Determination of Water Content in Vanilla Pods and Powder Using Near-Infrared Spectroscopy

The quality of vanilla depends heavily on its water content, a key parameter that influences its stability, preservation, and sensory properties. Conventional moisture determination by loss-on-drying, while accurate, is slow and destructive. In this study, a rapid, non-destructive approach based on near-infrared (NIR) spectroscopy combined with chemometric modeling was developed to predict the moisture content of vanilla samples. A total of 123 samples were analyzed by NIR spectroscopy and thermogravimetric analysis (reference values). Principal component analysis revealed a strong correlation between spectral variance and water content in the 7400- 4000 cm⁻¹ region. A partial least squares (PLS) regression model was optimized and validated, showing optimal performance with four latent variables (R² = 0.99, RMSEC = 0.98). Prediction on an independent set of 20 samples yielded a Q² of 0.99 and an RMSEP of 0.82, confirming the robustness and generalization of the model. Repeatability tests further demonstrated high stability and low variability of the predicted values. The method demonstrates strong potential for routine industrial quality control. Expanding the calibration set could support broader applicability across vanilla varieties