FORECASTING THE DEVELOPMENT OF THE ORIENTAL FRUIT MOTH (GRAPHOLITHA MOLESTA) TAKING INTO ACCOUNT WEATHER FACTORS FOR THE DEVELOPMENT OF A PLANT PROTECTION SYSTEM FOR PERENNIAL PLANTINGS

Abstract

Modern agriculture is impossible without the use of plant protection products against pests and diseases, which, with their free development, significantly reduce the productivity of plantings and the marketability of the harvested crop. Research conducted in this direction abroad is aimed at using predictive mathematical models that link environmental factors that are significant for the pest and its development. At the same time, the system of intellectualization of such a forecast is increasingly being used with the use of artificial intelligence methods that independently form models based on constantly accumulating information databases. The aim of the study was to evaluate the effectiveness of an automated program for forecasting the development of the oriental fruit moth, developed on the basis of the temperature factor of the environment for the subsequent selection of an optimal adaptive plant protection system for perennial crops. To compare the results of the automated calculation of the development of the eastern fruit moth with objective data in the field, we carried out observations of the calendar dates of the butterfly flights and overcoming the economic threshold of harmfulness (ETH) on pheromone traps placed in peach plantations, on which chemical treatments with insecticides were not carried out in the period from 2019 to 2022. In the course of the research, a useful computer program was developed to determine the calendar dates of the development of the oriental fruit moth based on air temperature data using flexible logical algorithms. It is established that the variability of the terms of individual development of the pest provides an increase in the phase periods with each successive generation. The use of a computer program will allow us to develop a system for protecting trees from pests, as well as to adjust the timing of measures depending on objectively changing indicators of the conditions of the year.