Development of a Predictive Model of the Flight Dynamics of the European Corn Borer, Ostrinia nubilalis Hübner, 1796 (Lepidoptera: Pyralidae), in the Vojvodina Region, Serbia—Implications for Integrated Pest Management

Author:

Ivezić Aleksandar1,Mimić Gordan1ORCID,Trudić Branislav2,Blagojević Dragana1ORCID,Kuzmanović Boris3ORCID,Kaitović Željko4,Petrović Kristina14ORCID

Affiliation:

1. BioSense Institute, University of Novi Sad, Dr Zorana Đinđića 1, 21000 Novi Sad, Serbia

2. Forest Biodiversity and Restoration Team, Forestry Division, Food and Agriculture Organisation of the United Nations, Viale delle Terme di Caracalla, 00153 Rome, Italy

3. Faculty of Agriculture, University of Novi Sad, Trg Dositeja Obradovića 8, 21000 Novi Sad, Serbia

4. Maize Research Institute “Zemun Polje”, Slobodana Bajića 1, 11185 Beograd, Serbia

Abstract

Although corn production is affected by several harmful insects, its most important pest in the southeastern region of Europe is the European corn borer (ECB), Ostrinia nubilalis Hübner, 1796 (Lepidoptera: Pyralidae). Chemical control of O. nubilalis remains the main strategy in conventional corn production. The key to successfully achieving a high efficiency of insecticides is determining the appropriate moment of application, including the exact time in the insect’s life cycle when it is most vulnerable. In this study, monitoring data on the flight dynamics of ECB adults from a seven-year period (2014–2020) were exploited for the development of a predictive model of adult numbers within the growing season. ECB monitoring was performed by using light traps at 15 different locations in the Vojvodina region (Serbia) during the specified time period. First, the calendar for Vojvodina was created based on the analytics of the collected monitoring data. Additionally, the calendar was converted to the probability of ECB occurrence during the growing season, specifying the time interval between the appearance of each generation of the pest. Second, using machine learning techniques, a phenological model was designed that included daily values of relevant meteorological features, such as cumulative degree-days, relative humidity, and precipitation. The calendar had a lower prediction error when compared to the phenological model, and it was tested as a supporting management tool for the ECB in 2021, with a root-mean-square error of the number of adults of 46.67. Such an approach could significantly reduce both the consumption of insecticides and the number of chemical treatments, respectively. Above all, this approach has broad potential in IPM and organic farming, and it is fully compatible with biological control methods.

Funder

Ministry of Science, Technological Development and Innovation of the Republic of Serbia

Horizon Europe CREDIT Vibes project

Publisher

MDPI AG

Subject

Agronomy and Crop Science

Reference44 articles.

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