Study on Discriminant Analysis of Photosensitive Ink

Abstract Background: Photosensitive inks are extensively employed in diverse industrial applications; however, rapid and non-destructive discrimination between ink types remains a persistent technical challenge. Conventional methods often lack the efficiency or precision required to differentiate inks from varying manufacturers and models. Aims and Objectives: This study aimed to evaluate the feasibility of integrating microspectrophotometry with chemometric analysis for non-destructive discrimination of photosensitive inks, addressing the need for accurate and rapid identification in practical scenarios. Materials and Methods: Spectral data within the 400–800 nm wavelength range were non-destructively collected from 50 photosensitive ink samples, representing diverse manufacturers and models, using MSP. The acquired spectral dataset was analyzed via principal component analysis (PCA), a chemometric technique, to assess its discriminative capacity. Results: PCA achieved a pairwise discrimination power of 99.67% across the 50 ink samples, as visualized through load scatter plots. This result underscores the method’s robustness in detecting subtle spectral variations arising from compositional differences among inks. Conclusion: The combination of MSP and PCA provides an efficient, non-destructive strategy for distinguishing photosensitive inks with high precision. This approach holds substantial promise for applications in forensic investigations, industrial quality control, and authentication processes requiring rapid and reliable ink differentiation.