Bootstrap simulations for evaluating the model estimation of the extent of cross-pollination in maize at the field-scale level

With the recent advent of genetic engineering, numerous genetically modified (GM) crops have been developed, and field planting has been initiated. In open-environment cultivation, the cross-pollination (CP) of GM crops with wild relatives, conventional crops, and organic crops can occur. This excha...

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Bibliographic Details
Published in:PloS one 2021-05, Vol.16 (5), p.e0249700-e0249700
Main Authors: Kuo, Bo-Jein, Jhong, Yun-Syuan, Yiu, Tien-Joung, Su, Yuan-Chih, Lin, Wen-Shin
Format: Article
Language:English
Subjects:
Agricultural land
Agriculture
Biology and Life Sciences
Corn
Crops
Cross-pollination
Earth Sciences
Empirical models
Engineering and Technology
Environmental factors
Experiments
Field tests
Genetic aspects
Genetically altered foods
Genetically modified crops
Genetically modified organisms
Plant reproduction
Pollen
Pollination
Regional climates
Regulation
Research and Analysis Methods
Small-scale farming
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Summary:With the recent advent of genetic engineering, numerous genetically modified (GM) crops have been developed, and field planting has been initiated. In open-environment cultivation, the cross-pollination (CP) of GM crops with wild relatives, conventional crops, and organic crops can occur. This exchange of genetic material results in the gene flow phenomenon. Consequently, studies of gene flow among GM crops have primarily focused on the extent of CP between the pollen source plot and the adjacent recipient field. In the present study, Black Pearl Waxy Corn (a variety of purple glutinous maize) was used to simulate a GM-maize pollen source. The pollen recipient was Tainan No. 23 Corn (a variety of white glutinous maize). The CP rate (%) was calculated according to the xenia effect on kernel color. We assessed the suitability of common empirical models of pollen-mediated gene flow (PMGF) for GM maize, and the field border (FB) effect of the model was considered for small-scale farming systems in Asia. Field-scale data were used to construct an optimal model for maize PMGF in the maize-producing areas of Chiayi County, southern Taiwan (R.O.C). Moreover, each model was verified through simulation and by using the 95% percentile bootstrap confidence interval length. According to the results, a model incorporating both the distance from the source and the FB can have optimal fitting and predictive abilities.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0249700