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

GROUP 4, SESSION B: CROP PRODUCTION SYSTEMS 8 th Int. Conference on LCA in the
Agri-Food Sector, 1-4 Oct 2012
810
104. Using spatial data to define industry sub-sectors for Australian
wheat
Gonzalo Mata 1,* , Sandra Eady 2 , Tim Grant 3
1 2
CSIRO Animal Food and Health Sciences, Private Bag 5, Wembley WA 6913, Australia, CSIRO Animal
Food and Health Sciences, Locked Bag 1, Armidale NSW 2350, Australia, 3 Life Cycle Strategies Pty Ltd,
125 Swanston Street, Melbourne Vic 3000, Australia, Corresponding author. E-mail:
Gonzalo.Mata@csiro.au
A Life Cycle Inventory (LCI) for Australian agriculture is currently in development. Within each industry
(e.g. crops, livestock, horticulture) sub-sectors need to be identified so that the LCI can be structured in such
a way users can identify the most appropriate on-farm production process for their supply chain. For instance,
major users of Australian wheat purchase grain based on grade (grain hardness and protein content)
rather than the region or production system employed to produce the wheat. However, primary sources of
information to describe production data don’t necessarily relate well to grade classifications, as grain quality
expectations can be affected due to environmental interactions or manipulated through blending of various
sources of grain to meet market specifications post-farm gate.
Therefore, in developing a national inventory for wheat it is necessary to define these production systems as
regional sub-sectors of the industry, decide how many sub-sectors are needed to represent important differences
in environmental impacts, and from these systems construct inventory processes that have utility to the
downstream users of Australian wheat.
This paper will explore the GIS methodology needed to define regional sub-sectors for the Australian wheat
industry, using a combination of industry expertise and spatial data on land use, soil types, rainfall and other
available statistical boundaries and biophysical parameters to capture regional differences which translate
into differentiated production systems with differentiated environmental impacts.