Literature DB >> 14575658

Spatially explicit modelling of transgenic maize pollen dispersal and cross-pollination.

Christine Loos1, Ralf Seppelt, Sara Meier-Bethke, Joachim Schiemann, Otto Richter.   

Abstract

Modelling of pollen dispersal and cross-pollination is of great importance for the ongoing discussion on thresholds for the adventitious presence of genetically modified material in food and feed. Two different modelling approaches for pollen dispersal are used to simulate the cross-pollination rate of pollen emerged from an adjacent transgenic crop field. The models are applied to cross-pollination data from field experiments with transgenic maize (Zea mays). The data were generated by an experimental setup specifically designed to suit the demands of mathematical modelling. First a Gaussian plume model is used for the simulation of pollen transport in and from plant canopies. This is a semiempirical approach combining the atmospheric diffusion equation and Lagrangian methodology. The second model is derived from the localised near field (LNF) theory and based on the physical processes in the canopy. Both modelling approaches prove to be appropriate for the simulation of the cross-pollination rates at distances of about 7.5m and more from the transgene source. The simulation of the cross-pollination rate is less precise at the edge of the source plot especially with the LNF theory. However, the simulation results lie within the range of variability of the observations. Concluding can be pointed out that both models might be adapted to other pollen dispersal experiments of different crops and plot sizes.

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Year:  2003        PMID: 14575658     DOI: 10.1016/s0022-5193(03)00243-1

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  9 in total

1.  Impact of gene stacking on gene flow: the case of maize.

Authors:  Lénaïc Paul; Frédérique Angevin; Cécile Collonnier; Antoine Messéan
Journal:  Transgenic Res       Date:  2011-06-17       Impact factor: 2.788

2.  The effect of flowering time and distance between pollen source and recipient on maize.

Authors:  Shuo-Cheng Nieh; Wen-Shin Lin; Yung-Heng Hsu; Guang-Jauh Shieh; Bo-Jein Kuo
Journal:  GM Crops Food       Date:  2014       Impact factor: 3.074

3.  Pollen flow of wheat under natural conditions in the Huanghuai River Wheat Region, China.

Authors:  Ai-Qing Sun; Chun-Qing Zhang; Cheng-Lai Wu; Qing-Rong Gao
Journal:  GM Crops Food       Date:  2015-02-06       Impact factor: 3.074

4.  Establishment and optimization of a regionally applicable maize gene-flow model.

Authors:  Ning Hu; Jichao Hu; Xiaodong Jiang; Zongzhi Lu; Yufa Peng; Wanlong Chen; Kemin Yao; Ming Zhang; Shirong Jia; Xinwu Pei; Weihong Luo
Journal:  Transgenic Res       Date:  2014-06-25       Impact factor: 2.788

5.  Model-based calculating tool for pollen-mediated gene flow frequencies in plants.

Authors:  Wang Lei; Lu Bao-Rong
Journal:  AoB Plants       Date:  2016-12-30       Impact factor: 3.276

6.  Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia.

Authors:  Yuan-Chih Su; Cheng-Bin Lee; Tien-Joung Yiu; Bo-Jein Kuo
Journal:  Sci Rep       Date:  2021-11-12       Impact factor: 4.379

7.  Application of the maximum threshold distances to reduce gene flow frequency in the coexistence between genetically modified (GM) and non-GM maize.

Authors:  Ning Hu; Ji-Chao Hu; Xiao-Dong Jiang; Wei Xiao; Ke-Min Yao; Liang Li; Xin-Hai Li; Xin-Wu Pei
Journal:  Evol Appl       Date:  2022-03-11       Impact factor: 5.183

8.  Modeling gene flow distribution within conventional fields and development of a simplified sampling method to quantify adventitious GM contents in maize.

Authors:  Enric Melé; Anna Nadal; Joaquima Messeguer; Marina Melé-Messeguer; Montserrat Palaudelmàs; Gisela Peñas; Xavier Piferrer; Gemma Capellades; Joan Serra; Maria Pla
Journal:  Sci Rep       Date:  2015-11-24       Impact factor: 4.379

9.  High-Resolution Gene Flow Model for Assessing Environmental Impacts of Transgene Escape Based on Biological Parameters and Wind Speed.

Authors:  Lei Wang; Patsy Haccou; Bao-Rong Lu
Journal:  PLoS One       Date:  2016-03-09       Impact factor: 3.240

  9 in total

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