Multivariate Discrimination of Some Grapevine Cultivars under Drought Stress in Iran

Abstract

Grapevine is one of the most important economic crops in horticulture, and drought stress is one of the most significant threatening factors in the world. Therefore, the identification and investigation of cultivars under drought stress are the basic steps and important goals in grapevine-breeding programs. In the present study, the 17 parameters of 14 grapevine cultivars under drought stress were first scaled. Based on the initial information, we divided the 14 grape cultivars according to their resistance to drought stress into four groups: tolerant, semi-tolerant, semi-sensitive, and sensitive. Then, the utilization of multivariate techniques comprising principal component analysis (PCA), along with quadratic discriminant analysis (QDA), were utilized to choose the most substantial and accountable traits for the four groups’ discrimination. For the QDA, the 17 parameters were arranged into four sets. The discrimination for all parameters showed 96% correct classification. The first set includes shoot length (Shoot L), shoot number (Shoot N), leaf area (Leaf A), relative water content (RWC), and chlorophyll a (Chl a) parameters that showed 71.5% correct classification. The second set includes chlorophyll b (Chl b), chlorophyll total, peroxidase (POX), and superoxide dismutase (Sod) parameters that had 75% correct classification. Electrolyte leakage (EL), malondialdehyde (MDA), proline, catalase (CAT), and ascorbate peroxidase (APX) parameters were in the third set and had 87% correct discrimination. The best discrimination was obtained by the combination of the first and third set, including the Shoot L, Shoot N, Leaf A, RWC, Chl a, EL, MDA, proline, CAT, and APX with 100% correct discrimination.