Discrimination of Varieties of Sugar Based on Partial Least Squares and Fuzzy Clustering Methods
近红外光谱技术与偏最小二乘法及模糊聚类法相结合的糖品种分类方法

A new method which combines Partial Least Squares (PLS) with a near infrared spectroscopy is proposed for the nondestructive discrimination of the varieties of sugar. A near infrared spectrometer is used to obtain the diffusion spectral characteristic curves from the samples of white granulated sugar, xylitol, maltose and glucose. Then, the PLS is used to derive the variety and characteristic values of the sugar. The derived eleven main components which are normalized are used as the parameters for establishing a fuzzy clustering model. By setting four clusters, the fuzzy clustering model is established and is used to predict forty unknown sugar samples. The prediction accuracy is up to 100 %. This shows that the new method has a good ability to fast discriminate the variety of sugar.