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Descripción
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| Common use of same environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as Enzyme-Linked Immunosorbent Assay (ELISA) and Real Time Polymerase Chain Reaction (RT-PCR) represent high specificity and sensitivity but are destructive, time consuming and require human involvement with high experimentation skills. The feasibility of NIR hyperspectral imaging (HSI) is 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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Internacional
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JCR del ISI
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Si |
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Título de la revista
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Journal of Near Infrared Spectroscopy |
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ISSN
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0967-0335 |
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Factor de impacto JCR
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1,48 |
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Información de impacto
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Datos JCR del año 2013 |
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Volumen
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23 |
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DOI
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Número de revista
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1 |
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Desde la página
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1 |
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Hasta la página
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9 |
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Mes
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SIN MES |
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Ranking
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