College of Food Science and Technology, Hunan Provincial Key Laboratory of Food Science and Biotechnology, Hunan Agricultural University, Changsha 410128, China.
Hunan Agricultural Product Processing Institute, Hunan Academy of Agricultural Sciences, Changsha 410128, China.
Sensors (Basel). 2020 Mar 12;20(6):1586. doi: 10.3390/s20061586.
Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment.
陈皮（CRP）在中国已被使用数百年，既是一种功能性食品，也是一种药材。然而，一些不法商人将一些短龄的陈皮伪装成老龄陈皮，以获取更高的利润。本研究建立了一种基于便携式近红外漫反射光谱（NIRS）结合适当化学计量学方法的快速无损鉴别不同陈化年限陈皮的方法。该方法无需破坏样品，直接获得不同贮藏年限陈皮的外果皮和内囊的光谱。采用主成分分析（PCA）结合单一和组合光谱预处理方法对不同陈化年限的陈皮进行分类。此外，对 PCA 方法进行数据预处理，并讨论了优化预处理方法的 Fisher 线性判别分析（FLD），以提高分类准确性。数据预处理方法可用于消除噪声和背景干扰。内囊数据的分类准确性优于外果皮数据。此外，即使不进行预处理，FLD 方法也可以获得最佳的 100%预测准确率的结果。
