EVALUATION OF DISCRIMINANT-ANALYSIS IN IDENTIFICATION OF LOW-WATER AND HIGH-WATER USE KENTUCKY BLUEGRASS CULTIVARS

Identification of water conserving Kentucky bluegrass (Pen pratensis L ., KEG) is an important objective in turfgrass breeding programs. Warm -season turfgrass selections with low evapotranspiration (ET) rates ha ve been successfully identified by components of canopy resistance to ET and leaf area. The objective of this study was to determine the eff ectiveness of discriminant analysis in distinguishing water conserving KEG on the basis of canopy resistance and leaf area from a population of 61 KEG cultivars. By means of cluster analysis, the 61 KEG cultiva rs were categorized as either low-or high-water use cases based on ET rate evaluated in the growth chamber at three VPD environments (1.263, 1.664, and 2.261 kPa). Fourteen morphological and growth characterist ics were assessed in the greenhouse with unmowed, spaced plants and mo wed turfgrass (2O-cm-diam. lysimeters), Eased on single plant morpholo gy, five-and seven-variable discriminant functions were identified tha t correctly classified eases into their actual water use groups with a n estimated 70.5% actual error rate from cross-validation with the lea ve-one-out method (LOER), Compared with single plant morphology, turfg rass morphology was more efficient in requiring fewer predictors (henc e fewer measurements) to perform classification. Based on turfgrass mo rphology, two-and three-variable functions were identified that correc tly classified an estimated 75.4% of the cases into their true water u se groups. A 75.4% correct classification was the best achieved and wa s as good as that obtained with all 14 original variables in the analy sis simultaneously. Leaf angle, a component of canopy resistance, was the most important discriminator of water use group, predicting actual group membership in 72.1% of the cases. Correct classification was im proved only slightly over leaf angle alone by incorporating a single l eaf area component such as leaf width or leaf extension rate, These re sults show that discriminant analysis may be an efficient and useful t ool for predicting the water use patterns of new cultivars on the basi s of a few plant measurements that are routinely assessed by breeders.