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 Updated 2017-04-02

 Value - the content of a component in a food

In the table metaphor (see the Main Entities), the value holds the actual numercal information about a certain component in a certain food. There are several kinds of attributes or metadata connected to a value, like unit, matrix unit, how the value was derived (value type), etc. To ensure proper use of the data, it is important that the food composition data compiler records this information very precisely.

Furthermore, there are several numerical restrictions on how a certain value can be presented.

Value documentation

The value documentation concerns all the metadata refering to and describing how the numerical value was derived. These issues concern units, how the value was derived (analytical, calculated, estimated, assumed zero, etc.), indication of data quality, etc. Other issues concern where the data come from (see also Reference).

In the EuroFIR context, the mandatory ducumentation that must follow a value is a component identifier, unit/matrix unit, value type, method type, acquisition type and reference.

In the FAO/INFOODS context, component identifiers (tagnames) include some of the information above, e.g. some analytical information.

For more information on the documentation of values, see Value documentation.

The uncertainty of a value determine how the value should be presented - significant digits

It is often a point of discussion how many decimals a certain component value should be presented with, and very often a decision is taken to use a fixed number of decimals for a certain nutrient. This is however a very dubious approach and from a scientific point of view not recommendable.

How precisely a numerical value can be presented depends on the uncertainty with which the value has been produced. The uncertainty of a component value depends among other things on the natural variation of the content of the component in food, sampling issues like representativity and number of samples, and analytical uncertainty. Summed up, the realtive uncertainty of a specific value can easily amount to 20-30%, which leaves us with values that correctly only can be represented with two significant digits at the most.

In short, the usual uncertainty of compositional values predicts that no more than three significant digits. What this means in terms of the numerical representation and the number of decimals is shown in the following table:

Significant digits
*   Round off to the nearest 10.                                  
** Change unit, if there are many values at this level.  

Please note that the rules given in the table above are practical and pragmatic rules and not strictly scientific. For example, a value of 1150 should with 3 significant digits correctly be shown as 1.15*103 (scientific notation). This is however not very readable, especially in a food composition table or database.
Instead the rounding of of the value to the nearest 10 is a pragmatic and practical solution.

Also note, that a 0 (zero) should never be given as a 0.0, 0.00 nor 0.000, which is often seen. A zero should be given as a 0. Similarly, a missing value should not be given or represented by a zero (0). Although it is frequently seen.

For more information on significant digits and numerical representation in numerical databases, see the page on Significant digits.

How to handle values below limits of quantification or determination

In food composition data work it is often a issue that values fall below the level of quantification (LOQ) or limit of determination (LOD) for the methodology used to determine the content of one or more components. In food composition tables, it has been a tradition to indicate such content with a trace, "tr".

In modern use of food composition data, this is however no longer a user-friendly approach, and it is especially of concern, when the data are being used in connection with exposure studies or dietary surveys where missing values is not well seen the fact that even small amounts of a component in a food, which is eaten or drunk in large amounts, have an inpact on the intake of the component.

In order to be able to calculate the contribution of the component, it is evident that a value is needed. It is known that the value is not zero in the food. So the amount must be bigger than 0 (zero), but it is not known what the real value is, because it below the LOQ/LOD. The issue was dealt with in the WHO GEMS/Food-EURO working group, which recommended - dependent on the actual circumstances - to represent values below LOD by LOD/2.

For more information, see the references below.



New release of the NZ Food Composition Database

The 2017 release of the NZFCD products are now available on the NZFCD website.
A farm to fork ontology.

FoodOn is a new ontology built to represent entities which bear a “food role”, currently based largely on LanguaL.
For more information,
see the FoodOn site.
Indian food composition tables 2017.

The Indian food composition tables 2017 have been published. A PDF copy of the tables can be downloaded.
For more information see the Indian FCDB site.
FAO/INFOODS dataset on pulses published.

The FAO/INFOODS Global food composition database for pulses – version 1.0 (uPulses1.0) has been published.
For more information, see the FAO/INFOODS website.