Title : Potential for detecting food adulteration using spectral techniques
Abstract:
Increase in food prices and rapid developments in food science have affected food industry both positively and negatively. The negative effect is that some bad producers now engage in food adulteration practices that are harder to detect. They can deceive consumers and make unfair profits. There is a dramatic increase in publications about food fraud after 2010. For example, while in 2005, there were 40 publications published on this subject in Scopus, this number reached 250 in 2020. Some types of foods are vulnerable to adulteration because their original specific characteristics cannot be easily identified. Hence, the economically motivated adulteration of some foods especially high price foods such as honey, olive oil, meat product and molasses are rather possibly to be practiced. This study aimed to assess the potential of spectral based detecting of adulteration for some foods. For this aim, researches on detecting food adulteration by using spectral methods have been compiled. Using potential of spectral techniques in industry or inspections have been evaluated. In order to detect food adulteration using spectral methods, the spectral technique must first be able to detect food with a high success rate of 99%. Foods may differ depending on agricultural production conditions and this difference may cause errors in determining adulteration. The spectral technique should not give misleading results due to effects such as climate, growing conditions, processing method and seasonal differences. When necessary, applications such as using spectral techniques by integrating them with classical methods or verifying with classical methods will make it possible to make more accurate decisions about adulteration in audits. Detecting adulteration with spectral data is always attractive as it is a cheap and practical method, but it is important that the detection success rate is always high. In order to have high detection success, it can be recommended to apply different modelling. There is a high possibility of adulteration in products such as honey, grape molasses, olive oil, minced meat and dairy products. It has been reported that if grape molasses is mixed with fructose, sucrose or glucose syrup in different proportions, adulteration can be clearly detected by spectral methods. Specific to the sensor, it has been reported that the spectroscopic data obtained has a significant potential for detecting adulteration in ground meat and determining the amount of adulteration. Spectral techniques have been shown to be effective in cheese authentication and geographic origin determination, especially when associated with chemometrics. It has been stated that the information obtained from mid-infrared and Raman spectroscopy offers descriptive advantages in honey and that mid-infrared spectroscopy can detect adulteration in honey with a 95% success rate. It seems that the spectral technique is promising in research on the detection of adulteration in different foods. In the future, it is recommended to determine the potential for use of spectral techniques in legal controls and to increase their widespread use.
