Gonzalez-Dominguez Elisa, Caffi Tito, Paolini Aurora, Mugnai Laura, Latinović Nedeljko, Latinović Jelena, Languasco Luca, Rossi Vittorio
Horta s.r.l., Piacenza, Italy.
Department of Sustainable Crop Production (DI.PRO.VES.), Università Cattolica del Sacro Cuore, Piacenza, Italy.
Front Plant Sci. 2022 Apr 7;13:872333. doi: 10.3389/fpls.2022.872333. eCollection 2022.
Phomopsis cane and leaf spot (PCLS), known in Europe as "excoriose," is an important fungal disease of grapevines caused by spp., and most often by (synonym ). PCLS is re-emerging worldwide, likely due to climate change, changes in the management of downy mildew from calendar- to risk-based criteria that eliminate early-season (unnecessary) sprays, and the progressive reduction in the application of broad-spectrum fungicides. In this study, a mechanistic model for infection was developed based on published information. The model accounts for the following processes: (i) overwintering and maturation of pycnidia on affected canes; (ii) dispersal of alpha conidia to shoots and leaves; (iii) infection; and (iv) onset of disease symptoms. The model uses weather and host phenology to predict infection periods and disease progress during the season. Model output was validated against 11 independent PCLS epidemics that occurred in Italy (4 vineyards in 2019 and 2020) and Montenegro (3 vineyards in 2020). The model accurately predicted PCLS disease progress, with a concordance correlation coefficient (CCC) = 0.925 between observed and predicted data. A ROC analysis (AUROC>0.7) confirmed the ability of the model to predict the infection periods leading to an increase in PCLS severity in the field, indicating that growers could use the model to perform risk-based fungicide applications.
拟茎点霉枝枯和叶斑病（PCLS），在欧洲被称为“表皮脱落病”，是由拟茎点霉属真菌引起的葡萄重要真菌病害，最常见的病原菌是Phomopsis viticola（同义词Macrophoma viticola）。PCLS正在全球范围内再度出现，这可能是由于气候变化、霜霉病管理从基于日历的标准转变为基于风险的标准（从而取消了早期（不必要的）喷雾）以及广谱杀菌剂使用的逐步减少。在本研究中，基于已发表的信息开发了一个关于拟茎点霉感染的机理模型。该模型考虑了以下过程：（i）受影响枝条上分生孢子器的越冬和成熟；（ii）α分生孢子向新梢和叶片的传播；（iii）感染；以及（iv）病害症状的出现。该模型利用天气和寄主物候来预测季节中的感染期和病害进展。模型输出结果与在意大利（2019年和2020年的4个葡萄园）和黑山（2020年的3个葡萄园）发生的11次独立的PCLS流行情况进行了验证。该模型准确预测了PCLS病害的进展，观测数据与预测数据之间的一致性相关系数（CCC）=0.925。ROC分析（AUROC>0.7）证实了该模型预测导致田间PCLS严重程度增加的感染期的能力，表明种植者可以使用该模型进行基于风险的杀菌剂施用。
