Food freshness and composition evaluated by Colorimetry, TPA, and spectroscopy through ICA-based ComDim: A case study of a peanut-based protein-enriched food

Abstract

This study aimed to apply Common Components and Specific Weights Analysis (CCSWA or ComDim) to explore the relations between colorimetry (color), Texture Profile Analysis (TPA), and Near-Infrared Spectroscopy (NIR) besides determining which of these techniques is most effective in differentiating the freshness and composition of the studied samples. ComDim-ICA, a recent modification of ComDim based on Independent Components Analysis (ICA) decomposition, was used. This approach was chosen to provide more straightforward and interpretable scores and loadings compared to the classical ComDim, which is based on Principal Components Analysis (PCA). The experiment was performed on a peanut-based food enriched with powdered proteins derived from pumpkin seed, rice, pea, sunflower seed, water lentil (duckweed), flaxseed, soybean, and whey. Measurements (Color, NIR, and TPA) were taken on the day of the food preparation, after seven days, and after fourteen days. The global scores indicated that CC2 carried information regarding freshness, while CC3, CC4, and CC5 were associated with food composition. According to the saliences, NIR and color were the most important techniques for determining food freshness (the most important in CC2). Additionally, in CC3, NIR was responsible for distinguishing lentil and rice proteins from the other protein sources. The best differentiation regarding food composition was found in CC4 and CC5, where colorimetry and TPA were most significant. These findings may encourage new applications of multiblock analysis to elucidate differences in food quality based on diverse evaluation techniques.