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Updated: Mar 23, 2026
A Precise and Autonomous System for the Detection of Insect Emergence Patterns
Published on: January 9, 2019
Prediction of biological sensors appearance with ARIMA models as a tool for Integrated Pest Management protocols
María Fernández-González1, David Ramos-Valcárcel2, María Jesús Aira3
1Department of Plant Biology and Soil Sciences, Sciences Faculty of Ourense, University of Vigo, Ourense, Spain.
Introduction And Objectives:
Powdery mildew caused by Uncinula necator and Downy mildew produced by Plasmopara viticola are the most common diseases in the North-West Spain vineyards. Knowledge of airborne spore concentrations could be a useful tool in the Integrated Pest Management protocols in order to reduce the number of pesticide treatments, applied only when there is a real risk of infection.
Material And Methods:
The study was carried out in a vineyard of the D. O. Ribeiro, in the North-West Spain, during the grapevine active period 2004-2012. A Hirts-type volumetric spore-trap was used for the aerobiological monitoring.
Results:
During the study period the annual total U. necator spores amount ranged from the 578 spores registered in 2007 to the 4,145 spores sampled during 2008. The highest annual total P. viticola spores quantity was observed in 2010 (1,548 spores) and the lowest in 2005 (210 spores). In order to forecast the concentration of fungal spores, ARIMA models were elaborated.
Conclusions:
The most accurate models were an ARIMA (3.1.3) for U. necator and (1.0.3) for P. viticola. The possibility to forecast the spore presence 72 hours in advance open an important horizon for optimizing the organization of the harvest processes in the vineyard.
