化学计量学
主成分分析
偏最小二乘回归
线性判别分析
傅里叶变换红外光谱
数学
模式识别(心理学)
人工智能
分析化学(期刊)
多元统计
统计
计算机科学
化学
色谱法
物理
光学
作者
Chrysanthi Christou,Agapios Agapiou,Rebecca Kokkinofta
标识
DOI:10.1016/j.jare.2017.12.001
摘要
Carob samples from seven different Mediterranean countries (Cyprus, Greece, Italy, Spain, Turkey, Jordan and Palestine) were analyzed using Fourier Transform Infrared (FTIR) spectroscopy. Seed and flesh samples of indigenous and foreign cultivars, both authentic and commercial, were examined. The spectra were recorded in transmittance mode from KBr pellets. The data were compressed and further processed statistically using multivariate chemometric techniques, including Principal Component Analysis (PCA), Cluster Analysis (CA), Partial Least Squares (PLS) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Specifically, unsupervised PCA framed the importance of the variety of carobs, while supervised analysis highlighted the contribution of the geographical origin. Best classification models were achieved with PLS regression on first derivative spectra, giving an overall correct classification. Thus, the applied methodology enabled the differentiation of carobs flesh and seed per their origin. Our results appear to suggest that this method is a rapid and powerful tool for the successful discrimination of carobs origin and type.
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