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dc.contributorBo-Jein Kuoen_US
dc.contributor.authorJung-Chiao Hungen_US
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dc.description.abstract如基因改造 (genetically modified, GM) 作物與野生近緣種、栽培種與雜草發生雜交,可能會對自然環境與生物多樣性造成很大的影響。水稻為世界上重要的作物之一,超過50%的世界人口以稻米為主食。儘管水稻為自交作物,但仍會藉由風傳播花粉而進行基因流動,造成non-GM水稻受到汙染。目前台灣並未開放種植GM作物,因此必須進行相關試驗,以提供決策者研擬GM水稻與non-GM水稻的共存規範之參考。 為模擬GM水稻之花粉飄散,本研究於2012年在桃園縣新屋鄉行政院農業委員會桃園區改良場進行田間試驗,其中試驗田區配置設計為一同心圓。花粉貢獻親為非糯性水稻品種台稉14號,用以模擬GM水稻並種植於同心圓田區中央,而花粉接受親為糯性水稻品種桃園糯2號,模擬non-GM水稻,並將其種植於同心圓周圍環形田區。利用糯稻與非糯稻的碘液呈色反應,判定是否發生異交。所蒐集到的試驗資料分別使用非線性log/log模式、高斯煙羽模式及M5'模式樹建立花粉飄散模式,並使用CART決策樹及Logistic回歸模式,分別將實際試驗資料依照不同的劃分方法分類為GF值'在安全範圍內'與'超標'等類別,並計算其正確分類率。 研究結果顯示,在進行基因流動頻度的估計上,M5'模式樹的配適結果最佳,其次為高斯煙羽模式,最後為log/log模式;針對試驗資料進行分類的結果中,CART決策樹的表現比Logistic回歸的結果佳。而在M5'模式樹與CART決策樹在樹之建構上,均以花粉貢獻親與接受親間的直線距離作為第一層節點分割的解釋變數;而花粉貢獻親與接受親間的直線距離亦為Logistic回歸模式中的重要變數,表示距離為影響水稻基因流動頻度的重要因子。而基因流動頻度在試驗地點之不同方位試區的表現情形,會受到抽穗期間盛行風向所影響;M5'模式樹與CART決策樹挑選風通道長度或適宜風向比例作為分類依據;而適宜風向比例與盛行風向之平均風速則為Logistic回歸模式中之重要變數,由此可知,風向與風速確實為影響基因流動頻度之重要因子。因此,除考慮抽穗期間之盛行風向與風速,並透過隔離距離的設置可降低GM基因汙染情形。利用Logistic回歸模式進行的隔離距離估計,發現當標示門檻值分別為0.1%、0.3%及0.5%時,所需的隔離距離分別為11.1 m、6 m及5.7 m,而此隔離距離可應用於微氣候條件與桃園新屋地區相近之地區。zh_TW
dc.description.abstractIf genetically modified (GM) crops outcross with wild relatives, cultivars and weeds, great impacts on the natural environment and biodiversity may arise. Rice is one of the most important crops in the world and the staple food for over half of the global population. Although rice is a self-pollinated crop, its transgenes can result in gene flow through the pollen dispersal. Up to now, no GM crop could be planted legally in the open field in Taiwan. Therefore, in order to provide the related information on the regulations of coexistence between GM and non-GM rice to the decision-maker, it is important to conduct the experiments of gene flow for GM rice. To simulate the pollen dispersal of GM rice, the field experiments were conducted at Taoyuan District Agricultural Research and Extension Station in Taoyuan County, Taiwan in 2012. The field experiments were a concentric circle design. In the center of the field, the non-glutinous rice named 'Taikeng 14' was planted as the pollen donor. In addition, the glutinous rice named 'Taoyuan glutinous 2' was planted as the pollen recipient in the circular ring of the field. The iodine test of glutinous and non-glutinous rice was used to distinguish the outcross seeds and self-pollinating seeds. Not only did our study use the log/log model, Gaussian plume model and M5' model tree to establish the pollen dispersal model in rice, but the actual gene flow frequency was classified into 'safe' and 'excessive' by different methods and the entire accuracy rate of CART decision tree and Logistic regression model was also calculated. According to the results, the fitting ability of M5' model tree was the best in estimating gene flow frequency, following by the Gaussian plume model and log/log model. Additionally, the performance of CART decision tree was better than Logistic regression model. As expected, the distance between the edge of pollen donor plot and pollen receipt was the first explanatory variable in M5' model tree and CART decision tree. Similarly, it was also the important variable in Logistic regression model suggesting that distance was the important factor of gene flow frequency in rice. Furthermore, the prevailing wind direction in flowering period influenced the gene flow frequency in different directions of the experimental site. Wind tunnel and appropriated wind percent were selected as the classification variables. Similarly, the appropriated wind percent and average wind speed of prevailing wind were also the important variables in the Logistic regression model. These results suggested that wind direction and speed were indeed the important factors influencing the gene flow frequency in rice. Therefore, in order to reduce the gene flow frequency, the prevailing wind direction and speed during the flowering period should be concerned first, and the isolation distance could be set up. If the labeling thresholds were set at 0.1%, 0.3% and 0.5%, the isolation distances calculated by the Logistic regression model were 11.1 m, 6 m and 5.7 m, respectively. Moreover, the isolation distance can be applied to the area which microclimate is similar to Sinwu Township, Taoyuan County.en_US
dc.description.tableofcontents摘要 i Abstract iii 目次 v 表目次 viii 圖目次 xii 第一章 緒言 1 第二章 前人研究 4 一、全球基因改造作物之概述 4 二、稻 5 三、影響水稻花粉調控之基因流動之因子 10 (一) 風速與風向 11 (二) 距離 19 (三) 開花期重疊日數 29 (四) 花粉貢獻親與花粉接受親族群之不同 32 第三章 材料與方法 35 一、試驗田區設計 35 二、種植材料與種植日期 35 三、栽培管理 36 四、開花期氣候監測 36 五、田間抽樣與資料蒐集 36 六、花粉流動模式 37 (一) log/log模式 37 (二) 高斯煙羽模式 38 (三) 決策樹與模式樹 41 1. 決策樹與模式樹之建構 41 2. 統計分析 46 (四) Logistic回歸模式 47 第四章 試驗結果 60 一、氣象監測結果 60 二、花粉飄散趨勢 60 三、花粉飄散模式配適結果 63 (一) log/log模式 63 (二) 高斯煙羽模式 64 (三) M5'模式樹 66 (四) 決策樹 69 (五) Logistic回歸模式 71 第五章 綜合討論 127 參考文獻 135zh_TW
dc.subjectpollen-mediated gene flowen_US
dc.subjectOryza sativa L.en_US
dc.subjectdata miningen_US
dc.subjectgussian plume modelen_US
dc.subjectCART decision treeen_US
dc.subjectlogistic regression modelen_US
dc.titleEstablishing the pollen-mediated gene flow model for the simulated GM rice: a case study for Sinwu Township, Taoyuan Countyen_US
dc.typeThesis and Dissertationen_US
item.openairetypeThesis and Dissertation-
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