TY - JOUR JF - JCPP JO - VL - 12 IS - 46 PY - 2009 Y1 - 2009/1/01 TI - Detection of Traits Affecting Potato Yield under Drought Stress and Non-Stress Conditions by Multivariate Analyses TT - شناسایی صفات مؤثر بر عملکرد سیب‌زمینی با استفاده از روش‌های آماری چند متغیره در شرایط تنش و عدم تنش خشکی N2 - Factor and principal component analyses are widely used in different sciences especially in agricultural science. To determine the factors that create variation between potato cultivars, in normal (non-stress) and water deficit (stress) conditions, two experiments were conducted in the form of randomized complete block design with three replications in summer 2002. Stepwise regression analysis showed that in normal conditions, stem length, number of stems/plant and leaflet width contributed significantly to yield. In stress condition, other than stem length and number of leaves/main stem, leaflet length also entered the model. As is evident, stem length had a detrimental effect on tuber yield in both stress and non-stress conditions. So, this trait could be used as an important criterion for the selection of high yielding genotypes. Principal component analysis revealed that number of stem, leaf length and leaf width were important traits creating variability between potato cultivars, especially number of stem that had high coefficients in the first principal for both environments. Factor analysis distinguished two factors in normal environment named leaf surface and structural attitude factors, and also two factors in stress environment called photosynthetic surface and structural attitude. Therefore, these factors should be intervened and attended to in breeding programs. SP - 131 EP - 140 AU - Rabiei, K AU - KHodambashi, M AU - Rezaei, A AD - KW - Factor Analysis KW - Principal component analysis KW - Stepwise regression KW - Potato. UR - http://jcpp.iut.ac.ir/article-1-1113-en.html ER -