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Near Infrared Spectrometry for Rapid Non-Invasive Modelling of Aspergillus -Contaminated Maturing Kernels of Maize ( Zea mays L.)

Author

Listed:
  • Titilayo D.O. Falade

    (Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane QLD 4108, Australia
    International Institute of Tropical Agriculture, Headquarters & West African Hub, Ibadan 200001, Nigeria)

  • Yasmina Sultanbawa

    (Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane QLD 4108, Australia)

  • Mary T. Fletcher

    (Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane QLD 4108, Australia)

  • Glen Fox

    (Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane QLD 4108, Australia)

Abstract

Aflatoxin-producing Aspergillus spp. produce carcinogenic metabolites that contaminate maize. Maize kernel absorbance patterns of near infrared (NIR) wavelengths (800–2600 nm) were used to non-invasively identify kernels of milk-, dough- and dent-stage maturities with four doses of Aspergillus sp. contamination. Near infrared spectrometry (NIRS) spectral data was pre-processed using first derivative Savitzky-Golay (1d-SG) transformation and multiplicative scatter correction on spectral data. Contaminated kernels had higher absorbance between 800–1134 nm, while uninoculated samples had higher absorbance above 1400 nm. Dose and maturity clusters seen in Principal Component Analysis (PCA) score plots were due to bond stretches of combination bands, CH and C=O functional groups within grain macromolecules. The regression model at 2198 nm separated uninoculated and inoculated kernels ( p < 0.0001, R 2 = 0.88, root mean square error = 0.15). Non-invasive identification of Aspergillus- contaminated maize kernels using NIR spectrometry was demonstrated in kernels of different maturities.

Suggested Citation

  • Titilayo D.O. Falade & Yasmina Sultanbawa & Mary T. Fletcher & Glen Fox, 2017. "Near Infrared Spectrometry for Rapid Non-Invasive Modelling of Aspergillus -Contaminated Maturing Kernels of Maize ( Zea mays L.)," Agriculture, MDPI, vol. 7(9), pages 1-13, September.
    • Handle: RePEc:gam:jagris:v:7:y:2017:i:9:p:77-:d:112413
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    References listed on IDEAS

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    1. Dong An & Yongjin Cui & Xu Liu & Shiqiang Jia & Shuyun Zheng & Xiaoping Che & Zhe Liu & Xiaodong Zhang & Dehai Zhu & Shaoming Li, 2016. "Effects of Varieties, Producing Areas, Ears, and Ear Positions of Single Maize Kernels on Near-Infrared Spectra for Identification and Traceability," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-12, September.
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      Keywords

      NIR; maize; Aspergillus;
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