With widespread use of pesticides in modern agriculture, the impacts of spray drift have become a topic of considerable interest. The drifting of sprays is a highly complex process influenced by many factors. The paper presents results of experimental research on a drifting cloud of droplets dispersing from aircraft. Experiments were conducted to quantify spray drift from aerial applications of pesticide. Parallel to the blowing wind, the measurement line 800 m long was disposed. The relationships between the relative dose and the distance of drift as well as spray density and its structure on the measuring length have been established.

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The purposes of the paper are at first to inspect the solar and geomagnetic variations during the solar cycle 24 and the earlier cycles from 16 th and the second to calculate the solar number progression during the next two solar cycles basing on the earlier cycles data from the period 1923-2019 by means of the artificial neural networks (ANN). We focus our attention on Elman ANN because comparisons of an ANN type effectiveness in modeling of disturb course of different solar and geomagnetic parameters indicated on an recurrent ANN as better predictor than equivalent feedforward ANN. Daily data averaged by Bartels rotation of different activity parameters as sunspot numbers, aa geomagnetic indices, neutron monitor records from a station ROME with cutoff rigidity of 6.24 GV are used. Because of the limited place for this report our estimations related to variability of cosmic ray intensity would be presented only in the poster. Additionally the wavelet technique is used to show the coherence between estimated data. We compare the results and estimate that the solar activity would be rather a little smaller during 25 cycle than in 24 cycle.