کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6391131 1628411 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Near-infrared hyperspectral imaging for detecting Aflatoxin B1 of maize kernels
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک دانش تغذیه
پیش نمایش صفحه اول مقاله
Near-infrared hyperspectral imaging for detecting Aflatoxin B1 of maize kernels
چکیده انگلیسی


- Hyperspectral imaging for identification of aflatoxin infected maize kernels.
- Role of key principal components of PCA to detect aflatoxin were explained.
- Two key wavelengths were identified to be used to indicate AFB1.
- End members extraction based on n-dimensional visualization techniques.
- SAM classification for matching toxin concentration with pixel distribution.

The feasibility of detecting the Aflatoxin B1 in maize kernels inoculated with Aspergillus flavus conidia in the field was assessed using near-infrared hyperspectral imaging technique. After pixel-level calibration, wavelength dependent offset, the masking method was adopted to reduce the noise and extract region of interest (ROI's) of spectral image, then an explanatory principal component analysis (PCA) followed by inverse PCA and secondary PCA was conducted to enhance the signal to noise ratio (SNR), reduce the dimensionality, and extract valuable information of spectral data. By interactive analysis between score image, score plot and load line plot, the first two PCs were found to indicate the spectral characteristics of healthy and infected maize kernels respectively. And the wavelengths of 1729 and 2344 nm were also identified to indicate AFB1 exclusively. The n-dimensional visualization method based on PC3 to PC7 was adapted to select the two classes of end members as the input data of the spectral angle mapper (SAM) classifier to separate the aflatoxin infection and clean kernels. The result was compared with chemical analysis of Aflatest®. And the verification accuracy of pixel level reached 100% except the tip parts of some healthy kernels were falsely identified as aflatoxin contamination. Furthermore, another 26 maize kernels were selected as an independent data set to verify the reproducibility of the method proposed, and the detection accuracy attained to 92.3%, which demonstrated that hyperspectral imaging technique can be used to detect aflatoxin in artificially inoculated maize kernels in the field.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Control - Volume 51, May 2015, Pages 347-355
نویسندگان
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