Raman on ramen: Nutritional analysis and brand identification

Abstract

Precise and nondestructive assessment of food quality and its nutritional composition can be used to personalize nutrition, which, in turn, will improve well-being and help to prevent chronic diseases for millions of people around the world. Currently used methods for elucidation of nutritional composition of food are destructive, time, and labor consuming. In this study, we investigate the potential of Raman spectroscopy (RS), an emerging analytical technique, in a noninvasive, nondestructive, and a chemical-free analysis of the nutritional composition of ramen, one of the most popular foods in the world. We found that RS could be used to quantify the amount of carbohydrates, gluten, and lipids in ramen. In coupled to chemometrics, RS enables ~100% accurate differentiation between gluten-rich and gluten-free ramen. Furthermore, using RS, one can identify the brand and the country of origin of ramen. These findings suggest that Raman-based sensors can be used in daily life for quality control of consumed food in both restaurants and grocery stores.