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Spatially isolating genetically modified (GM) maize fields from non-GM maize
fields is a robust on-farm measure to keep the adventitious presence of GM
material in the harvest of neighboring fields due to cross-fertilizations
below the European labeling threshold of 0.9%. However, the
implementation of mandatory and rigid isolation perimeters can affect the
farmers' freedom of choice to grow GM maize on their fields if neighboring
farmers do not concur with their respective cropping intentions and crop
plans. To minimize the presence of non-GM maize within isolation perimeters
implemented around GM maize fields, a method was developed for optimally
allocating GM maize to a particular set of fields. Using a Geographic
Information System dataset and Monte Carlo analyses, three scenarios were
tested in a maize cultivation area with a low maize share in Flanders
(Belgium). It was assumed that some farmers would act in collaboration by
sharing the allocation of all their arable land for the cultivation of GM
maize. From the large number of possible allocations of GM maize to any
field of the shared pool of arable land, the best field combinations were
selected. Compared to a random allocation of GM maize, the best field
combinations made it possible to reduce spatial co-existence problems, since
at least two times less non-GM maize fields and their corresponding farmers
occurred within the implemented isolation perimeters. In the selected field
sets, the mean field size was always larger than the mean field size of the
common pool of arable land. These preliminary data confirm that the optimal
allocation of GM maize over the landscape might theoretically be a valuable
option to facilitate the implementation of rigid isolation perimeters
imposed by law.
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