урожай

Purpose. To assess the impact of climate change on oat productivity in the steppe zone of Ukraine. Methods. Statistical, mathematical modeling. Results. It is established that the seed sowing and of seedling emergence will be postponed to an earlier date. More favorable conditions are expected for the formation of seedling emergence, growth and development of plants during the period of "seedling - heading". Reduced background temperature will lead to a decrease in the value of total evaporation and a decrease in moisture demand by 47–58 mm. The moisture content of the first vegetation period will be significantly higher than in the middle perennial years. Agroclimatic conditions of the second half of the vegetation period of oats will develop at low tem-peratures and uneven moisture across the territory. The demand for moisture will increase everywhere by 12–28 mm. The supply of moisture will decrease. Using the model of the formation of the yield of agricul-tural crops, the influence of changes in the agro-climatic conditions of the growing season on the indica-tors of photosynthetic productivity of oat crops and the formation of the yield was assessed. Conclusions. It was concluded that a possible increase in the yield of oats in the Steppe zone of Ukraine under the implementation of climatic scenarios and early sowing terms. Changes in agroclimatic conditions in the implementation of climatic scenarios will lead to changes in the photosynthetic activity of oat crops: the relative leaf area will increase, the increase in total plant mass will increase, the photo-synthetic potential of crops will grow during the growing season. Proposed cartographic schemes of the expected yield of oats in the Steppe zone of Ukraine.

Purpose. Evaluate the use kvadrokopteriv for evaluation of weed-infested crops of sunflower. Methods. Aerial survey using drones, object-oriented image analysis. Results. In the article are given the results of as-sessment of a contamination of crops of sunflower by results of decryption of the pictures made by means of the UAV in the visible range.It is shown that the best results of decoding of photo-images are received when using supervised classification by a method of the maximum plausibility. Conclusions. For improving of recognition of weeds and separation of their image from images of cultural plants it is expedient to use the object-oriented analysis.