# Rapid and Accurate Quantification Detection of BHT in Edible Oils Using Raman Spectroscopy Combined with Chemometric Models

**Authors:** Congli Mei, Shuai Lu, Xiaolin Zhou, Fanzhen Meng, Hui Jiang

PMC · DOI: 10.3390/foods15040730 · Foods · 2026-02-15

## TL;DR

This study uses Raman spectroscopy and chemometric models to quickly and accurately detect BHT in edible oils, showing promising results for quality control.

## Contribution

The study introduces an optimized PLS model using CARS for high-precision BHT quantification in edible oils.

## Key findings

- The PLS model optimized with CARS achieved an average RP2 of 0.9687 and RMSEP of 3.1211.
- Multiple variable selection methods identified features highly correlated with BHT content.
- Raman spectroscopy combined with chemometrics is feasible for rapid BHT screening in edible oils.

## Abstract

The chemical composition of vegetable cooking oils is a key parameter in determining the quality of their products. Antioxidants are widely used in these products to extend their shelf life. In this study, the concentration of butylated hydroxytoluene (BHT) in edible oil was quantitatively determined by Raman spectroscopy combined with chemometrics. Initially, Raman spectra of edible oil samples with varying concentrations of BHT were obtained. Subsequently, three variable selection methods were applied to the pre-processed spectra. Optimised characteristic wavelengths were then used to establish a Radial Basis Function (RBF) neural network and partial least squares (PLS) models. The impact of variable selection on feature wavelengths was evaluated for both models in both independent and combined cases. The results demonstrate that the features identified through multiple variable selection methods correlate highly with the BHT content and can be utilised to develop high-precision detection models. The findings indicate that the PLS model, optimised using competitive adaptive reweighting (CARS), achieved the best prediction performance, with an average RP2 of 0.9687, and RMSEP of 3.1211. These results demonstrate the feasibility of using Raman spectroscopy combined with chemometrics for the rapid screening of BHT in edible oils. While the current study focuses on a broad concentration range to validate the method’s linearity, further optimisation is required for trace-level detection to meet strict regulatory limits.

## Linked entities

- **Chemicals:** BHT (PubChem CID 31404)

## Full-text entities

- **Diseases:** BOSS (MESH:C562950), injury to (MESH:D014947)
- **Chemicals:** fatty acid (MESH:D005227), Oil (MESH:D009821), tocopherols (MESH:D024505), corn oil (MESH:D003314), peroxide (MESH:D010545), soybean oil (MESH:D013024), unsaturated fatty acids (MESH:D005231), CARS (-), hydroperoxides (MESH:D006861), TBHQ (MESH:C018855), lipid (MESH:D008055), BHA (MESH:D002083), essential fatty acids (MESH:D005228), oxygen (MESH:D010100), acid (MESH:D000143), BaA (MESH:C030935), BbF (MESH:C006703), BaP (MESH:D001564), fat (MESH:D005223), PAHs (MESH:D011084), vegetable oils (MESH:D010938), Chr (MESH:C031180), BHT (MESH:D002084)
- **Species:** Homo sapiens (human, species) [taxon 9606], Helianthus annuus (common sunflower, species) [taxon 4232], Glycine max (soybean, species) [taxon 3847], Arachis hypogaea (goober, species) [taxon 3818]
- **Mutations:** R5600X

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12940983/full.md

## References

34 references — full list in the complete paper: https://tomesphere.com/paper/PMC12940983/full.md

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Source: https://tomesphere.com/paper/PMC12940983