利用多光譜成像系統區分杭白菊栽培種和測定木犀草素含量

    杭白菊是重要的可食用中藥，因其主要活性成份為木犀草素，其具有自由基清除和抗氧化性能，可改善健康。研究人員利用多光譜成像法進行了杭白菊栽培種區分和木犀草素含量測定的研究。支持向量機法（ (LS-SVM)）用來區分杭白菊栽培種。從樣品獲得的光譜學和形態學特征數據用做前三個主要成份（99.61%）， LS-SVM模型在預測集的區分精度可達98%。另外，偏小二乘法PLS和 LS-SVM 用于預測木犀草素含量，預測結果Rp分別為 0.949和0.965； RMSEP 分別為0.387和0.314 mg g−1。所有結果顯示，將MSI多光譜成像技術與化學計量法結合的方法，可能是一種快速、無損區分杭白菊栽培種和測定木犀草素含量的有效方法。該文章利用了VideometerLab 多光譜測量系統進行了研究。
   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.