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Using Two-step Model and M5’ Regression Tree to Model the Pollen-Mediated Gene Flow (PMGF) and the Isolation Distance of Maize in Taiwan
Pollen-Mediated Gene Flow (PMGF) model
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|摘要:||隨著生物技術的迅速發展，基因改造(genetically modified, GM)作物的種植面積和產量也在近十年間大幅成長。然而，GM作物對於環境和人體是否造成影響，仍持續引發學者以及消費者的疑慮。因此，為了使農民可以自由選擇種植GM或非GM作物，以及讓消費者得以安心的食用相關產品，如何使GM和非GM作物在田間共存便顯得相當重要。本研究以紫色玉米模擬GM玉米為花粉貢獻親，白色玉米作為花粉接受親，分別在行政院農委會台南區農業改良場朴子分場和農業試驗所進行花粉飄散試驗。並以two-step模式以及M5’回歸樹搭配比較三個非線性模式(exponential模式、log/log模式和log/square模式)以建立花粉飄散模式並進行探討，以期找到適合台灣氣候環境下的花粉飄散模式，因台灣尚未開放商業種植GM作物，相關政策也尚未定案，因此暫用標示於基改商品上的強制標示門檻值探討所需之隔離距離。
研究結果顯示，在朴子地區以M5’回歸樹的配適能力最佳，其次為two-step模式，接著是log/log和log/square模式，其中以exponential模式表現較差。經推算，若當強制標示門檻值為0.9%時，最遠則需要50.25 m(log/log模式)的隔離距離。在霧峰地區，因受到風向的影響，下風處的異交率較上風處為高，其中M5’回歸樹、two-step模式與log/log模式的表現差異不大，並且同樣以exponential模式和log/square模式的配適能力較差。若強制標示門檻值為0.9%，經推算在下風處則需至少4.5 m(two-step模式)的隔離距離。此外，在朴子地區以及霧峰地區的研究結果亦指出，花粉貢獻親和花粉接受親間的最短距離(minidist)均為M5’回歸樹中作為分類的第一個解釋變數，此也與現今常用的花粉飄散模式，如非線性模式、two-step模式和MAPOD等，均以花粉接受親和貢獻親間的最短距離為模式建立的基礎相符。依據研究結果所示，整體而言two-step模式和M5’回歸樹應可作為台灣建立共存決策時花粉飄散模式的參考依據。|
As improvements in biotechnology, the acreage and yield of genetically modified (GM) crops have been increased rapidly during the past decade. However, the influence of the GM crops for environment and human body are concerned by some researchers and customers. Therefore, the coexistence between GM crops and non-GM crops in the open field is important. Such that the farmers can choose one kind of crops to plant freely, including GM crops, non-GM crops, organic crops, or conventional crops. Moreover, customers can purchase freely the relational products. In our study, the purple-glutinous maize was used to simulate the GM crops. The non-GM crops were the white-glutinous maize. The field experiments were conducted at Puzih Branch Station in Puzih in 2009 and 2010 and Taiwan Agricultural Research Institute (TARI) in Wufeng in 2011. To construct the pollen-mediated gene flow (PMGF) models suited the climate and environment conditions in Taiwan (R.O.C), three non-linear models (exponential model, log/log model, log/square model), two-step model and M5’ regression tree were used to compare the fitting capability. Furthermore, based on the different compulsory labeling thresholds, the isolation distance calculated by the PMGF models were also discussed. Accordingly, in Puzih, the fitting ability of M5’ regression tree was better than the other PMGF models, followed by the two-step model and log/log model. The exponential model and log/square model had a poorer fitting performance. When the labeling threshold was set as 0.9%, the farthest isolation distance was 50.25 m calculated by the log/log model. However, in Wufeng, due to the wind direction, the cross pollination rates in the downwind direction were higher than those in the upwind direction. The M5’ regression tree, two-step model and log/log model had the similar performance. The results of the exponential model and log/square model were similar to those obtained from Puzih with the poor fitting performance. Moreover, in the downwind direction, the farthest isolation distance was 4.5 m calculated by the log/log model for sufficing the compulsory labeling threshold of 0.9%. In addition, the results in Puzih and Wufeng also indicated that the distance from the nearest edge of the donor field (minidist) was the first classificatiory variable in M5’ regression tree. It was also an important variable in general PMGF models, e.g. non-linear model, two-step model and MAPOD etc. Finally, the two-step model was better fitting than non-linear models and thence the isolation distance that the two-step model calculated was to conform to agricultural environment in Taiwan. M5’ regression tree is an empirical model, and the results indicate that the fitting capability can perform obviously well as increasing in the number of explanatory variable and sample information. The results indicate that two-step model and M5’ regression tree should be suggested for drafting the coexistence policy in Taiwan (R.O.C).
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