| Titles |
|
English :
|
APPLYING A DEVELOPED PATH ANALYSIS MODEL IN FABA BEAN
|
|
Arabic :
|
تطبيق نموذج معدل لتحليل معامل المرور في محصول الفول البلدي
|
|
| Abstract |
Two field experiments were conducted at the Agricultural Research Station of New Valley during the successive seasons of 2010/2011 and 2011/2012 to evaluate the yielding ability of twelve faba bean genotypes and to study the relationship between seed yield and its main components. Analogous to multiple linear regression model, the orthogonality (no or weak associations among the explanatory variables) is a necessary assumption to satisfy goodness of fit of the ordinary path analysis model. In fact, this assumption is usually violated because there are strong associations among yield components which are called the multicollinearity problem. Therefore, the current work proposed and examined an alternative path analysis model to overcome the negative effects in the presence of multicollinearity dilemma. The proposed model (sometimes called ridge path analysis) is considered a simple modified form of the normal path analysis model. The results revealed significant differences among the tested genotypes for all studied traits. Genotypes; 11, 12 and 5 surpassed the other genotypes for seed yield (ardab/fed). Significant and highly significant and positive associations were obtained between seed weight/plant and each of number of pods/plant and the weight of 100 seeds, respectively. Doing the ordinary path analysis model, highest values of Variance Inflation Factor VIF (above 10) were obtained for some yield components i.e. number of pods/plant, number of seeds/plant and number of seeds/pod indicating the presence of multicollinearity. Consequently, unstable path coefficients, undesirable high value of coefficient of determination (R2) and wrong sign for some path coefficients were resulted as negative effects of multicollinearity which is statistically enough to reject this model. More precise and valid results were obtained using the modified path analysis model because it can overcome the adverse effects of multicollinearity problem. The proposed model revealed that the traits of the weight of 100 seeds, number of seeds/plant and number of pods/plant exerted the greatest influence directly or indirectly upon seed weight/plant in faba bean indicating their importance as selection criteria to obtain a valuable gain of selection for seed yield in faba bean.
|
| Publication year |
2012
|
| Pages |
107 – 119
|
| Organization Name |
Central Laboratory for Design and Statistical Analysis Research (CLDSAR)
|
| Author(s) from ARC |
|
| External authors (outside ARC) |
خالد محمد محمد يمانى
قسم بحوث المحاصيل البقولية - معهد بحوث المحاصيل الحقلية
عزام عبد الرازق محمد عشرى
قسم بحوث المحاصيل البقولية - معهد بحوث المحاصيل الحقلية
ايهاب حلمى الحارتى
قسم بحوث المحاصيل البقولية - معهد بحوث المحاصيل الحقلية
|
| Publication Type |
Researsh & Applied Activities
|