Review
Hyperspectral imaging – an emerging process analytical tool for food quality and safety control

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Hyperspectral imaging (HSI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Although HSI was originally developed for remote sensing, it has recently emerged as a powerful process analytical tool for non-destructive food analysis. This paper provides an introduction to hyperspectral imaging: HSI equipment, image acquisition and processing are described; current limitations and likely future applications are discussed. In addition, recent advances in the application of HSI to food safety and quality assessment are reviewed, such as contaminant detection, defect identification, constituent analysis and quality evaluation.

Introduction

Food process control necessitates real-time monitoring at critical processing points. Fast and precise analytical methods are essential to ensure product quality, safety, authenticity and compliance with labelling. Traditional methods of food monitoring involving analytical techniques such as high performance liquid chromatography (HPLC) and mass spectrometry (MS) are time consuming, expensive and require sample destruction. Near infrared spectroscopy (NIRS) is well established as a non-destructive tool for multi-constituent quality analysis of food materials (Scotter, 1990). However, the inability of NIR spectrometers to capture internal constituent gradients within food products may lead to discrepancies between predicted and measured composition. Furthermore, spectroscopic assessments with relatively small point-source measurements do not contain spatial information, which is important to many food inspection applications (Ariana, Lu, & Guyer, 2006).

Recent advances in computer technology have led to the development of imaging systems capable of identifying quality problems rapidly on the processing line, with the minimum of human intervention (Brosnan and Sun, 2004, Du and Sun, 2004). Red–Green–Blue (RGB) colour vision systems find widespread use in food quality control for the detection of surface defects and grading operations (Chao et al., 1999, Daley et al., 1993, Throop et al., 1993). However, conventional colour cameras are poor identifiers of surface features sensitive to wavebands other than RGB, such as low but potentially harmful concentrations of animal faeces on foods (Liu et al., 2007, Park et al., 2006). To overcome this, multispectral imaging systems have been developed to combine images acquired at a number (usually 3–4) of narrow wavebands, sensitive to features of interest on the object. Compared with conventional analytical methods such as HPLC, multispectral imaging systems can perform non-destructive analyses in a fraction of the time required (Malik, Poonacha, Moses, & Lodder, 2001).

Section snippets

Hyperspectral imaging

Hyperspectral imaging, known also as chemical or spectroscopic imaging, is an emerging technique that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. It was originally developed for remote sensing applications (Goetz, Vane, Solomon, & Rock, 1985) but has since found application in such diverse fields as astronomy (Hege et al., 2003, Wood et al., 2002), agriculture (Monteiro et al., 2007, Smail et al., 2006, Uno et al., 2005),

Applications of hyperspectral imaging to food quality and safety

Hyperspectral imaging is a powerful tool for the identification of key wavebands in the development of online automated multispectral imaging systems. Consequently, it finds widespread use in research for the development of multispectral inspection tools. Hyperspectral imaging, like other spectroscopy techniques, can be carried out in reflectance, transmission or fluorescence modes. While the majority of published research on hyperspectral imaging has been performed in reflectance mode,

Limitations

HSI is a powerful platform technology for food process monitoring. Currently, however, there are two major barriers to its widespread adoption in the food industry. The first is the high purchase cost of HSI systems: since this technology is emerging as a tool for food quality evaluation, there are few commercial suppliers. It is anticipated that future technological developments in HSI systems for the pharmaceutical industry will promote the manufacture of low cost systems suitable for food

Conclusions

Hyperspectral imaging (HSI) is an emerging tool for food quality and safety analysis; the spatial feature of HSI enables characterisation of complex heterogeneous samples, while the spectral feature allows for the identification of a wide range of multi-constituent surface and sub-surface features. Due to the current high cost of HSI systems, most food related HSI research has been geared towards identification of important wavebands for the development of low cost multispectral imaging

Acknowledgement

The authors would like to acknowledge the funding of the Irish Government Department of Agriculture and Food under the Food Institutional Research Measure (FIRM).

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