Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/89476
標題: Using Gaussian plume– exponential approach to simulate the pollen-mediated gene flow (PMGF) of maize in the landscape scale: a case study for Puzih City, Chiayi County
利用高斯煙羽-指數法模擬地景尺度下玉米花粉調控之基因流動 -以嘉義朴子地區為例
作者: 余昇驊
Sheng-Hua Yu
關鍵字: GM;non-GM;GPM;gene flow;maize pollen dispersal;coexistence;基改;非基改;高斯煙羽模式;基因流動;玉米花粉飄散;共存
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摘要: 
基因改造(genetically modified, GM)玉米(Zea mays L.),為典型的風媒作物,目前已知花粉調控的基因流動(pollen-mediated gene flow, PMGF)為基因改造玉米基因流動的主要途徑,由於目前沒有確切證據可以證明基因改造作物對人體健康無害,且台灣目前仍未有任何可合法種植的GM作物,因此必須在合法種植之前,進行玉米PMGF範圍的模擬,並探討未來在台灣有合法種植的GM作物進行商業生產後,其與非GM作物之間共存方法的實用性。
為模擬GM玉米的PMGF在台灣朴子玉米栽培區的實際影響範圍,本研究利用在朴子地區進行二年三期作平行田區玉米花粉飄散(pollen dispersal)試驗資料,試驗乃模擬在最差條件(worst-case)下的表現,試驗以黑美珍(black pearl)品種模擬為GM玉米的花粉貢獻親,而模擬為非GM玉米的花粉接受親,則選用台南23號(Tainan 23),兩者皆為台灣農民常用的商業品種,本研究於收穫期間對接受親田區進行抽樣調查,並以花粉直感效應判斷是否發生異交(cross-pollination, CP)並透過計算汙染粒所佔比例的方式以量化異交率的觀測值;異交率的估計值則透過網格化田區,並以高斯煙羽模式(Gaussian plume model, GPM)配合開花期間的平均風速與最大瞬間風速的風向資料,計算網格之間貢獻親的相對花粉濃度(relative pollen concentration, RPC),最後再以指數模式將貢獻親RPC轉換為異交率,以上估計方法稱之為高斯煙羽-指數法,模式經由十折交叉驗證後,所得之相關係數的平均值大於0.85,誤差均方根的平均值則小於0.03,代表模式具有良好的配適能力。
本研究利用高斯煙羽-指數法,估計台灣農業栽培地景中玉米的PMGF,並模擬隔離周界的實施、去除保護行以及集中種植GM三種共存措施,所得結論為:由於台灣農業栽培田區平均面積小且排列緊密,因此不適宜使用隔離周界作為共存方法,本研究建議採用複合方式的隔離措施,將GM玉米田區集中種植於non-GM玉米田區的下風處,並且為了得到保守的結論,建議同時將non-GM田區直接面對GM田區邊界20 m的部分,作為GM種子收穫,剩餘的non-GM田區若面積大於1 ha,經由收穫後並均勻混和,理論上平均異交率可降低至歐盟門檻值0.9%以下。

The genetically modified maize (GM maize) is the wind-pollinated crop. It is reported sure that the pollen-mediated gene flow (PMGF) is the major way in maize gene flow. Until now, there is no evidence to prove that the GM food is harmless in human health. Because no GM crops can legally planted in the open field in Taiwan, it is important to model the PMGF of maize and simulate the coexistence measure before the GM crops are allowed to be planted in Taiwan.
To investigate the influence of gene flow of maize in Taiwan, our study assessed the maize pollen dispersal experiments in the worst-case for modeling the PMGF between pollen donor and recipient field at Puzih in 2009 and 2010. The donor field used the commercial variety named Black pearl and the recipient field used Tainan No. 23. Both varieties were the popular commercial varieties in Taiwan. At harvest, we sampled the tassels at the recipient field and quantified the cross-pollination (CP) rate in terms of the proportion of contaminated kernels by the Xenia effect. To predict the CP % in the real agricultural landscape, our study used the Gaussian plume model (GPM) to calculate the relative pollen concentration in the gridded by means of inputting the hourly mean wind speed (m/s) and the hourly wind direction of instantaneous wind speed. Finally, we used the exponential model to transform the relative pollen concentration to CP %. Our study called this estimated method as Gaussian-exponential approach. According to the 10-fold cross-validation, the correlation coefficient was greater than 0.85 and the RMSE was lower than 0.03, confirming the ability of the model fitting.
Our study used the Gaussian-exponential approach to predict maize PMGF in the landscape scale, and simulate three coexistence measures, e.g. implemented isolation perimeters, separated border rows and clustering planted GM maize. However, the average field area of the agriculture landscape in Taiwan was too small to implement the isolation perimeter as the coexistence measure. Our study suggested that implemented a complex coexistence measure by clustering GM field at the downwind area and harvested GM-facing rows in 20m separately. If the remained area of the non-GM field was larger than 1 ha, theoretically, the average CP % of the non-GM field could be lower than the EU threshold 0.9%.
URI: http://hdl.handle.net/11455/89476
其他識別: U0005-2201201415490900
Rights: 同意授權瀏覽/列印電子全文服務,2017-01-24起公開。
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