Method for Rapid Determination of Hexeneuronic Acid in Non‐Wood Pulp by Multivariate Analysis of FT‐NIR Spectroscopic Data

In the chlorine dioxide bleaching stage of elemental chlorine‐free (ECF) chemical pulp production, hexeneuronic acid (HexA) in the brown stock contributes to the kappa number and consumes chlorine dioxide. This study aims to develop a feasible, environmentally friendly, and rapid method for quantifying HexA content in non‐wood pulp using FT‐NIR spectroscopy combined with chemometric modeling. The HexA levels were measured in 44 non‐wood pulp samples to validate the approach. The same samples were analyzed using FT‐NIR spectroscopy, and the obtained spectral data were preprocessed using Savitzky–Golay (S–G) smoothing followed by first and second derivatives, a common approach in chemometric analysis. Principal component regression (PCR) and partial least squares regression (PLSR) were evaluated for HexA quantification using both raw and pretreated FT‐NIR spectra. The PLSR model demonstrated superior predictive performance ( R 2 = 94.24%) when applied to FT‐NIR data preprocessed with Savitzky–Golay filtering, derivatives, and leverage correction. Finally, the validated model exhibited excellent accuracy in predicting HexA content in unknown non‐wood pulp samples, achieving a high correlation coefficient ( r = 0.993).