LCA Food 2012 in Saint Malo, France! - Manifestations et colloques ...

PARALLEL SESSION 5A: FOOD LABELLING 8 th Int. Conference on LCA in the
Agri-Food Sector, 1-4 Oct 2012
Table 1. Example of product groups
Feature Non-processed food Processed food
Same product, different tastes - Sterilised full-cream milk (choco- - Chicken snack in 110,
late, pineapple, lychee, lemon taste) 250, 500 grams
Same product, different sizes - Canned sliced pineapple in 8, 16, - Instant noodles in 55, 85,
20 ounces’ pack
210 grams’ pack
Same product, with at least 90% of
- Instant noodles in differ-
the total weight being the same and
ent flavours (tom yum
the rest of the ingredients will not
kung, minced pork, roasted
cause a difference in the total carbon
footprint value of more than 5%
duck, etc.)
3.2.4. Functional unit
It is generally agreed at the conceptual level that the unit of analysis should not be the sold unit but reflecting
the functional unit of product. The discussion on the function of food has not yet been settled; there
is not yet a common consensus on which unit would be the best choice to facilitate the product comparison.
The nutrition level received a wide debate, especially the edible protein from different types of meat which
could favour one product over another. For instance, the carbon footprint of tilapia will be much lower than
other meat sources if the functional unit is based on the content of edible protein (Table 2). More importantly,
whereas the whole fish is eaten in Asian countries, in Europe, people prefer having only the fillets; the
functional unit based on whole fish and fillet cannot be compared in this case. For livestock, the proposed
unit is the standard unit in terms of volume or mass, e.g. meat in 1 kg, milk in 1 litre and egg is per egg according
to their size and weight based on the national standard.
Table 2. Comparison of different meats with tilapia, at the farm gate, based on different functional unit
Aquatic products
Carbon footprint value Carbon footprint value
(Reference)
(kg CO2e/250 g of live weight) (kg CO2e/100 g of protein)
Thai tilapia
(Tessa and Mungkung, 2011)
0.55 0.92
French trout
(Papatryphon et al., 2003)
1.13 2.20
Canadian salmon
(Pelletier et al., 2009)
0.82 1.65
Norwegian salmon
(Ellingsen et al., 2009)
0.75 1.51
3.2.5. Data collection
The focus of companies was around the issues of data collection, such as the primary and secondary data
requirements (i.e. which ones should be collected directly and which ones sourced from literature). The difficulties
in data collection in the field vary due to different levels of data recording systems in place. The companies
with proper data recording systems see this as an advantage; while those with poor data recording
systems see this as the way out to easily substitute with the secondary data. The quality of primary and secondary
data was discussed at length, as the industry is concerned about this. It can happen that the secondary
data has better quality than primary data or vice versa. This is particularly of concern among Thai food companies
as the food database is being developed and it is in a very early stage of development; as a result, several
substitute data are used when there is no related database; this could be a disadvantage as compared to
the countries where the databases are well developed.
454