Potato crops are susceptible to numerous field diseases causing significant losses in the quality and tuber yield. Control measures have a negative impact in soil and water resources affecting also farmers’ health and food security. Hence, a more sustainable agriculture management is a need to preserve ecosystems. Therefore, the objective of this study was to evaluate the response of nine potato cultivars (Fleur Bleue, Frisia, Fontane, Louisa, Agria, Daifla, Red Pontiac, Kennebec and Desiree) against early blight using a Decision Support Systems (DSS) in a potato-producing area from Northwest Spain. The experimental design was established using control plots and sprayed plots with fungicide according to a disease risk model adapted to the geographical region (DSS plots). Disease rating and severity were evaluated in field from the appearance of the first symptoms to final of senescence and the area under disease progress curve (AUDPC and r-AUDPC) was calculated. Aerobiological monitoring of main Alternaria species responsible potato early blight (Alternaria solani and Alternaria alternata) and the most vulnerable phenological stages were also considered. The susceptibility of the potato cultivars was analyzed based on the weather, severity of the disease and tuber yields. Specifically, temperature and leaf wetness were the meteorological variables that most influenced on the concentration of Alternaria. Conidia accounted for the previous week was the variable that most influenced in development of symptoms measured by AUDPC in natural conditions. Yields in the cultivars of DSS plots were higher than in control plots. Therefore, alternative pest management strategies, and specifically, Decision Support Systems for pest assessment are crucial for sustainable potato production. In this sense, the integration of particular information on disease resistance of commercial cultivars, phenological development of plant, or fungal particles surrounding the crop atmosphere could support these systems for better adjustment without compromising tuber yield and environment.

马铃薯作物易受多种田间病害影响，导致质量和块茎产量显着下降。控制措施对土壤和水资源产生负面影响，也会影响农民的健康和粮食安全。因此，需要更可持续的农业管理来保护生态系统。因此，本研究的目的是使用决策支持系统 (DSS) 在西班牙西北部马铃薯产区。根据适应地理区域的疾病风险模型（DSS 地块），使用对照地块和喷洒杀真菌剂的地块建立了实验设计。从最初的症状出现到衰老的最后阶段，在现场评估疾病等级和严重程度，并计算疾病进展曲线下的面积（AUDPC 和 r-AUDPC）。主要空气生物监测链格孢种马铃薯负责早疫病（番茄早疫病菌和交链孢）和最脆弱的生育期也被认为。根据天气、疾病的严重程度和块茎产量分析了马铃薯品种的易感性。具体而言，温度和叶片湿度是对链格孢浓度影响最大的气象变量. 前一周的分生孢子是在自然条件下对 AUDPC 测量的症状发展影响最大的变量。DSS 地块品种的产量高于对照地块。因此，替代的虫害管理策略，特别是虫害评估的决策支持系统，对于马铃薯的可持续生产至关重要。从这个意义上说，整合有关商业栽培品种抗病性、植物物候发育或作物大气周围真菌颗粒的特定信息可以支持这些系统进行更好的调整，而不会影响块茎产量和环境。