Multivariate Evaluation of Vitamin and Mineral Retention Across Diverse Foods and Processing Methods

Year 2025, Volume: 9 Issue: 4, 1379 - 1393, 26.12.2025

Yusuf Durmuş

https://doi.org/10.31015/2025.4.38

https://izlik.org/JA28EF24RA

Abstract

This study aimed to elucidate the effects of food matrix and processing methods on nutrient retention by applying multivariate and dimensionality reduction analyses to retention factor data. The nutrient retention factor (RF) data for different foods and processing methods were obtained from the Australian Food Composition Database. A total of 261 RF values were analyzed for 16 nutrients, 30 food categories, and 57 processing types. Dimensionality reduction and clustering techniques, including principal component analysis (PCA), isometric mapping (ISOMAP), uniform manifold approximation and projection (UMAP), and hierarchical cluster analysis (HCA), were employed to explore relationships among nutrients, foods, and processing conditions. The results showed that nutrient stability varies substantially depending on the nutrient class, food matrix, and processing intensity. Minerals such as Zn, Fe, Ca, P, and Mg showed the highest mean RFs (>0.90), indicating strong thermal and oxidative stability, whereas water-soluble vitamins, including folic acid, vitamin B1, vitamin B6, and vitamin C, showed the lowest retention (<0.80). The highest nutritional losses occurred by moist-heat treatments, especially extended boiling while the most effective nutrient preservation was achieved by reheating and rapid preparation. Correlation and clustering analyses demonstrated that the nutrient retention patterns are significantly impacted by dietary matrix composition and processing intensity. Dimensionality reduction techniques revealed distinct grouping patterns among food categories, emphasizing the effects of the food matrix on nutrient retention. Legumes and pasta experienced extensive water-soluble vitamin loss due to leaching, while meats and dairy products exhibited moderate vitamin loss and stable mineral retention. Overall, this study offers a thorough multivariate evaluation of nutrient retention behavior, providing insightful information for improving processing and cooking techniques to raise food quality while minimizing micronutrient losses.

Keywords

ISOMAP , Mineral , PCA , Retention factor , UMAP , Vitamin

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