Application of zNose™ for classification of enzymatically-macerated and steamed pumpkin using principal component analysis
High resolution olfactory images, called VaporPrintsTM, derived from the frequency of a surface acoustic wave (SAW) detector, are particularly useful to human because of their ability to recognize and differentiate visual images. In this study, the VaporPrintTM of fresh pumpkin (Cucurbita moscha...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Faculty of Food Science and Technology, Universiti Putra Malaysia
2011
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| Online Access: | http://psasir.upm.edu.my/id/eprint/24037/1/24037.pdf http://psasir.upm.edu.my/id/eprint/24037/ http://www.ifrj.upm.edu.my/volume-18-2011.html |
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| Summary: | High resolution olfactory images, called VaporPrintsTM, derived from the frequency of a surface acoustic
wave (SAW) detector, are particularly useful to human because of their ability to recognize and differentiate
visual images. In this study, the VaporPrintTM of fresh pumpkin (Cucurbita moschata) and different products of
the pumpkin including steamed pumpkin and also pumpkin purees as affected by different enzymes (Pectinex®
Ultra SP-L and Celluclast®; Novozyme, Denmark) were determined using an ultra-fast GC (zNoseTM) based on
a SAW sensor. The zNose™ fingerprints served as a potential tool for qualitative and discriminative distinction
of aroma between the different pumpkin products. Principal component analysis (PCA) was used to analyse the
data. Based on the results, samples were categorized into three different groups. According to the score plot of
PC 2 (second component) versus PC 1 (first component), aromas of enzymatically macerated pumpkin were
close together. The PC 1 and PC 2 factors resulted in the model that describe the 82.9% of the total variance and
seemed sufficient to define a good model. |
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