Identifying and describing foods unambiguously
Clear, unambiguous food description is essential to enable users to correctly identify and select foods required from a food composition database (FCDB). Even when using the most comprehensive and up-to-date food composition data (FCD) available, errors will be introduced if the selected food does not match that consumed.
Food names alone do not always allow identification of foods, since they may be ambiguous, particularly when using FCD from other countries. For example, ‘sherbert’ can be a flavoured sweet sparkling powder (confectionery), a drink of sweet diluted fruit juice, or a sorbet (frozen dessert). Similarly, ‘squash’ can refer to a soft drink or to a vegetable.
A number of food classification and description systems have been developed, including LanguaL (‘Langua aLimentaria’ or ‘language of food’). It is an automated method for describing, capturing and retrieving data about food. The thesaurus provides a standardised language for describing foods, specifically for classifying food products for information retrieval. LanguaL is based on the concept that:
- Any food (or food product) can be systematically described by a combination of characteristics
- These characteristics can be categorised into viewpoints and coded for computer processing
- The resulting viewpoint/characteristic codes can be used to retrieve data about the food from external databases
LanguaL is a multilingual thesaural system using facetted classification. Each food is described by a set of standard, controlled terms chosen from facets characteristic of the nutritional and/or hygienic quality of a food, as for example the biological origin, the methods of cooking and conservation, and technological treatments. It is therefore particularly useful for exchange of data between FCDB compilers and also for users who are comparing the nutrient content of equivalent foods across a range of international FCDBs.
In the LanguaL system, each food is described by a set of standard, controlled terms chosen from facets that describe different characteristics of foods. These include food origin (e.g. plant, animal, chemical; part of plant or animal used), physical attributes (e.g. physical state or form), processing (e.g. heat treatment, preservation method), cooking method, packaging and geographic origin.
A hierarchical structure is used so that information can be retrieved at varying levels of specificity depending on the user’s requirements. For example, a user might require information on breakfast cereals. Depending on the level of detail needed, it would be possible to search, for example, for corn-based breakfast cereals, corn-based breakfast cereals with added sucrose, or corn-based breakfast cereals with added sucrose and fortified with vitamins and iron.