Payal Ketan Kholiya, Smita Bonde, Varad Gore, Shivang Kahar
ABSTRACT Quality assessment in herbal medicine is challenging due to risks of contamination, adulteration, and variability in active constituents. The absence of universal reference standards further contributes to inconsistent efficacy and safety. Current quality control methods often overlook issues, such as heavy metals, microbial load, and intentional adulteration. Regulatory differences across regions and the limited application of AI and machine learning add to the complexity. Moreover, a clear correlation between chemical fingerprints and pharmacological activity is still lacking. To address these challenges, wavelength fusion fingerprinting (WFF) emerges as a promising innovation. It involves integrating spectral data from multiple wavelength ranges, such as ultraviolet (UV), visible, near‐infrared (IR), and far‐IR, to capture the unique absorption, reflection, and emission characteristics of herbal constituents across different spectral bands. By combining these complementary datasets, WFF offers a more holistic and accurate representation of the chemical composition of herbal products. Given the phytochemical diversity and the lack of standardized markers in herbal formulations, revisiting and integrating techniques like WFF into quality evaluation protocols is essential. This review aims to present an updated and comprehensive overview of recent advances and technological innovations in WFF, with a particular focus on its applications in the quality assessment of herbal medicines.