Abstract
Estimating food intake is an important means of assessing dietary exposure to chemicals. However, while sources of concentration data (e.g., safety levels and nutrient content) are often available for food raw materials, foods are consumed in both processed and raw forms. Therefore, processed food intake levels must be properly converted to those of their constituent ingredients to accurately estimate food intake. On this premise, the current study aimed to generate processed-to-raw food conversion factors (PRCFs). To generate PRCFs, two approaches were primarily employed. One approach involved the percentage yield method, wherein conversion factors were generated by calculating reverse percentage yield. For foods that had undergone simple processing procedures (e.g., soaking and dehydration) as a whole foods, percentage yield was exclusively used. Nevertheless, numerous processed foods (e.g., milled grains and butter) are simultaneously produced from distinct fractions after undergoing separation from their initial raw materials. For these foods, PRCFs were derived using partition ratios in combination with reverse percentage yield. For the remaining processed foods (e.g., vinegars and tea infusions) in which weight changes were not easily traceable, the migration rate method, which calculates the content of specific components in the final processed food relative to that in the initial food ingredients, was utilized. The literature was extensively reviewed to collect the required data. In addition, polyphenol content was directly measured using the Folin-Ciocalteu assay to derive polyphenol migration rates for tea infusions and stocks prepared with spices. In total, the current study generated 120 PRCFs across diverse processing procedures and food types. These factors will serve as a valuable tool for the accurate estimation of food intake, thereby facilitating adequate dietary exposure assessments associated with food chemicals, such as pesticide residues, food contaminants, nutrients, and other substances.