North Florida Research and Education Center, University of Florida, Quincy, FL, U.S.A.
Plant Pathology Department, University of Florida, Gainesville, FL, U.S.A.
Phytopathology. 2024 Feb;114(2):393-404. doi: 10.1094/PHYTO-05-23-0164-R. Epub 2024 Feb 26.
Peanuts grown in tropical, subtropical, and temperate regions are susceptible to stem rot, which is a soilborne disease caused by . 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 to examine the relationship between germination of 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 belowground) and RH (at 0.15 m aboveground) 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 (adjusted = 0.51, Akaike information criterion [AIC] = 324, root average square error [RASE] = 14.21) or two-variable model (adjusted = 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 and 35°C in 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. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
在热带、亚热带和温带地区种植的花生容易感染茎腐病,这是一种由引起的土传病害。由于缺乏可靠的基于环境的调度建议,茎腐病的防治主要依赖于在预定间隔时间施用的杀菌剂。我们在佛罗里达州北部进行了为期六年的接种田间试验,以研究 菌核的萌发与花生作物中茎腐病症状发展之间的关系,以及环境因素,如土壤温度(ST)、土壤湿度、相对湿度(RH)、降水、蒸散和太阳辐射。使用相关分析、正则化回归和穷尽特征选择,对每个疾病评估前 5 至 28 天的每小时和每日环境数据进行窗格分析,以选择模型预测因子。我们的结果表明,冠层内 ST(地下 0.05 米处)和 RH(地上 0.15 米处)是影响感病花生作物中菌丝活动进展的最重要环境变量。决策树分析产生了一个易于解释的单变量模型(调整 = 0.51,Akaike 信息准则 [AIC] = 324,根均方误差 [RASE] = 14.21)或两变量模型(调整 = 0.61,AIC = 306,RASE = 10.95),根据 14 天窗口中冠层 RH 超过 90%和 ST 在 25 到 35°C 之间的小时数,为各种疾病情况提供了一个行动阈值。将现有的茎腐病 preseason 风险指数(如 Peanut Rx)与本研究中确定的基于环境的预测因子相结合,将是优化茎腐病管理的下一个合乎逻辑的步骤。[公式:见文本] 版权所有 2024 年作者。这是一份在 CC BY 4.0 国际许可下发布的开放获取文章。