Gent David H, Mahaffee Walter F, Turechek William W
United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Forage Seed and Cereal Research Unit.
USDA-ARS, Horticultural Crops Research Laboratory, Oregon State University, Department of Botany and Plant Pathology, Corvallis 97331.
Plant Dis. 2006 Nov;90(11):1433-1440. doi: 10.1094/PD-90-1433.
The spatial heterogeneity of the incidence of hop cones with powdery mildew (Podosphaera macularis) was characterized from transect surveys of 41 commercial hop yards in Oregon and Washington from 2000 to 2005. The proportion of sampled cones with powdery mildew ( p) was recorded for each of 221 transects, where N = 60 sampling units of n = 25 cones assessed in each transect according to a cluster sampling strategy. Disease incidence ranged from 0 to 0.92 among all yards and dates. The binomial and beta-binomial frequency distributions were fit to the N sampling units in a transect using maximum likelihood. The estimation procedure converged for 74% of the data sets where p > 0, and a loglikelihood ratio test indicated that the beta-binomial distribution provided a better fit to the data than the binomial distribution for 46% of the data sets, indicating an aggregated pattern of disease. Similarly, the C(α) test indicated that 54% could be described by the beta-binomial distribution. The heterogeneity parameter of the beta-binomial distribution, θ, a measure of variation among sampling units, ranged from 0.01 to 0.20, with a mean of 0.037 and a median of 0.015. Estimates of the index of dispersion ranged from 0.79 to 7.78, with a mean of 1.81 and a median of 1.37, and were significantly greater than 1 for 54% of the data sets. The binary power law provided an excellent fit to the data, with slope and intercept parameters significantly greater than 1, which indicated that heterogeneity varied systematically with the incidence of infected cones. A covariance analysis indicated that the geographic location (region) of the yards and the type of hop cultivar had little effect on heterogeneity; however, the year of sampling significantly influenced the intercept and slope parameters of the binary power law. Significant spatial autocorrelation was detected in only 11% of the data sets, with estimates of first-order autocorrelation, r, ranging from -0.30 to 0.70, with a mean of 0.06 and a median of 0.04; however, correlation was detected in only 20 and 16% of the data sets by median and ordinary runs analysis, respectively. Together, these analyses suggest that the incidence of powdery mildew on cones was slightly aggregated among plants, but patterns of aggregation larger than the sampling unit were rare (20% or less of data sets). Knowledge of the heterogeneity of diseased cones was used to construct fixed sampling curves to precisely estimate the incidence of powdery mildew on cones at varying disease intensities. Use of the sampling curves developed in this research should help to improve sampling methods for disease assessment and management decisions.
2000年至2005年期间，通过对俄勒冈州和华盛顿州41个商业啤酒花种植场的横断面调查，对感染白粉病（黄斑单囊壳菌）的啤酒花球果发病率的空间异质性进行了表征。根据整群抽样策略，在每个横断面的221个样段中，记录了感染白粉病的抽样球果比例（p），每个样段中有N = 60个抽样单元，每个单元包含n = 25个球果。在所有种植场和日期中，病害发病率范围为0至0.92。使用最大似然法将二项分布和贝塔 - 二项分布拟合到横断面中的N个抽样单元。对于74%的p>0的数据集，估计程序收敛，对数似然比检验表明，对于46%的数据集，贝塔 - 二项分布比二项分布更适合数据，表明病害呈聚集模式。同样，C(α)检验表明54%的数据可以用贝塔 - 二项分布描述。贝塔 - 二项分布的异质性参数θ，即抽样单元间变异的度量，范围为0.01至0.20，均值为0.037，中位数为0.015。离散度指数估计值范围为0.79至7.78，均值为1.81，中位数为1.37，54%的数据集显著大于1。二元幂律对数据拟合良好，斜率和截距参数显著大于1，这表明异质性随感染球果的发病率系统变化。协方差分析表明，种植场的地理位置（区域）和啤酒花品种类型对异质性影响较小；然而，采样年份显著影响二元幂律的截距和斜率参数。仅在11%的数据集检测到显著的空间自相关，一阶自相关估计值r范围为 - 0.30至0.70，均值为0.06，中位数为0.04；然而，通过中位数和普通游程分析分别仅在20%和16%的数据集检测到相关性。总之，这些分析表明，球果上白粉病的发病率在植株间略有聚集，但大于抽样单元的聚集模式很少见（20%或更少的数据集）。利用病果的异质性知识构建固定抽样曲线，以精确估计不同病害强度下球果上白粉病的发病率。本研究中开发的抽样曲线的使用应有助于改进病害评估的抽样方法和管理决策。
