Near-infrared spectroscopy coupled with chemometrics for content determination of Ganoderma lucidum extract in chewable gels

Abstract

Near-infrared (NIR) spectroscopy, coupled with chemometric techniques, has seen increased use in complex formulations; however, its implementation in semi-solid dosage forms containing multicomponent natural extracts remains limited. Chewable gels represent a particularly challenging case, as their structural heterogeneity, high water content, and strong light-scattering effects render spectral responses highly sensitive to measurement conditions. The feasibility of applying NIR spectroscopy for quantitative content determination in chewable gels was investigated, with emphasis on the systematic evaluation and control of sources of spectral variability. Gelatinbased chewable gels containing a multicomponent Ganoderma lucidum extract (250–750 mg per unit) were used as a model system. The effects of sample handling, applied pressure at the measurement interface, and the use of an opaque cover on NIR spectral profiles were assessed using Principal Component Analysis and PERMANOVA across different spectral regions and preprocessing strategies. Sample handling conditions introduced statistically significant spectral variability, mainly affecting the first-overtone C–H stretching region (9000–7000 cm− 1 ). The combination of an opaque cover and slight pressure, together with Standard Normal Variate preprocessing, minimized non-chemical variability and improved dose discrimination. Under optimized acquisition and preprocessing conditions, Partial Least Squares regression models demonstrated excellent predictive performance (R2 val = 0.977, RPD = 6.9, RSEP = 4.1%) and high precision (RSD < 2.1%). Prediction accuracy improved with matrix stabilization and remained robust for samples analyzed between 11 and 58 days after preparation. This study demonstrates that accurate quantitative analysis by NIR spectroscopy is achievable in chewable gels containing chemically heterogeneous analytes, provided that matrix-related sources of spectral variability are explicitly identified and controlled.