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Applications of single kernel conventional and hyperspectral imaging near infrared spectroscopy in cereals

Authors

  • Glen Fox,

    Corresponding author
    1. Queensland Alliance for Agriculture & Food Innovation, Centre for Nutrition & Food Science, The University of Queensland, Toowoomba, Qld, Australia
    2. Department of Food Science, Stellenbosch University, Matieland, (Stellenbosch), South Africa
    • Correspondence to: Glen Fox, Queensland Alliance for Agriculture & Food Innovation, Centre for Nutrition & Food Science, The University of Queensland, P.O. Box 2282, Toowoomba, Qld 4350, Australia. E-mail: g.fox1@uq.edu.au

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  • Marena Manley

    1. Department of Food Science, Stellenbosch University, Matieland, (Stellenbosch), South Africa
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Abstract

Single kernel (SK) near infrared (NIR) reflectance and transmittance technologies have been developed during the last two decades for a range of cereal grain physical quality and chemical traits as well as detecting and predicting levels of toxins produced by fungi. Challenges during the development of single kernel near infrared (SK-NIR) spectroscopy applications are modifications of existing NIR technology to present single kernels for scanning as well as modifying reference methods for the trait of interest. Numerous applications have been developed, and cover almost all cereals although most have been for key traits including moisture, protein, starch and oil in the globally important food grains, i.e. maize, wheat, rice and barley. An additional benefit in developing SK-NIR applications has been to demonstrate the value in sorting grain infected with a fungus or mycotoxins such as deoxynivalenol, fumonisins and aflatoxins. However, there is still a need to develop cost-effective technologies for high-speed sorting which can be used for small grain samples such as those from breeding programmes or commercial sorting; capable of sorting tonnes per hour. Development of SK-NIR technologies also includes standardisation of SK reference methods to analyse single kernels. For protein content, the use of the Dumas method would require minimal standardisation; for starch or oil content, considerable development would be required. SK-NIR, including the use of hyperspectral imaging, will improve our understanding of grain quality and the inherent variation in the range of a trait. In the area of food safety, this technology will benefit farmers, industry and consumers if it enables contaminated grain to be removed from the human food chain. © 2013 Society of Chemical Industry

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