Food Composition Databases: Considerations about Complex Food Matrices

Abstract

Nowadays, many countries have their own national Food Composition Databases, whose continuous updating allows the inclusion of a large number of foods, reflecting the food habits of the population and the growing number of foods on the market in the best way possible. Therefore, particular attention should be directed to the study not only of individual foods or food components but also of the nutritional characteristics of dishes, meals and diets, as they are really consumed. Recently, a reviewed sensitivity in Europe towards the implementation of standardized procedures for generating reliable composition data for composite dishes has been carried out. Although direct chemical analysis is the most accurate method to determine food composition, the nutrient content of complex matrices and composite dishes is often calculated from the nutrient contents of the individual ingredients, considering the different thermal treatments and using some preparation factors. In this context, this paper aims to give an updated picture on Food Composition Databases; in particular, their application regarding complex matrices is examined together with the need to optimize their calculated nutritional values. Results obtained by this calculation should almost always be observed as approximations.

A Disaggregation Methodology to Estimate Intake of Added Sugars and Free Sugars: An Illustration from the UK National Diet and Nutrition Survey

“…In added sugar and free sugar estimations, recipe calculation is an inevitable step, as in the method developed by Louie et al [ 19 ]; however it can be challenging to develop a recipes database. Various countries or organizations use some form of datasets including standard recipes or the disaggregation of composite foods [ 36 , 37 , 38 , 39 ] which can also be used in a similar way equivalent to a recipe database. Technical database facilities such as the automated background calculation facilitate the recipe calculation process.…”

MIGHT: Statistical Methodology for Missing-Data Imputation in Food Composition Databases

“…We also plan to extend the methodology to work for data imputation of more than one missing value using multivariate statistical analysis and some modification of the NMF method. On the topic of missing FCD, one of our next steps is also considering other solutions for missing data-calculating missing data from recipes [16] or estimating values from a similar food or the same food in different form. In terms of improving MIGHT, we are planning to work on an extension which will handle situations when more than one nutrient value is missing, following the idea of non-negative matrix factorization in a combination with multi-view learning [57,58].…”

“…Calculated values: Data are derived from recipes, calculated from the nutrient contents of the ingredients and corrected for preparation factors [16].…”

Ethnomycological Knowledge of Three Ethnic Groups in Ethiopia

“…In various cultures, mushrooms can serve as sources of food [14], medicine [16], enzymes and various industrial compounds [17]. They serve as also important composition of food and recipes for traditional foods and recipes [18,19]. In addition, mushrooms can serve in a recreational context and in myths and beliefs [20].…”