高光谱成像
近红外光谱
残留物(化学)
化学
二氧化硫
主成分分析
分光计
红外线的
化学成像
支持向量机
分析化学(期刊)
色谱法
人工智能
光学
计算机科学
生物化学
有机化学
物理
作者
Xiulin Bai,Qinlin Xiao,Lei Zhou,Yu Tang,Yong He
出处
期刊:Molecules
[Multidisciplinary Digital Publishing Institute]
日期:2020-04-03
卷期号:25 (7): 1651-1651
被引量:26
标识
DOI:10.3390/molecules25071651
摘要
Sodium pyrosulfite is a browning inhibitor used for the storage of fresh-cut potato slices. Excessive use of sodium pyrosulfite can lead to sulfur dioxide residue, which is harmful for the human body. The sulfur dioxide residue on the surface of fresh-cut potato slices immersed in different concentrations of sodium pyrosulfite solution was classified by near-infrared hyperspectral imaging (NIR-HSI) system and portable near-infrared (NIR) spectrometer. Principal component analysis was used to analyze the object-wise spectra, and support vector machine (SVM) model was established. The classification accuracy of calibration set and prediction set were 98.75% and 95%, respectively. Savitzky-Golay algorithm was used to recognize the important wavelengths, and SVM model was established based on the recognized important wavelengths. The final classification accuracy was slightly less than that based on the full spectra. In addition, the pixel-wise spectra extracted from NIR-HSI system could realize the visualization of different samples, and intuitively reflect the differences among the samples. The results showed that it was feasible to classify the sulfur dioxide residue on the surface of fresh-cut potato slices immersed in different concentration of sodium pyrosulfite solution by NIR spectra. It provided an alternative method for the detection of sulfur dioxide residue on the surface of fresh-cut potato slices.
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