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Author ORCID Identifier


Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Food Science

Year Degree Awarded


Month Degree Awarded


First Advisor

Xin Guo

Subject Categories

Food Chemistry


Microplastic pollution has emerged as a global concern in both aquatic and terrestrial environments. The presence of microplastics in the food chain poses a potential threat to human health. To accurately assess the risks associated with microplastics, it is crucial to have a reliable analytical technique capable of detecting, quantifying, and identifying microplastics of varying materials, sizes, and shapes in environmental, agricultural, and food samples. Spectroscopic techniques, specifically vibrational spectroscopy (Raman and Infrared), are extensively utilized in microplastic analysis. These techniques enable rapid and high-throughput identification, while also providing size and shape information. However, there are certain gaps in the current knowledge micro(nano)plastic pollution in food related appplication. These gaps can be attributed, in part, to the lack of available testing methods. Herein, the goal of this project is to develop easy and cost-effective methods for the micro(nano)plastic identification and quantification by Raman microscopy. To achiece this goal, we initially investigated the analytical capabilities of the conventional methods used in the field of micro(nano)plastics through the utilization of Raman microscopy to quantify microplastics in polyethylene terephthalate (PET) bottled edible oil. The conventional method consists of three steps: (i) destruction of the food matrix through sample digestion, (ii) filtration or separation of the particles, and (iii) detection, quantification, and characterization of microplastics. In this method, filters were directly scanned under the Raman lens. Due to the large area of the filter membrane, only a representative fraction was selected for scanning to save time. For microplastic recovery from oil, hexane was used to dilute the oil and facilitate the filtration process, resulting in the recovery of 63% to 118% of microplastics using standard polystyrene particles. The results showed that particles ranging from 1.34×105 to 5.80×105 per liter of oil were detected in four commercial edible oils (olive oil, canola oil, sunflower oil, and coconut oil). Over 80% of the detected plastics were smaller than 10 μm. To better understand the capability of Raman microscopy for micro(nano) plastics migrated from food packages, we conducted an experiment using the conventional method to to determine the quantity and size distribution of microplastics migrating from various water and food plastic containers following the US Food and Drug Administration (FDA)'s guidance using Raman microscopy. Six commonly used water and food containers made of polypropylene (PP), polyethylene terephthalate (PET), and polystyrene (PS) were treated using distilled water and food stimulants (10% and 50% ethanol) under various conditions. Following the FDA guidelines, a range of 2.37×105 to 4.90×105 particles per liter of microplastics with 77-92% smaller than 5 µm were detected. The temperature and ethanol percentage were key attributes for elevating microplastic migration. Direct microwave heating led to a significantly higher release of microplastics, with a concentration of 5.34×105 particles per liter compared to the FDA-suggested method (1.56×105 particles per liter). Through these two studies, we found the majority of the particles detected in oil and released from food packages were smaller than 10 µm, which highlights the signfiicance of developing Raman microscopic methods for analyzing microplastics in food, as IR spectroscopy is not capable of approaching the size smaller than 10 µm. However, we identified some significant limitations of the conventional Raman microscopic methods. Firstly, the detection of particles is based on visual inspection on the filter membrane under the microsocpe which is time consuming, labor-intenstive, and subjective. Secondly, the identification rate was low, e,g. 48%–95% of microplasticsin the first study, 12%–63% of the microplastics in the second study, which could be attributed to their small particle size. To overcome the current limitations of the conventional method, the third study was aimed to develop novel methods that improved the time and labor efficiency, and increase the detection and identification confidence and sucessful rate. The first method involved the development of an automated approach to quantify microplastics using a gold-coated glass chip. The utilization of the gold-coated glass chip enables the detection of extremely small structures or the capture of extremely weak signals. For quantification, the ImageJ software was employed, which automatically counted the microplastics, significantly reducing the required time. Despite marginally lower recovery rates (61% to 99%), the gold chip-based method demonstrated significant advantages in time efficiency and reliability, reducing the processing time from 60 to 10 minutes per sample and expanding the representative area from 0.377% to 8.493%. The practicality of the new method was evaluated through its application to quantification of microplastics released from PS cups. The results revealed that the PS cup packaging generated a total of 6.44×105 particles per liter of PS microplastics, with 74% of the particles being smaller than 10 μm. The identification rate for the released particles was found to be 41%. These findings validate the effectiveness of the method and highlight the health concerns associated with the substantial presence of microplastics in everyday items. A comparison with the results of the conventional method further supports this conclusion. The second method aimed to overcome the size limitations for detection and identification of nanoplastics. In this experiment, we investigated the impact of acetone on nanoplastic size and its detectability using Raman spectroscopy. Notably, nanoplastics with initial sizes of 100 nm, 500 nm, and 200 nm exhibited a significant expansion in diameter to 1890 nm, 920 nm, and 540 nm, respectively, particularly under higher temperature conditions (50°C). This enlargement in diameter resulted in improved detectability. While the intensity of the Raman signal varied depending on the nanoplastic size and temperature conditions, the larger sizes facilitated by acetone dissolution exhibited an enhanced Raman signal. Specifically, the Raman signal intensity of 200-nm nanoplastics increased from 0 to 1359 a.u., making nanoplastics easier to identify. The optimized conditions for the method included a 4-hour incubation with acetone at 50°C, which were applied to released micro(nano)plastics from PS cups. The results supported the capability of acetone in enhancing the visual detection and identification rate of PS particles, increasing it from 68% to 93%. To further improve the detection capability of Raman microscopy for micro(nano)plastics, we combined the first method (gold chip-based method) and the second method (acetone-based method) together to develop an easy and reliable automatic method for detecting micro(nano)plastics in real environmental samples. By optimizing the experimental processing steps (microscope lens: 20×, drop numbers: 1, acetone wash times: 2, drying to 100 μL), we achieved a final recovery rate of 96.93% and an identification rate of 85% for the analysis of released microplastics. Finally, we explore the use of Surface-Enhanced Raman Spectroscopy (SERS), an intergration between Raman spectroscopy for molecular fingerprinting and nanotechnology for signal enhancement. to analyze. The result demonstrated the feasbility of SERS to chemically detect actone disolved nanoplastics. Overall, these dissertation results will offer new approaches and insights into micro(nano)plastic analysis, contributing to a better understanding of micro(nano) plastic exposure.