A hybrid sensing approach for pure and adulterated honey classification
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MDPI AG, Basel, Switzerland
2014
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my.unimap-318402014-02-10T08:13:45Z A hybrid sensing approach for pure and adulterated honey classification Norazian, Subari Junita, Mohamad Saleh, Dr. Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria aziansubari@ump.edu.my jms@eng.usm.my aliyeon@unimap.edu.my ammarzakaria@unimap.edu.my Data fusion Electronic nose FTIR Honey classification Pure honey Link to publisher’s homepage at http://www.mdpi.com 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. 2014-02-10T08:13:45Z 2014-02-10T08:13:45Z 2012-10 Article Sensors (Switzerland), vol. 12(10), 2012, pages 14022-14040 1424-8220 http://www.mdpi.com/1424-8220/12/10/14022 http://dspace.unimap.edu.my:80/dspace/handle/123456789/31840 en MDPI AG, Basel, Switzerland |
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Malaysia |
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Universiti Malaysia Perlis |
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| language |
English |
| topic |
Data fusion Electronic nose FTIR Honey classification Pure honey |
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Data fusion Electronic nose FTIR Honey classification Pure honey Norazian, Subari Junita, Mohamad Saleh, Dr. Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria A hybrid sensing approach for pure and adulterated honey classification |
| description |
Link to publisher’s homepage at http://www.mdpi.com |
| author2 |
aziansubari@ump.edu.my |
| author_facet |
aziansubari@ump.edu.my Norazian, Subari Junita, Mohamad Saleh, Dr. Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria |
| format |
Article |
| author |
Norazian, Subari Junita, Mohamad Saleh, Dr. Ali Yeon, Md Shakaff, Prof. Dr. Ammar, Zakaria |
| author_sort |
Norazian, Subari |
| title |
A hybrid sensing approach for pure and adulterated honey classification |
| title_short |
A hybrid sensing approach for pure and adulterated honey classification |
| title_full |
A hybrid sensing approach for pure and adulterated honey classification |
| title_fullStr |
A hybrid sensing approach for pure and adulterated honey classification |
| title_full_unstemmed |
A hybrid sensing approach for pure and adulterated honey classification |
| title_sort |
hybrid sensing approach for pure and adulterated honey classification |
| publisher |
MDPI AG, Basel, Switzerland |
| publishDate |
2014 |
| url |
http://dspace.unimap.edu.my:80/dspace/handle/123456789/31840 |
| _version_ |
1643796699681914880 |