2016
DOI: 10.1016/j.jspr.2015.11.004
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Detection of fungal infection and Ochratoxin A contamination in stored wheat using near-infrared hyperspectral imaging

Abstract: Fungal infection and mycotoxin contamination in agricultural products are a serious food safety issue. The detection of fungal infection and mycotoxin contamination in food products should be in a rapid way. A Near-Infrared (NIR) hyperspectral imaging system was used to detect fungal infection in 2013 crop year canola, wheat, and barley at different periods after inoculation and different concentration levels of ochratoxin A in wheat and barley. Artificially fungal infected (Fungi: Aspergillus glaucus, Penicil… Show more

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Cited by 32 publications
(11 citation statements)
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“…Near-infrared hyperspectral imaging was used to detect fungal infection and Ochratoxin A contamination in stored wheat and PCA was applied to obtain significant wavelengths. All the three classifiers of linear, quadratic and Mahalanobis discriminant classifiers differentiated healthy kernels from fungal-infected kernels with a classification accuracy higher 90% [7] . Besides the application on crop quality detection, spectroscopy technology had been widely used on qualitative analysis of variety [8,9] , adulteration [10][11][12][13][14] , crops of different years [15] , etc.…”
Section: Introduction mentioning
confidence: 94%
“…Near-infrared hyperspectral imaging was used to detect fungal infection and Ochratoxin A contamination in stored wheat and PCA was applied to obtain significant wavelengths. All the three classifiers of linear, quadratic and Mahalanobis discriminant classifiers differentiated healthy kernels from fungal-infected kernels with a classification accuracy higher 90% [7] . Besides the application on crop quality detection, spectroscopy technology had been widely used on qualitative analysis of variety [8,9] , adulteration [10][11][12][13][14] , crops of different years [15] , etc.…”
Section: Introduction mentioning
confidence: 94%
“…Though a slight misclassification may occur when the AFB 1 concentration is lower than 10 μg/kg, aflatoxinfree samples could readily be separated from contaminated ones. Senthilkumar et al (2016a) was the first to apply HSI to the detection of OTA in stored wheat. After carrying out PCA, based on the highest factor loadings of PC 1 , 1,280, 1,300, and 1,350 nm were identified as the three significant wavelengths that corresponded to fungal (Aspergilus glaucus and Penicillium spp.)…”
Section: Raman Spectroscopymentioning
confidence: 99%
“…Specific groups of feature wavelengths associated with Aspergillus glaucus , Penicillium spp., and ochratoxin A were identified as significant wavelengths according to the loading plot of PCA. These selected wavelengths were used in statistical discriminant analyses (such as linear, quadratic, and Mahalanobis discriminant classifiers) to differentiate fungal‐infected kernels with over 90% classification accuracy (Senthilkumar and others , , ). In the study of Sun and others (), fungal‐infected peaches were effectively distinguished based on multispectral imaging and band ratio (BR) method.…”
Section: Determination Of Quality Parameters Of Plant Foodsmentioning
confidence: 99%