Smith D L, Hollowell J E, Isleib T G, Shew B B
Department of Plant Pathology.
Department of Crop Science, North Carolina State University, Raleigh 27695.
Plant Dis. 2007 Nov;91(11):1436-1444. doi: 10.1094/PDIS-91-11-1436.
In North Carolina, losses due to Sclerotinia blight of peanut, caused by the fungus Sclerotinia minor, are an estimated 1 to 4 million dollars annually. In general, peanut (Arachis hypogaea) is very susceptible to Sclerotinia blight, but some partially resistant virginia-type cultivars are available. Up to three fungicide applications per season are necessary to maintain a healthy crop in years highly favorable for disease development. Improved prediction of epidemic initiation and identification of periods when fungicides are not required would increase fungicide efficiency and reduce production costs on resistant and susceptible cultivars. A Sclerotinia blight disease model was developed using regression strategies in an effort to describe the relationships between modeled environmental variables and disease increase. Changes in incremental disease incidence (% of newly infected plants of the total plant population per plot) for the 2002-2005 growing seasons were statistically transformed and described using 5-day moving averages of modeled site-specific weather variables (localized, mathematical estimations of weather data derived at a remote location) obtained from SkyBit (ZedX, Inc.). Variables in the regression to describe the Sclerotinia blight disease index included: mean relative humidity (linear and quadratic), mean soil temperature (quadratic), maximum air temperature (linear and quadratic), maximum relative humidity (linear and quadratic), minimum air temperature (linear and quadratic), minimum relative humidity (linear and quadratic), and minimum soil temperature (linear and quadratic). The model explained approximately 50% of the variability in Sclerotinia blight index over 4 years of field research in eight environments. The relationships between weather variables and Sclerotinia blight index were independent of host partial resistance. Linear regression models were used to describe progress of Sclerotinia blight on cultivars and breeding lines with varying levels of partial resistance. Resistance affected the rate of disease progress, but not disease onset. The results of this study will be used to develop site- and cultivar-specific spray advisories for Sclerotinia blight.
在北卡罗来纳州，由小核盘菌引起的花生菌核病造成的损失估计每年达100万至400万美元。一般来说，花生（落花生）对菌核病非常敏感，但有一些部分抗性的弗吉尼亚型品种。在病害极易发生的年份，每季最多需要施用三次杀菌剂才能维持作物健康生长。改进对病害流行起始的预测以及确定无需施用杀菌剂的时期，将提高杀菌剂的使用效率，并降低抗性和敏感品种的生产成本。利用回归策略建立了一个菌核病病害模型，以描述模拟环境变量与病害增长之间的关系。对2002 - 2005年生长季的病情增量发生率（每块地新感染植株占总植株数的百分比）变化进行了统计转换，并使用从SkyBit（ZedX公司）获得的特定地点模拟天气变量（远程获取的天气数据的本地化数学估计值）的5天移动平均值进行描述。描述菌核病病害指数的回归变量包括：平均相对湿度（线性和二次项）、平均土壤温度（二次项）、最高气温（线性和二次项）、最高相对湿度（线性和二次项）、最低气温（线性和二次项）、最低相对湿度（线性和二次项）以及最低土壤温度（线性和二次项）。在八个环境中进行的为期4年的田间研究中，该模型解释了菌核病病害指数约50%的变异性。天气变量与菌核病病害指数之间的关系与寄主的部分抗性无关。使用线性回归模型来描述不同部分抗性水平的品种和育种系上菌核病的发病进程。抗性影响病害进展速度，但不影响发病起始。本研究结果将用于制定针对菌核病的特定地点和品种的施药建议。
