葉稻熱病病勢進展時間效應之分析

Analysis of the time effect on disease progress of rice leaf blast

10.6715/PPB.200412_46(4).0005

蔣國司(Chiang, K. S.)；黃益田(Huang, Y. T.)

生長曲線模式 ； 病勢進展曲線下之面積 ； 重複測量變方分析 ； growth curve model ； area under the disease progress curve ； repeatedmeasures analysis of variance

植物保護學會會刊

46卷4期（2004 / 12 / 01）

357 - 365

繁體中文

時間效應通常在植物流行病學的研究上扮演著重要的角色，病害在數個時間點被測量之量為病勢進展曲線，它是病害強度對時間點之圖形，為研究流行病學之必要項目。病勢之進展最普遍的方法是使用一個或數個參數來描繪，例如：病害傳染速率就是一個典型的指標，這類的模式稱之為生長曲線模式（growth curve model）；但先前的文獻曾指出其存在的缺失，因此我們使用另外兩種方法來描述、分析及比較病勢之進展，這些方法為「病勢進展曲線下之面積（area under the disease progress curve, AUDPC）」與「重複測量變方分析（repeated measures analysis of variance）」，並以數種測試藥劑對水稻葉稻熱病病勢防治情形數據為例，來評估測試藥劑對葉稻熱病的防治效果，並比較兩種分析方法，所得到的數據差異及其代表的意義。

The time effect often plays an important role in the study of plant epidemiology. Usually, the extent of diseases that occur in a plant population is assessed several times during plant growth. The results are collected and analyzed as a disease progress curve, which is plotted as disease intensity against the time frame of the measurements. Such a disease progress curve is essential for epidemiological research. Traditionally, disease epidemics were described using one or more descriptive parameters, such as the rate of disease progress. The most commonly used model is the growth curve model. However, there are some flaws in this model based on discussions in the previous literature. Therefore, we utilized two other approaches to describe, analyze, and compare epidemics, i.e., the area under the disease progress curve and repeated-measures analysis of variance. We further used a dataset consisting of the effect of several fungicides of rice leaf blast to illustrate these two approaches and evaluate which fungicide was better when used in the field.

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