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Detection of fusarium damage in Canadian wheat using visible/near-infrared hyperspectral imaging

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Abstract

Fusarium damage in wheat may reduce the quality and safety of food and feed products. In this study, the use of hyperspectral imaging was investigated to detect fusarium damaged kernels (FDK) in Canadian wheat samples. More than 5,200 kernels, representing seven major Canadian wheat classes, with varying degree of infection symptoms ranging from sound through mild to severe were imaged in the visible-NIR (400–1,000 nm) wavelength range. Partial least squares discriminant analysis (PLS-DA) was used to segregate kernels into sound and damaged categories based on kernel mean spectra. A universal PLS-DA model based on four wavelengths was able to detect FDK in all seven classes with an overall accuracy of 90 % and false positives of 9 %.

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Acknowledgments

The authors thank the Inspection Division of the Canadian Grain Commission (CGC) for providing inspected samples for this research. They would also like to thank Loni Powell of the Image Analysis & Spectroscopy Program (CGC) for scanning the samples.

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Authors and Affiliations

  1. Grain Research Laboratory, Canadian Grain Commission, 1404-303 Main Street, Winnipeg, MB, R3C 3G8, Canada

    Muhammad A. Shahin & Stephen J. Symons

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  1. Muhammad A. Shahin
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  2. Stephen J. Symons
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Correspondence to Muhammad A. Shahin.

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Shahin, M.A., Symons, S.J. Detection of fusarium damage in Canadian wheat using visible/near-infrared hyperspectral imaging. Food Measure 6, 3–11 (2012). https://doi.org/10.1007/s11694-012-9126-z

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  • DOI: https://doi.org/10.1007/s11694-012-9126-z

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