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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

更新時(shí)間:2018-06-12 點(diǎn)擊量:1581

    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(jìn)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(lái)區分杭白菊栽培種。從樣品獲得的光譜學(xué)和形態(tài)學(xué)特征數據用做前三個(gè)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(shù)與化學(xué)計量法結合的方法,可能是一種快速、無(wú)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(jìn)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.

 

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