A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

Clicks: 296
ID: 111938
2012
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Abstract
This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar) were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose) and Fourier Transform Infrared Spectroscopy (FTIR) were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0%) gave higher classification accuracy than e-nose data (76.5%) using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.
Reference Key
subari2012sensorsa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Norazian Subari;Junita Mohamad Saleh;Ali Yeon Md Shakaff;Ammar Zakaria;Subari, Norazian;Mohamad Saleh, Junita;Md Shakaff, Ali Yeon;Zakaria, Ammar;
Journal sensors
Year 2012
DOI
10.3390/s121014022
URL
https://www.mdpi.com/1424-8220/12/10/14022
Keywords
ftir electronic nose data fusion honey classification pure honey National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine research support non-u.s. gov't Evaluation Study discriminant analysis principal component analysis biosensing techniques / methods* spectroscopy fourier transform infrared food contamination / analysis* pmid:23202033 pmc3545604 doi:10.3390/s121014022 norazian subari junita mohamad saleh ammar zakaria beta vulgaris / chemistry biosensing techniques / instrumentation dietary sucrose / analysis electronic nose honey / analysis honey / classification* saccharum / chemistry

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