Application of an atmospheric gene flow model for assessing environmental risks from transgenic corn crops

摘要

Gene flow data from experiments under limited environmental conditions (e.g. wind speed and direction, atmospheric stability) have only provided limited information for gene flow risk management. It is necessary to apply models to predict the gene flow under a complete set of possible environmental conditions to inform farmers, seed companies, government agencies, and researchers about the risks and potential prevention and precaution methods. In this paper, the previous validated gene flow model developed by the authors was used to predict gene flow from genetically modified (GM) corn crops. The model was used to simulate potential gene flow from GM corn sources of different sizes from one plant area of 0.1 m2 to an area 3.1×106 m2 under normal weather conditions. In addition, the model was also used to predict the potential gene flow for different source strengths, atmospheric conditions, buffer heights, buffer field sizes, and pollen settling speeds from 10,000 m2 sources. The model simulations have provided gene flow information for risk management under the above conditions and have shown that the source sizes, source strengths, buffer heights, buffer sizes, atmospheric conditions, and pollen settling speeds had important effects on gene flow. While the atmospheric conditions and pollen settling speeds cannot be controlled, choosing appropriate buffer heights and sizes will effectively prevent gene flow. The lost seed control is crucial to limit gene flow because even a GM corn plant can result in a grand total deposition flux of 646,272 grains/m2, an outcrossing ratio of 0.016, and outcrossed seed of 110 kernels/m2 at 0.8 m from the plant in the non-target field under normal atmospheric conditions. Keywords: model, risk management, crops, corn, pollen, gene flow, random walk, outcrossing DOI: 10.3965/j.issn.1934-6344.2010.03.036-042 Citation: Junming Wang, Xiusheng Yang. Application of an atmospheric gene flow model for assessing environmental risks from transgenic corn crops. Int J Agric & Biol Eng, 2010; 3(3): 36.