title: [Study on varieties identification of Kentucky bluegrass using hyperspectral imaging and discriminant analysis].
abstract: Hyperspectral images of six varieties of Kentucky bluegrass were acquired using hyperspectral imager (550-1 000 nm) and the leaf spectral properties were extracted. Wilks' lambda stepwise method was used and 9 optimal wavelengths were selected from the original 94 wavelengths and the discriminant models for varieties identification of Kentucky bluegrass were built based on Fisher' s linear discriminant function. The results showed that the Fisher' s linear discriminant model with 9 wavelengths achieved classification accuracies of 100% for both training and testing samples. While for the models with three wavelengths and six wavelengths, classification accuracies reached 83.3% and 96.7% for the testing samples, respectively. It indicates that hyperspectral images combined with discriminant analysis might be a good method to identify the varieties of Kentucky bluegrass.
authors.affiliation: Institute of Turfgrass Science, Beijing Forestry University, Beijing 100083, China. xiaobo3000@126.com
authors.forename: Bo
authors.initials: B
authors.lastname: Xiao
authors.forename: Wen-Hua
authors.initials: WH
authors.lastname: Mao
authors.forename: Xiao-Hong
authors.initials: XH
authors.lastname: Liang
authors.forename: Li-Juan
authors.initials: LJ
authors.lastname: Zhang
authors.forename: Lie-Bao
authors.initials: LB
authors.lastname: Han
mesh_terms: D016002:Discriminant Analysis; D008962:Models, Theoretical; D031785:Poa / Q000145:classification*; D019265:Spectroscopy, Near-Infrared