Abstract
Portable NIR spectrometers was used for the identification of six kinds of food-contacted plastic material including polyethylene terephthalate (PET), high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyvinyl chloride (PVC), polystyrene (PS) and polycarbonate (PC). Four kinds of spectral preprocessing methods including 5-point smoothing, multivariate scattering correction (MSC), first-order derivative and standard normal variable transformation (SNV) were used to preprocess the spectra of plastic samples. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to analyze the spectral space distribution of plastic samples and establish qualitative discriminant models. The results showed that six kinds of food-contacted plastic material could be clearly separated in the first three principal component spaces after the pretreatment of SNV and MSC methods. The PLS-DA combined with SNV could be used to get a concise plastic material qualitative discriminant model, and the correct recognition rates (CRR) were 100% both for calibration and prediction datasets. The method was expected to be a reference method for rapid identification of food-contacted plastic materials.
Publication Date
4-28-2018
First Page
124
Last Page
127
DOI
10.13652/j.issn.1003-5788.2018.04.025
Recommended Citation
Yong, HAO; Qinhua, WEN; Min, RAO; and Bin, CHEN
(2018)
"Research on plastic material identification based on portable near infrared spectrometer,"
Food and Machinery: Vol. 34:
Iss.
4, Article 25.
DOI: 10.13652/j.issn.1003-5788.2018.04.025
Available at:
https://www.ifoodmm.cn/journal/vol34/iss4/25
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