Adulterated stingless bee honey identification using VIS-NIR-spectroscopy technique

A. M. Mustafah, . and D. Jamaludin, . and M. F. I. Azmi, . and S. Abd. Aziz, . and Y. A. Yusof, . Adulterated stingless bee honey identification using VIS-NIR-spectroscopy technique. pp. 85-93. ISSN 2550-2166

The objective of this study was to study the ability of the VIS-NIR spectroscopy to classify the pure and adulterated stingless bee honey across the wavelength range of 450“ 969 nm using an optical spectrometer. The physicochemical properties such as soluble solid content (SSC) and moisture content (refractive index RI) of pure and adulterated honey has also been investigated using a refractometer. The result showed that pure stingless bee honey has the highest transmittance rate SSC and RI value compared to adulterated honey. There are significant differences (P 0.0001) in the transmittance rate SSC and RI of stingless bee honey over five different types of treatments. The results also showed that VIS-NIR data were good in classifying the samples into different treatments with 99.33 accuracy rate. About thirty-four wavelengths were found to be the most significant to discriminate the different treatments by principal component analysis (PCA) and linear discriminant analysis (LDA) techniques.

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Abstract

The objective of this study was to study the ability of the VIS-NIR spectroscopy to classify the pure and adulterated stingless bee honey across the wavelength range of 450“ 969 nm using an optical spectrometer. The physicochemical properties such as soluble solid content (SSC) and moisture content (refractive index RI) of pure and adulterated honey has also been investigated using a refractometer. The result showed that pure stingless bee honey has the highest transmittance rate SSC and RI value compared to adulterated honey. There are significant differences (P 0.0001) in the transmittance rate SSC and RI of stingless bee honey over five different types of treatments. The results also showed that VIS-NIR data were good in classifying the samples into different treatments with 99.33 accuracy rate. About thirty-four wavelengths were found to be the most significant to discriminate the different treatments by principal component analysis (PCA) and linear discriminant analysis (LDA) techniques.

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Item Type:	Article
AGROVOC Term:	Bees
AGROVOC Term:	Honey bees
AGROVOC Term:	NIR spectroscopy
AGROVOC Term:	Sampling
AGROVOC Term:	Moisture content
AGROVOC Term:	Statistical analysis
AGROVOC Term:	Quality controls
AGROVOC Term:	Food safety
AGROVOC Term:	Data processing
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/10567

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