Hyperspectral imaging as an emerging tool to analyze microplastics: A systematic review and recommendations for future development

Microplastics and Nanoplastics

Table 4 Overview of common conclusions in the literature review

Conclusions	Source
Water reduces spectral reflectance, drying of particles is important	[61, 64]
SVM model outperforms PLS-DA, ML	[60, 64]
Dark particles are harder to detect	[60, 65]
ID of smaller particles is hindered by spatial resolution	[56, 60, 61, 64]
Weathered polymers have degraded spectra as compared with pristine polymers	[55, 62]
Reference polymers should be more diverse, include weathering and polymer mixtures	[65]
Over 90% of particles > 1 mm positively identified	[58, 60]
Addition of extra “class” for background or non-polymer material helped classification	[56, 59, 60]
Glass fiber filter is a suitable background material	[54,55,56,57, 64, 65]