The present study focuses on establishing thresholds of weather variables for predict early blight in potato crops. For this, the TOMCAST model was adjusted using weather variables and Alternaria conidia levels (mainly A. solani and A. alternata) during six growing seasons in A Limia (Northwest Spain). TOMCAST for the effective management of early blight considers leaf wetness and air temperature to calculate daily severity values (DSVs). Spearman correlations between temperature (minimum and average), mean temperature during leaf wetness period and Alternaria concentration showed the highest positive significant coefficients (0.386, 0.230 and 0.372, respectively; p < 0.01). Specifically, Alternaria levels higher than 50 spores/m³ were found the days with air mean temperature above 18 °C, more than 7 h of leaf wetness. Leaf wetness was decisive to estimate the concentration of Alternaria, resulting in a significant linear regression model (R² = 0.41; p < 0.001). TOMCAST was adapted to the area, considering 10 °C the minimum threshold for the mean value of temperature during the wet period and 10–15 accumulated disease severity values (DSV). Using TOMCAST, it was possible to predict the first Alternaria peak in most of potato growing seasons. Combining aerobiological and meteorological data to control fungal diseases during crops are a useful tool for sustainable agriculture.

中文翻译：

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用微生物学数据对TOMCAST模型的修改以管理马铃薯早疫病

本研究的重点是确定天气变量的阈值，以预测马铃薯作物的早疫病。为此，TOMCAST模型是用天气变量和调节孢分生孢子水平（主要是A.菌和链格孢过程中以Limia（西班牙西北部）六个生长季节）。为了有效控制早疫病，TOMCAST考虑了叶片的湿度和气温，以计算每日严重度值（DSV）。温度（最低和平均），叶片湿润期间的平均温度和链格孢菌浓度之间的Spearman相关性显示出最高的正显着系数（分别为0.386、0.230和0.372；p <0.01）。特别，在空气平均温度高于18°C，叶片湿润超过7 h的日子里，发现链孢菌的水平高于50孢子/ m ³。叶片湿度决定估计链格孢的浓度是决定性的，从而产生了显着的线性回归模型（R ² = 0.41；p <0.001）。TOMCAST已针对该区域进行了调整，考虑到在湿润时期的最低平均温度阈值10°C和10-15累积的疾病严重程度值（DSV）。使用TOMCAST，可以预测大多数马铃薯生长季节中的首个链格孢菌高峰。结合航空生物学和气象学数据来控制作物期间的真菌病害是可持续农业的有用工具。