Literature DB >> 25495222

Feasibility of detecting aflatoxin B1 on inoculated maize kernels surface using Vis/NIR hyperspectral imaging.

Wei Wang1, Gerald W Heitschmidt, William R Windham, Peggy Feldner, Xinzhi Ni, Xuan Chu.   

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 B1 (AFB1 ) 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 AFB1 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 F2 can be used to separate control samples from all of the other groups of kernels with AFB1 inoculated, whereas the discriminant factors F1 can be used to identify maize kernels with levels of AFB1 as low as 10 ppb. An overall classification accuracy of 98% was achieved. Finally, the peaks of β coefficients of the discrimination factors F1 and F2 were analyzed and several key wavelengths identified for differentiating maize kernels with and without AFB1 , as well as those with differing levels of AFB1 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 AFB1 artificially inoculated on the maize kernels surface. However, indicated the potential to detect and differentiate naturally occurring toxins in maize kernel.
© 2014 Institute of Food Technologists®

Entities:  

Keywords:  aflatoxin B1 (AFB1); factorial discriminant analysis (FDA); hyperspectral imaging; maize; principal components analysis (PCA)

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Year:  2014        PMID: 25495222     DOI: 10.1111/1750-3841.12728

Source DB:  PubMed          Journal:  J Food Sci        ISSN: 0022-1147            Impact factor:   3.167


  6 in total

1.  Detection of Aflatoxin B1 in Single Peanut Kernels by Combining Hyperspectral and Microscopic Imaging Technologies.

Authors:  Haicheng Zhang; Beibei Jia; Yao Lu; Seung-Chul Yoon; Xinzhi Ni; Hong Zhuang; Xiaohuan Guo; Wenxin Le; Wei Wang
Journal:  Sensors (Basel)       Date:  2022-06-27       Impact factor: 3.847

Review 2.  Aflatoxins in Food and Feed: An Overview on Prevalence, Detection and Control Strategies.

Authors:  Dipendra K Mahato; Kyung Eun Lee; Madhu Kamle; Sheetal Devi; Krishna N Dewangan; Pradeep Kumar; Sang G Kang
Journal:  Front Microbiol       Date:  2019-10-04       Impact factor: 5.640

Review 3.  Hyperspectral imaging for seed quality and safety inspection: a review.

Authors:  Lei Feng; Susu Zhu; Fei Liu; Yong He; Yidan Bao; Chu Zhang
Journal:  Plant Methods       Date:  2019-08-08       Impact factor: 4.993

4.  Principal component analysis of hyperspectral data for early detection of mould in cheeselets.

Authors:  Jessica Farrugia; Sholeem Griffin; Vasilis P Valdramidis; Kenneth Camilleri; Owen Falzon
Journal:  Curr Res Food Sci       Date:  2021-01-11

5.  Non-destructive classification and prediction of aflatoxin-B1 concentration in maize kernels using Vis-NIR (400-1000 nm) hyperspectral imaging.

Authors:  Subir Kumar Chakraborty; Naveen Kumar Mahanti; Shekh Mukhtar Mansuri; Manoj Kumar Tripathi; Nachiket Kotwaliwale; Digvir Singh Jayas
Journal:  J Food Sci Technol       Date:  2020-06-06       Impact factor: 2.701

6.  Assessment of Fusarium Infection and Mycotoxin Contamination of Wheat Kernels and Flour Using Hyperspectral Imaging.

Authors:  Elias Alisaac; Jan Behmann; Anna Rathgeb; Petr Karlovsky; Heinz-Wilhelm Dehne; Anne-Katrin Mahlein
Journal:  Toxins (Basel)       Date:  2019-09-21       Impact factor: 4.546

  6 in total

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