| Issue |
BIO Web Conf.
Volume 223, 2026
The 3rd International Conference on Food Technology and Nutrition (ICFTN 2025)
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 7 | |
| Section | Food Chemistry and Functional Food | |
| DOI | https://doi.org/10.1051/bioconf/202622304002 | |
| Published online | 25 February 2026 | |
Multiplicative Scatter Correction Improves Near-Infrared Spectroscopy–Based PLS Models for Acetic Acid Quantification in Jamblang Vinegar
1 Department of Agricultural Product Technology, Universitas Teuku Umar, 23681 Aceh Barat, Indonesia
2 Department of Food and Agricultural Product Technology, Universitas Syiah Kuala, 23111 Banda Aceh, Indonesia
3 Department of Agricultural Engineering, Universitas Syiah Kuala, 23111 Banda Aceh, Indonesia
4 Research Organization for Environmental and Life Sciences, Research Centre for Applied Botany, National Agency for Research and Innovation, 16911 Cibinong, Indonesia
5 Department of Biology Education, Universitas Syiah Kuala, 23111 Banda Aceh, Indonesia
6 Halal Research Centre, Universitas Syiah Kuala, 23111 Banda Aceh, Indonesia
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
† Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
Jamblang (Syzygium cumini L.) vinegar is a potential functional fermented product that requires rapid and reliable quality assessment. This study developed a near-infrared spectroscopy (NIRS)-based method combined with partial least squares regression (PLSR) to quantify acetic acid content in jamblang vinegar. Vinegar samples representing a wide range of acetic acid concentrations were obtained through varied fermentation conditions and analyzed using a reference enzymatic method. NIR spectra were preprocessed using Multiplicative Scatter Correction (MSC) to reduce scattering effects caused by sample heterogeneity. PLSR models constructed from MSC-treated spectra showed improved predictive performance compared with uncorrected spectra, achieving a coefficient of determination (R2) of 0.995 and a residual predictive deviation greater than 2.3. Regression coefficient analysis identified wavelength regions associated with O–H and C–H overtone vibrations as key contributors to acetic acid prediction. The results demonstrate that NIRS coupled with MSC-enhanced PLSR provides a rapid, non-destructive, and accurate approach for acetic acid determination in jamblang vinegar, supporting its application for routine quality control and fermentation monitoring.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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