Microplastic pollution in aquatic environment has raised concern and as a result a number of studies have recently been published to find solutions for its rapid increase. Different methods have been proposed for microplastic identification. Spectral imaging shows a lot of promise for polymer identification; however, the identification time needs to be improved. Hyperspectral imaging (HSI) combined with chemometric analysis can reduce the identification times. In this study, we provide a review of recent studies related to polymer identification using HSI with a focus on the adopted classification algorithm and its factors for the online implementation of HSI. Furthermore, we review the limit of detection by HSI and the effect of particle size on classification accuracy. Additionally, performance of this method for various types of samples is also discussed. We conclude that HSI is possible to be a fast alternative for online microplastic detection.

水生环境中的微塑料污染引起了人们的关注，因此最近发表了许多研究，以寻找其快速增加的解决方案。已经提出了不同的方法来识别微塑料。光谱成像显示了聚合物鉴定的许多前景；但是，识别时间需要改进。高光谱成像 (HSI) 结合化学计量分析可以减少识别时间。在这项研究中，我们回顾了最近与使用 HSI 进行聚合物识别相关的研究，重点是所采用的分类算法及其在线实施 HSI 的因素。此外，我们回顾了 HSI 的检测限以及粒度对分类精度的影响。此外，还讨论了该方法对各种类型样品的性能。我们得出结论，HSI 有可能成为在线微塑料检测的快速替代方案。