StandFood: Standardization of Foods Using a Semi-Automatic System for Classifying and Describing Foods According to FoodEx2.

Tome Eftimov,Peter Korošec,Barbara Koroušić Seljak

doi:10.3390/nu9060542

Abstract

The European Food Safety Authority has developed a standardized food classification and description system called FoodEx2. It uses facets to describe food properties and aspects from various perspectives, making it easier to compare food consumption data from different sources and perform more detailed data analyses. However, both food composition data and food consumption data, which need to be linked, are lacking in FoodEx2 because the process of classification and description has to be manually performed—a process that is laborious and requires good knowledge of the system and also good knowledge of food (composition, processing, marketing, etc.). In this paper, we introduce a semi-automatic system for classifying and describing foods according to FoodEx2, which consists of three parts. The first involves a machine learning approach and classifies foods into four FoodEx2 categories, with two for single foods: raw (r) and derivatives (d), and two for composite foods: simple (s) and aggregated (c). The second uses a natural language processing approach and probability theory to describe foods. The third combines the result from the first and the second part by defining post-processing rules in order to improve the result for the classification part. We tested the system using a set of food items (from Slovenia) manually-coded according to FoodEx2. The new semi-automatic system obtained an accuracy of 89% for the classification part and 79% for the description part, or an overall result of 79% for the whole system.

Highlights

In 2011, the European Food Safety Authority (EFSA) [1] introduced a comprehensive food classification and description system for exposure assessment, known as FoodEx1 [2], aimed at covering the need to describe food in data collections across different food safety domains
The main goal is to describe food items according to FoodEx2 and to find the most relevant food item that exists in the FoodEx2 data
The obtained FoodEx2 code is compared with the FoodEx2 code that was manually assigned to the food item by a human expert

Summary

Introduction

In 2011, the European Food Safety Authority (EFSA) [1] introduced a comprehensive food classification and description system for exposure assessment, known as FoodEx1 [2], aimed at covering the need to describe food in data collections across different food safety domains. In 2015, EFSA introduced a new version called FoodEx2 [2], in order to match the needs expressed by different users. It provides generic food descriptions that represent the minimum level of detail required for making intake or exposure assessments. FoodEx2 is applicable across different domains, in particular food consumption, chemical contaminants, pesticide residues, zoonoses, and food composition.

Methods

Results

Discussion

Conclusion