# Quantification of Microplastics in Plastic-Bottled Chinese Baijiu Using Micro-FTIR in Imaging Mode
## 3 Results
### Validation and Data Analysis of Plastic-Bottled Chinese Baijiu Using Micro-FTIR  
The FPA detector coupling allows for the entire filter area to be imaged, in contrast to single-point measurements. This method of analysis has the added advantage of collecting both spectral and spatial information of multiple particles simultaneously through automated mapping of a sample, enabling the analysis of small microplastics without the manual sorting and estimation of particles' characteristics such as their areas and diameters. The infrared spectrometer exhibits a superior spectral resolution of over 0.1 cm\({}^{-1}\) in the mid-infrared region and over 1 cm\({}^{-1}\) at a wavelength of 1000 nm in the near-infrared region. The equipment achieved a spatial resolution detection limit of 25 \(\upmu\)m.  
Statistical analysis was performed using MATLAB R2014a. This technique was pioneered by [PERSON] in \"Micoplastic Characterisation by Infrared Spectroscopy\", found in the _Handbook of Microplastics in the Environment_, pp. 1-33, 2020 [21]. The authors provide an extensive account of the multiple approaches employed to analyze microplastics utilizing infrared spectroscopy. Specifically, the implementation of spectral imaging techniques along with spectral auto-analysis techniques can significantly enhance the efficacy of microplastic spectral analysis. MATLAB scripts and datasets are also provided in the book.  
Figure 4: Microplastic size distribution in Chinese baijiu.  
FTIR spectra of unknown species are typically identified by comparing their recorded spectra with those in a library of known substances. The Pearson correlation coefficient (r) is a method that has been suggested in determining the similarity between spectra [22]. To enhance the accuracy and robustness of library searching, a curve-fitting approach has been developed. This approach calculates a match by using the most relevant bands instead of the entire spectrum for identification [23; 24; 25]. By utilizing this robust identification method, MP identification accuracy can be increased from 60% to 98% compared to traditional library searching [26]. It is crucial to develop, validate, and improve automated analysis methods to reduce the identification time and enhance the accuracy and robustness of the complete analytical chain.  
Taking the results of the Red Star Erguotou Liquor sample as a representative, Figure 6 displays the various types of plastic components, which are represented by the distinctive peaks observed in the micro-FTIR spectra. Using a Pearson correlation coefficient threshold of 0.7, our study identified the following five components in the plastic bottle of the Red Star Erguotou Liquor sample: cellulose, PET, PU, PA, and PVC, which were found at levels of 24, 72, 5, 16, and 1 microplastics, respectively.  
The spectra's characteristic peaks provided useful identification information. For instance, characteristic peaks for PA were given in Figure 7, whereby 1635 cm\({}^{-1}\) peaks correspond to carbonyl group absorption peaks (v C=O). Furthermore, the 1537 cm\({}^{-1}\), 1264 cm\({}^{-1}\), and 1170 cm\({}^{-1}\) peaks correspond to vibration absorption peaks (v C-N and v C-O).  
The spectra evidenced degradation of the plastic particles, attributable to alcoholic beverage exposure. This indicates that the environment can influence the chemical composition and structural integrity of microplastics present. In general, the micro-FTIR analysis provided valuable information about the chemical composition and potential degradation of microplastic particles in the Red Star Erguotou Liquor sample.  
Figure 5: Distribution of types of microplastics in various brands of plastic-bottled Chinese baijiu.  
Figure 6: Microplastic abundance in the sample (quarter part).  
Figure 7: The FTIR spectra of typical microplastic particle samples within the range of 700–2000 cm\({}^{-1}\).