[Qualitative detection of bottled vinegar based on NIR spectroscopy technique]

Area of Science:

• Analytical Chemistry
• Spectroscopy

Background:

• Non-invasive analysis of food products like vinegar is crucial for quality control.
• Near infrared (NIR) spectroscopy offers a rapid, non-destructive method for chemical analysis.
• Glass packaging can interfere with spectroscopic measurements, necessitating method optimization.

Purpose of the Study:

• To assess the feasibility of using NIR spectroscopy for detecting bottled vinegar.
• To investigate the impact of glass packaging on NIR spectral data.
• To develop a method for accurate qualitative analysis of bottled vinegar.

Main Methods:

• Transmission spectra of bottled vinegar samples were acquired using NIR spectroscopy.
• Spectra were compared between direct bottled detection and traditional cell detection methods.
• The 1st derivative method was applied to mitigate packaging interference.
• Principal Component Analysis-Artificial Neural Network (PCA-ANN) was used for qualitative analysis.

Main Results:

• Significant spectral differences were observed between bottled and cell detection methods.
• Glass packaging altered characteristic absorption peaks and absorbance values.
• The 1st derivative method effectively removed the influence of glass packaging.
• The PCA-ANN model achieved 100% prediction accuracy for qualitative analysis.

Conclusions:

• NIR spectroscopy is applicable for bottled vinegar detection.
• Glass packaging significantly influences NIR spectral data.
• The 1st derivative method combined with PCA-ANN is a robust approach for accurate qualitative analysis of bottled vinegar, overcoming packaging interference.