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Abstract
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| In the present work the feasibility of NIR hyperspectral imaging (HSI) was studied for the detection of peanut traces down to 0.01 % by weight. Principal Component Analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image and the percentage of peanut adulteration was compared to the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01 % and quantification of peanut adulteration from 10 % to 0.1 % with a determination coefficient R2 = 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjuction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality control surveyance on food product processing lines. | |
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International
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Si |
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Type
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Master |
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Mark Rating
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Sobresaliente |
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Date
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03/07/2015 |