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Crop Science Abstract -

Evaluation of Discriminant Analysis in Identification of Low- and High-Water Use Kentucky Bluegrass Cultivars


This article in CS

  1. Vol. 38 No. 1, p. 152-157
    Received: Nov 3, 1995

    * Corresponding author(s):
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  1. J. S. Ebdon ,
  2. A. M. Petrovic and
  3. S. J. Schwager
  1. D ep. of Plant and Soil Sciences, 12F Stockbridge Hall, Univ. of Massachussets, Amherst, MA 01003
    D ep. of Floriculture and Ornamental Horticulture, Cornell Univ.
    B iometrics Unit and Statistics Center, Cornell Univ., Ithaca, NY 14853



Identification of water conserving Kentucky bluegrass (Poa pratensis L., KBG) is an important objective in turfgrass breeding programs. Warm-season turfgrass selections with low evapotranspiration (ET) rates have been successfully identified by components of canopy resistance to ET and leaf area. The objective of this study was to determine the effectiveness of discriminant analysis in distinguishing water conserving KBG on the basis of canopy resistance and leaf area from a population of 61 KBG cultivars. By means of cluster analysis, the 61 KBG cultivars 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 characteristics were assessed in the greenhouse with unmowed, spaced plants and mowed turfgrass (20-cm-diam. lysimeters). Based on single plant morphology, five- and seven-variable discriminant functions were identified that correctly classified cases into their actual water use groups with an estimated 70.5% actual error rate from cross-validation with the leave-one-out method (LOER). Compared with single plant morphology, turfgrass morphology was more efficient in requiring fewer predictors (hence fewer measurements) to perform classification. Based on turfgrass morphology, two and three-variable functions were identified that correctly classified an estimated 75.4% of the cases into their true water use groups. A 75.4% correct classification was the best achieved and was as good as that obtained with all 14 original variables in the analysis 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 improved only slightly over leaf angle alone by incorporating a single leaf area component such as leaf width or leaf extension rate. These results show that discriminant analysis may be an efficient and useful tool for predicting the water use patterns of new cultivars on the basis of a few plant measurements that are routinely assessed by breeders.

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