CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11754 > Article
Translator Disclaimer
Presentation + Paper
12 April 2021 Near-infrared hyperspectral imaging for identification of aflatoxin contamination on corn kernels
Feifei Tao, Haibo Yao, Zuzana Hruska, Russell Kincaid, Kanniah Rajasekaran
Author Affiliations +
Proceedings Volume 11754, Sensing for Agriculture and Food Quality and Safety XIII; 1175408 (2021) https://doi.org/10.1117/12.2591078
Event: SPIE Defense + Commercial Sensing, 2021, Online Only
Abstract
The potential of near infrared hyperspectral imaging over the spectral range of 900 - 2500 nm was investigated for identification of aflatoxin contamination on corn kernels. A total of 600 kernels were used with 3 treatments, namely, 200 kernels inoculated with the AF13 fungus (aflatoxigenic), 200 kernels inoculated with the AF36 fungus (nonaflatoxigenic), and 200 kernels inoculated with sterile distilled water as control. One hundred kernels from each treatment were incubated at 30 °C for 5 and 8 days, separately, and then the kernels were dried and surface wiped to remove exterior signs of mold prior to imaging. The mean spectra including mean reflectance and absorbance, and the textural features consisting of contrast, correlation, energy and homogeneity, were extracted separately from the endosperm regions of single kernels. The partial least-squares discriminant analysis (PLS-DA) models were established using extracted mean spectra or textural features as individual inputs. The full spectral PLS-DA modeling results indicate that the mean spectra including both reflectance and absorbance spectra performed significantly better than using the textural features in identifying aflatoxin contamination on corn kernels. Using the mean reflectance and absorbance spectra between 925 and 2484 nm, the full spectral PLS-DA models achieved mean overall prediction accuracies of 88.3% and 86.3% when taking 20 ppb as the classification threshold. The corresponding means of overall prediction accuracies were 85.5% and 85.6% when 100 ppb was applied as the classification threshold. The extracted textural features were not found to be useful in identifying aflatoxin contamination.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Feifei Tao, Haibo Yao, Zuzana Hruska, Russell Kincaid, and Kanniah Rajasekaran "Near-infrared hyperspectral imaging for identification of aflatoxin contamination on corn kernels", Proc. SPIE 11754, Sensing for Agriculture and Food Quality and Safety XIII, 1175408 (12 April 2021); https://doi.org/10.1117/12.2591078
ACCESS THE FULL ARTICLE
PERSONAL SIGN IN
Full access may be available with your subscription
Forgot your username?
Forgot your password?
No SPIE account? Create an account
Institutional Access:
Sign in with your institutional credentials
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 8 PAGES + PRESENTATION
DOWNLOAD PAPER SAVE TO MY LIBRARY
WATCH
PRESENTATION
SHARE
GET CITATION
Advertisement
Advertisement
KEYWORDS
Contamination
Hyperspectral imaging
Near infrared
Agriculture
Imaging systems
Nondestructive evaluation
Safety
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top