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Agri 2025

Development of online Spatio-temporal risk Prediction Model for Downy Mildew (Plasmopara viticola) in grapevine

Vladimir Todiras, Speaker at Agriculture Conferences
State University of Moldova, Moldova, Republic of
Title : Development of online Spatio-temporal risk Prediction Model for Downy Mildew (Plasmopara viticola) in grapevine

Abstract:

Development of a spatio-temporal model to predict downy mildew risk would facilitate development and implementation of a disease warning system for efficient fungicide application in grapevine. The objective of this study was to estimate the incidence of the downy mildew in grapevine and validate a spatio-temporal risk prediction model for downy mildew. Development of spatio-temporal risk prediction model for downy mildew was based on  fuzzy classifiers in BioClass DSS. BioClass  is a GIS  tool designed to solve multiple-criteria classification and optimization problems. We present a new classification system which is based on combining fuzzy logic and level set methods. Preference-Ordered Fuzzy Sets approach provide the degree to which two classes are related to each other. An essential part of forming membership functions is the input space partitioning.  The Response function as degree of satisfaction and Membership function as the expression of fuzziness for decision making and optimization problems is introduced. Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of downy mildew biology and environmental data to derive new information for decision making. It was concluded that spatio-temporal models provide new possibilities for real time action in downy mildew risk analysis using decision support digital maps. The adopted methodology permitted quantifying the severity of the grape downy mildew not only in spatial terms, identifying the variability among the different regions of Moldova, but also in temporal terms, making an adequate distinction of the studied areas. The online version of spatio-temporal model  was implemented into information system for integrated plant protection.

Biography:

Dr. Vladimir Todiraș studied agriculture at Timireazev agricultural Academy, Russian Federation and graduated as MS in 1980. He then joined the research group at the Institute of Plant Physiology and Biochemistry, Moldavian Academy of Sciences. He received PhD degree in 1996 at the same institution. After one year he obtained the position of head of laboratory. Now he is working as head of laboratory in the Institute of Genetics, Physiology, and Plant protection, State University of Moldova, Chisinau, Moldova. He has published more than 80 research articles in SCI journals.

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