Peanuts grown in tropical, subtropical, and temperate regions are susceptible to stem rot, which is a soil-borne disease caused by Athelia rolfsii. Due to the lack of reliable environmental-based scheduling recommendations, stem rot control relies heavily on fungicides that are applied at predetermined intervals. We conducted inoculated field experiments for six site-years in North Florida, USA, to examine the relationship between germination of A. rolfsii sclerotia: the inoculum, stem rot symptom development in the peanut crop, and environmental factors such as soil temperature (ST), soil moisture, relative humidity (RH), precipitation, evapotranspiration, and solar radiation. Window-pane analysis with hourly and daily environmental data for 5- to 28- day periods before each disease assessment were evaluated to select model predictors using correlation analysis, regularized regression and exhaustive feature selection. Our results indicated that within-canopy ST (at 0.05 m below ground) and RH (at 0.15 m above ground) were the most important environmental variables that influenced the progress of mycelial activity in susceptible peanut crops. Decision tree analysis resulted in an easy-to-interpret one-variable model (Adj R2 0.51, AIC 324, RASE 14.21) or two-variable model (Adj. R2 0.61, AIC 306, RASE 10.95) that provided an action threshold for various disease scenarios based on number of hours of canopy RH above 90% and ST between 25-35°C on a 14-day window. Coupling an existing preseason risk index for stem rot, such as Peanut Rx, with the environmentally based predictors identified in this study would be a logical next step to optimize stem rot management.

中文翻译：

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影响花生茎腐病发展的环境因素：疾病管理的预测因素和行动阈值。

热带、亚热带和温带地区种植的花生容易发生茎腐病，这是一种由罗尔夫氏小叶蛾引起的土传病害。由于缺乏可靠的基于环境的调度建议，茎腐病控制严重依赖于按预定时间间隔施用的杀菌剂。我们在美国佛罗里达州北部进行了六个站点年的接种田间实验，以研究罗氏菌核萌发之间的关系：接种物、花生作物茎腐病症状的发展以及土壤温度（ST）等环境因素、土壤湿度、相对湿度 (RH)、降水量、蒸散量和太阳辐射。在每次疾病评估之前，对 5 至 28 天的每小时和每日环境数据进行窗格分析，以使用相关分析、正则化回归和详尽的特征选择来选择模型预测因子。我们的结果表明，冠层内 ST（地下 0.05 m）和 RH（地上 0.15 m）是影响易感花生作物菌丝体活性进展的最重要的环境变量。决策树分析产生了易于解释的单变量模型（Adj R2 0.51、AIC 324、RASE 14.21）或双变量模型（Adj. R2 0.61、AIC 306、RASE 10.95），为各种情况提供了行动阈值。疾病情景基于 14 天窗口内冠层相对湿度高于 90% 且 ST 处于 25-35°C 之间的小时数。将现有的茎腐病季前风险指数（例如 Peanut Rx）与本研究中确定的基于环境的预测因素结合起来，将是优化茎腐病管理的合理下一步。