| dc.description.abstract | With the substantial global population growth, it is estimated that the population will be nearing around 9.7 billion by 2050. With this in hand, the demand for food production is an imminent matter in question that must be fulfilled to avert a food crisis of global malnutrition. This is where we introduce our research to enhance the upcoming, cutting-edge technology that is Raman spectroscopy (RS), known for being non-invasive, non-destructive, and chemical free. Through this method, we aim to strengthen and test the instrument's potential in its ability to accurately identify and classify different vibrational frequencies to enhance our nutritional analysis. Through advancements in nutritional analysis, we can identify important macromolecules such as carbohydrates, proteins, and fats to reach a precise quantification of one's nutrient intake. By analyzing popular international foods such as ramen noodles, bread, and similar carbohydrate foods, we can promote the use of RS to create a non-destructive and chemical-free method in the production of these foods. In this study, we hypothesized that through RS we could collect substantial data and process this data to produce accurate results to enhance our nutritional analysis. Our results indicate that RS is successful in its ability to differentiate between foods and, more specifically, food brands. The data collected is then analyzed using a multi-paradigm programming language to further enhance this precise nutritional analysis. In this study we use RS to analyze and distinguish the samples tested, however, we are also studying the potential of RS towards our agricultural sciences to impact the impending global issue. | |
