Feasibility of Detecting Aflatoxin B 1 on Inoculated Maize Kernels Surface using Vis/NIR Hyperspectral Imaging
Authors:
- 12 December 2014
- journal article
- Published by Wiley in Journal of Food Science
- Vol. 80 (1) , M116-22
Abstract
The feasibility of using a visible/near‐infrared hyperspectral imaging system with a wavelength range between 400 and 1000 nm to detect and differentiate different levels of aflatoxin B 1 (AFB 1 ) artificially titrated on maize kernel surface was examined. To reduce the color effects of maize kernels, image analysis was limited to a subset of original spectra (600 to 1000 nm). Residual staining from the AFB 1 on the kernels surface was selected as regions of interest for analysis. Principal components analysis (PCA) was applied to reduce the dimensionality of hyperspectral image data, and then a stepwise factorial discriminant analysis (FDA) was performed on latent PCA variables. The results indicated that discriminant factors F 2 can be used to separate control samples from all of the other groups of kernels with AFB 1 inoculated, whereas the discriminant factors F 1 can be used to identify maize kernels with levels of AFB 1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of β coefficients of the discrimination factors F 1 and F 2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB 1 , as well as those with differing levels of AFB 1 inoculation. Results indicated that Vis/NIR hyperspectral imaging technology combined with the PCA–FDA was a practical method to detect and differentiate different levels of AFB 1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel.Keywords
This publication has 39 references indexed in Scilit:
- A rapid and non-invasive method for authenticating the origin of pistachio samples by NIR spectroscopy and chemometricsChemometrics and Intelligent Laboratory Systems, 2013
- Classification of oat and groat kernels using NIR hyperspectral imagingTalanta, 2013
- Detection of Fusarium damaged kernels in Canada Western Red Spring wheat using visible/near-infrared hyperspectral imaging and principal component analysisComputers and Electronics in Agriculture, 2011
- Early detection of toxigenic fungi on maize by hyperspectral imaging analysisInternational Journal of Food Microbiology, 2010
- A rapid FT-NIR method for estimation of aflatoxin B1 in red chili powderFood Control, 2009
- Determination of aflatoxins in eggs, milk, meat and meat products using HPLC fluorescent and UV detectorsFood Chemistry, 2009
- An ELIME-array for detection of aflatoxin B1 in corn samplesFood Control, 2009
- NIR Absorbance Characteristics of Deoxynivalenol and of Sound and Fusarium-Damaged Wheat KernelsJournal of Near Infrared Spectroscopy, 2009
- Aflatoxin and fumonisin contamination of corn (maize, Zea mays) hybrids in ArkansasCrop Protection, 2006
- Rapid Detection of Kernel Rots and Mycotoxins in Maize by Near-Infrared Reflectance SpectroscopyJournal of Agricultural and Food Chemistry, 2005