SAMPLE SIZE FOR ASSESS THE LEAF BLAST SEVERITY IN EXPERIMENTS WITH IRRIGATED RICE

ABSTRACT The aim of this study was to determine the sample size needed to assess the severity of leaf blast in rice in experiments with different fungicide treatments. The severity and the area under the disease progress curve data of three chemical disease control treatments carried out in Rio Grande do Sul, were used in the study. Analysis of variance was performed to verify whether the severity of the disease differed between treatments. The spread of disease was was also found to be different between treatments and assessments, using the variance/mean ratio and Morisita index. The spatial distribution of the disease among the treatments and during the evaluations is important for the choice of the equation used to calculate the sample size. The spatial distribution of the disease was not the same across the experiments, and it varied between treatments and evaluations. Thus, we decided to use a formula that was not associated with distributions to indicate the spatial distribution (negative binomial or Poisson) of the disease in the field. The sample size to estimate the average of rice leaf blast severity varied between treatments and evaluations. The area under the disease progress curve is necessary to be determined to reduce the number of samples needed. Thus, it is recommended to assess 293 sheets to estimate severity, and 63 to estimate AUDPC at 20% error.

摘要：本研究旨在明确在开展不同杀菌剂处理的水稻叶瘟病（leaf blast）田间试验时，评估病害严重度所需的样本量。本研究采用了在南里奥格兰德州实施的3种化学防病处理的病害严重度及病情进展曲线下面积（area under the disease progress curve，AUDPC）数据。通过方差分析验证不同处理间的病害严重度是否存在差异；借助方差均比（variance/mean ratio）与莫里西塔指数（Morisita index）分析，发现不同处理及不同调查时期的病害传播特征亦存在差异。病害在不同处理间与调查阶段的空间分布，是选择样本量计算模型方程的核心依据。不同试验间的病害空间分布并不一致，且在不同处理与调查时期间存在差异。因此，本研究选用无需依赖特定分布类型的公式，来表征田间病害的空间分布（负二项分布（negative binomial）或泊松分布（Poisson））。用于估算水稻叶瘟病平均严重度的样本量，在不同处理与调查时期间存在差异。若要缩减所需样本量，需预先确定病情进展曲线下面积（AUDPC）。据此，当允许误差为20%时，建议采集293片稻叶以估算病害严重度，采集63片稻叶以估算AUDPC。