Title: LPIS (Land Parcel Identification System) to manage GM/conventional maize co-existence in the EU intensive agricultural region of Lombardy
Authors: PIZZIOL PaoloFASOLINI DanteBRUGNA Elena
Citation: Fourth International Conference on Coexistence between Genetically Modified (GM) and non-GM based agricultural supply chains
Publisher: Prof German Spangenberg
Publication Year: 2009
JRC N°: JRC55065
URI: http://www.gmcc-09.com/wp-content/uploads/pizziol.pdf
http://publications.jrc.ec.europa.eu/repository/handle/JRC55065
Type: Contributions to Conferences
Abstract: Lombardy is a region of Northern Italy, located in the wide and flat Po Valley where arable crops are widespread and agriculture is very intensive. Within this region, the GIS system SIARL (Sistema Informativo Agricolo Regione Lombardia), is used for the registration and management of farmer declarations when applying for EU subsidies. According to provisions under EU law, land use history referring to the past 5 years is required to be documented therefore, land use is registered on the basis of the declaration at the time of its introduction. In particular, farmers applying for public subsidies and growing GM crops are obliged to declare the GM seeds or plants cropped. The aim of the simulation is to quantify in a real agricultural context, the potential GM cropping area in 3 different intensively cropped areas (municipalities) of Lombardy region. This simulation will take into consideration the historical cropping systems, farming systems and size and rotation schemes. Simulations using 3 different cropping distances, allow for gauging the three municipalities¿ availability of agricultural land suitable to for the expansion of maize cropping to GM cultivars. Results indicated area suitability is very limited in 2 simulations out of 3, but the establishment of an ad hoc procedure for crop declaration prior neighbors¿ authorization could extend the suitable area in all simulations. This suggests that, in this case, land use distribution, more than isolation distances and relative maize area percentage, is the most significant variable. These results can assist in outlining the management control strategy and features of the control program to be triggered. This system is can be adapted to other crops.
JRC Institute:Institute for Environment and Sustainability

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