Phytopathology. 2006 Oct;96(10):1142-7. doi: 10.1094/PHYTO-96-1142.
ABSTRACT Panicle and shoot blight, caused by a Fusicoccum sp., is one of the major aboveground diseases of pistachio in California. The effects of temperature, number of continuous rainy days in April and May, irrigation system, and incidence of latent infection of the Fusicoccum sp. on severity of panicle and shoot blight of pistachio leaves and fruit have been quantified previously, using data collected from 1999 through 2001. A predictive model for leaves and another model for fruit with good explanatory power were generated. In 2003 and 2004, newly collected data were used to evaluate the two models with non-Bayesian and Bayesian methods. The 95% credible (i.e., confidence) intervals of initial (before modification with non-Bayesian and Bayesian methods) and updated parameter estimates were used to investigate their prognostic validity. In 2003, the non-Bayesian analysis resulted in all parameter estimates, with the exception of cumulative daily mean temperature from 1 June until harvest, having different 95% confidence intervals than the parameter estimates of the original models. In addition, the parameter estimates for drip irrigation for the leaf infection and the parameter estimates for drip irrigation and number of continuous rainy days in April and May for fruit infection were not statistically significant. With Bayesian methods, the reestimated model parameters had overlapping 95% credible intervals with the initial estimated parameters, except for the number of continuous rainy days in April and May. When the two sets of modified parameter estimates were used to predict disease severity, statistically significant (alpha = 0.05) differences between observed and predicted disease severities were found with non-Bayesian analysis for leaf infection in three locations and with Bayesian analysis for fruit infection in one orchard. The parameter estimates were modified again at the end of the 2004 season and were all statistically significant with both non-Bayesian and Bayesian methods. Both sets of parameter estimates gave predictions that were not significantly different from observed disease severity on leaves and fruit in all monitored orchards in 2004. In summary, Bayesian methods gave more consistent results when used to update parameter estimates with new information and yielded predictions not statistically different from observed disease severity in more cases than the non-Bayesian analysis.
摘要 束枯梢病，由一种 Fusicoccum 真菌引起，是加利福尼亚州开心果树地上主要病害之一。此前已经量化了温度、4 月和 5 月连续降雨天数、灌溉系统以及 Fusicoccum 真菌潜伏感染对开心果叶片和果实束枯梢病严重程度的影响，使用的是 1999 年至 2001 年收集的数据。已经生成了具有良好解释能力的叶片预测模型和果实预测模型。2003 年和 2004 年，使用新收集的数据，采用非贝叶斯和贝叶斯方法对这两个模型进行了评估。使用初始（未使用非贝叶斯和贝叶斯方法修改之前）和更新的参数估计的 95%置信区间（即可信度）来研究其预后准确性。2003 年，非贝叶斯分析导致除了从 6 月 1 日到收获期间的累积日平均温度外，所有参数估计的 95%置信区间都与原始模型的参数估计不同。此外，叶片感染的滴灌和果实感染的滴灌和 4 月和 5 月连续降雨天数的参数估计在统计学上都不显著。使用贝叶斯方法，重新估计的模型参数与初始估计参数的 95%置信区间重叠，除了 4 月和 5 月的连续降雨天数外。当使用两组修改后的参数估计来预测疾病严重程度时，非贝叶斯分析在三个地点的叶片感染和贝叶斯分析在一个果园的果实感染中发现了观察到的和预测到的疾病严重程度之间存在统计学上显著（alpha = 0.05）的差异。在 2004 年季节结束时再次修改了参数估计，非贝叶斯和贝叶斯方法都得到了统计学上显著的结果。两组参数估计都在 2004 年所有监测果园的叶片和果实疾病严重程度上做出了预测，且与观察到的疾病严重程度没有显著差异。总之，贝叶斯方法在使用新信息更新参数估计时提供了更一致的结果，并且在更多情况下，与非贝叶斯分析相比，预测结果与观察到的疾病严重程度没有统计学差异。
