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影响花生茎腐病发展的环境因素:病害管理的预测因子和临界值。

Environmental Factors Influencing Stem Rot Development in Peanut: Predictors and Action Thresholds for Disease Management.

机构信息

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.

出版信息

Phytopathology. 2024 Feb;114(2):393-404. doi: 10.1094/PHYTO-05-23-0164-R. Epub 2024 Feb 26.

Abstract

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.

摘要

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。

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