Non-destructive food testing is becoming increasingly important due to expanding automation and the incorporation of new and more efficient processes in the food industry. The quality and safety of food are the main points of interest. It is important to have a technology which will allow for a high throughput and a short response time to increase process efficiency and reduce waste. In order for this equipment to be integrated with the existing infrastructure, it should be robust and capable of functioning in varying environments. Near infrared (NIR) spectroscopy provides several advantages compared with traditional analytical methods; it is fast and non-destructive, it requires little or no sample preparation, it can provide simultaneous determination of multiple components per measurement, it has a remote sampling capability and it can provide real-time information in a process stream. Thus, NIR spectroscopy provides the ideal technology needed for fast and efficient food analysis. This review reports recently published (in the last 10 years) applications of NIR spectroscopy in both raw and prepared foods. It highlights the ability of NIR spectroscopy to assess food and beverage composition, functional properties, quality attributes, regional and varietal differences and contribute to food safety and consumer confidence.

This paper reviews the current state of development of both near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for process monitoring, quality control, and authenticity determination in cheese processing. Infrared spectroscopy has been identified as an ideal process analytical technology tool, and recent publications have demonstrated the potential of both NIR and MIR spectroscopy, coupled with chemometric techniques, for monitoring coagulation, syneresis, and ripening as well as determination of authenticity, composition, sensory, and rheological parameters. Recent research is reviewed and compared on the basis of experimental design, spectroscopic and chemometric methods employed to assess the potential of infrared spectroscopy as a technology for improving process control and quality in cheese manufacture. Emerging research areas for these technologies, such as cheese authenticity and food chain traceability, are also discussed.

The potential of near-infrared transflectance spectroscopy (1100-2498 nm) combined with chemometric techniques to confirm the geographical origin of European olive oil samples was evaluated. In total, 913 extra virgin olive oil samples (210 Ligurian and 703 non-Ligurian) were collected over three consecutive harvests (2005, 2006, and 2007). A multivariate spectral fingerprint for Ligurian olive oil was developed and deployed to confirm or refute a claim that any given sample was Ligurian. Samples were pseudorandomly split into calibration (n = 280) and validation sets (n = 633); the only selection constraint applied was to insist on equal numbers of Ligurian and non-Ligurian samples in the calibration set. Following preliminary examination by principal component analysis, the full spectrum modeling method applied to the spectral data set was discriminant partial least-squares regression; various data pretreatments were also investigated. The best models correctly predicted the origins of samples in the prediction set up to 92.8 and 81.5% for Ligurian and non-Ligurian olive oil samples, respectively, using a first-derivative data pretreatment. The potential of this approach in commercial traceability and quality assurance schemes is noted.