杭白菊是重要的可食用中药，因其主要活性成份为木犀草素，其具有自由基清除和抗氧化性能，可改善健康。研究人员利用多光谱成像法进行了杭白菊栽培种区分和木犀草素含量测定的研究。支持向量机法（ (LS-SVM)）用来区分杭白菊栽培种。从样品获得的光谱学和形态学特征数据用做前三个主要成份（99.61%）， LS-SVM模型在预测集的区分精度可达98%。另外，偏小二乘法PLS和 LS-SVM 用于预测木犀草素含量，预测结果Rp分别为 0.949和0.965； RMSEP 分别为0.387和0.314 mg g−1。所有结果显示，将MSI多光谱成像技术与化学计量法结合的方法，可能是一种快速、无损区分杭白菊栽培种和测定木犀草素含量的有效方法。该文章利用了VideometerLab 多光谱测量系统进行了研究。
   Chrysanthemum morifolium Ramat. (Chr) is a notable medicinal and edible crop that stimulates health owing to its radical-scavenging and antioxidant properties due to its main active flavonoid luteolin. The performance of discriminating between Chr c*rs and determining luteolin content in Chr using multispectral imaging (MSI) was investigated. A combination of MSI with principal component analysis (PCA) and least squares-support vector machines (LS-SVM) was applied to classify Chr c*rs. PCA derived from the spectral and morphological features data of the samples explained 99.61% for summing up the first three principal components and the LS-SVM model achieved 98% discrimination accuracy in the prediction set. Additionally, partial least squares (PLS) and LS-SVM models were obtained to predict performance for luteolin content determination, with Rp of 0.949 and 0.965, and RMSEP of 0.387 and 0.314 mg g−1, respectively. All results demonstrated that the combination of MSI system with chemometrics methods could be a rapid and non-destructive method to discriminate between Chr c*rs and determine luteolin content in Chr.