect on WSY. In general, the sequential path analysis was efficiently demonstrated the effects of predictor variables.