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

PARALLEL SESSION 4C: CROP PRODUCTION SYSTEMS 8 th Int. Conference on LCA in the
Agri-Food Sector, 1-4 Oct 2012
Figure 7. Inter-field variability regarding the climate change and acidification indicators
With 0.42 kg eq.CO2 / kg wheat grain, improved wheat has a higher potential impact on climate change
than standard winter wheat (0.35 kg eq.CO2 / kg grain wheat). According to the statistical Student test this
difference is significant (p-value = 0.0170).
This difference can be explained by the fact that, having higher protein content grains, improver wheat
needs more nitrogen to fill up its grains. When the functional unit is 110g protein rather than 1 kg of wheat
grain, conclusions on the potential impact on climate change of improver wheat and standard winter wheat
change: their respective GHG emissions are 0.36 and 0.40 kg eq CO2 / 110g protein.
On the other hand, when considering terrestrial acidification potential, improver wheat has a lower potential
impact than standard winter wheat: its emissions are 4.4.10-3 kg eq. SO2 / kg grain when standard winter
wheat ones stand at 4.9.10-3 kg eq. SO2 / kg grain wheat. This better result of improver wheat is due to the
use of fertilisers that have lower NH3-emission rates (ammonium nitrate essentially). In this case, the fertiliser
type enables to make up for the bigger use of fertilisers (reported to 1 kg wheat grain) by improver
wheat. The change of the fertiliser type constitutes a key lever for improving the acidification indicator. It is
also true for the climate change and energy consumption indicators (Berthoud and Rocca, 2011). According
to the statistical Student test this difference is not significant (p-value = 0.7156).
4. Discussion
Carrying out such analyses at the field scale allows for more accurate results than at larger scales. This is
especially true where cooperatives are involved, as they are key players who can thus put their agroenvironmental
knowledge to good use.
However the main benefit of a field scale approach is to offer a wide range of improvement possibilities.
For instance in another case study, the results of which could not be detailed here and which is separately
published, we worked specifically on the ecotoxicity indicator. We were able to simulate a 50% decrease of
the cooperative’s mean impact regarding this indicator by identifying the most impacting practices (in this
case, pesticide use) and substituting them for less impacting ones (Berthoud et al., 2011). There indeed lie
the stakes of the variability study: to identify the most impacting practices in order to improve them, as well
as to identify good practices.
The main limit to a field scale approach, however, is that it requires flux and impacts modelling tools and
methods to be sufficiently practice-sensitive. To date, it is not (or to the least, not enough) the case for some
indicators such as freshwater eutrophication.
5. Conclusion
What makes it particularly interesting to work on agricultural field practices is to address variability. The
knowledge of this variability is a crucial asset: understanding, identifying the most and the less impacting
practices, progressing towards an eco-conception of agricultural practices or even towards a very early consideration
of potential impacts through the agricultural advising stage by informing advisers of the potential
impacts of the agronomical solutions they recommend.
Similar studies have been carried out by InVivo Agro Solutions, with real data for agricultural practices,
on other crops, such as barley, maize, etc, thus creating an environmental information system. Moreover,
each of these studies will be conducted during 5 years, allowing for the cooperatives to have an inter-annual
view of their impacts.
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