期刊
VIBRATIONAL SPECTROSCOPY
卷 110, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.vibspec.2020.103129
关键词
Palm oil; Integrity; Sudan 1V dye; Handheld spectroscopy; Multivariate technique
资金
- Institute for Global Food Safety of Queen's University Belfast, UK
- School of Agriculture, University of Cape Coast, Cape Coast, Ghana
Shortwave handheld NIR spectroscopy coupled with multivariate algorithm was attempted to simultaneously classify and measure Sudan IV dye adulteration in palm oil samples. K-nearest neighbour (KNN) was used to develop a classification model to discriminate between authentic palm oil samples and Sudan IV dye adulterated (0.10-0.002 % w/w) ones. Principal component regression (PCR), partial least square regression (PLSR) and support vector machine regression (SVMR) algorithms were comparatively employed to quantify the addition of Sudan IV dye in authentic palm oil samples. The models were evaluated by the classification rate (R), correlation co-efficient in the calibration set/prediction set (Rp(2)/Rc(2)), and root mean square error of calibration/prediction (RMSEC/P). The developed multiplicative scatter correction plus KNN technique was found to accurately classify where R = 95.48 % and 97.00 % in the calibration set and prediction set respectively. Among the quantification model developed for measuring Sudan IV dye, standard normal variant preprocessing plus partial least square regression (SNV-PLSR) gave the best performance at Rc(2) = 0.91, Rp(2) = 0.90 and RMSEC = 0.0841, RMSEP = 0.0868 while standard normal variant preprocessing plus principal component regression gave Rc(2) = 0.90, Rp2 = 0.90 and RMSEC = 0.0846, RMSEP = 0.870. The findings have proved that, the integrity of palm oil samples can be certified rapidly and nondestructively in terms of the presence of Sudan IV by using short wave handheld NIR spectroscopy. This offers the opportunity for incorporating NIR spectroscopy into mobile phone devices to enhance mobile detection.
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