Optical techniques for quality determination of cereal grains

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INTRODUCTION: In today's world, consumers are becoming increasingly concerned about the safety and quality of their food. This has put a pressure on the production industry to heighten quality-monitoring standards. Automation of quality inspection processes is the only way the industry can deliver consistent and efficient results. However, there is gap in technology to provide inexpensive and real-time solutions to meet these demands. It is hypothesized that the fundamental theories of mathematics and modern computational techniques can be integrated together and be used for developing instrumentation for comprehensive assessment of food quality. SCIENTIFIC APPROACH: The long-term goal of my research is to develop advanced knowledge of the basis by which spectral signals are related to the quality aspects of food materials; improve hardware and software techniques to enhance these signals; and use this information to develop instrumentation to optimize the quality monitoring, grading, and processing operations in industries such as food, nutraceutical, dairy, etc.The proposed research is focussed on developing and optimizing algorithms and data analyses techniques to acquire, enhance, transform, and analyze hyperspectral near-infrared images of wheat kernels. The developed methods will be tested on western Canadian wheat to identify early onset of Fusarium, a mold that causes health hazards in humans and animals and causes millions of dollars of economic losses to the grain industry worldwide. Spectral data will be analyzed using techniques such as wavelets, multivariate-image analysis, and genetic algorithm. EXPECTED SIGNIFICANCE: The knowledge base developed through this research will provide health benefits to the whole society and economic benefits to the Canadian grain industry. Although the developed techniques are being evaluated only in the food engineering area in this study, they will be instrumental in a variety of other disciplines e.g. manufacturing, biomedicine, nanotechnology, remote sensing, etc.