In order to successfully conduct agricultural work and obtain a competitive harvest, it is mandatory to carry out spraying operations of crops that require highly qualified personnel, expensive equipment and suitable weather conditions. The use of tractors for spraying fields is the most common solution available at the moment, has disadvantages: high cost, risk of damage to the crop by "hitting", "hooking" or otherwise; environmental damage; due to exhaust gases, the demolition of the solution increases with increasing speed. Using a device designed specifically for spraying equipment is an ideal solution. The purpose of the article is to develop a working model of an automated sprayer for processing agricultural crops. The methods used are: technical justification of a controlled device for processing agricultural crops. Calculation of functional capabilities, algorithms of operation of the proposed automated device: selection of the type of sprayer, engine, chassis, controller, battery, as well as justification of the possibilities of using alternative energy sources (wind energy, solar energy); development of a 3D model of an automation device for anti-weed processing of agricultural crops, printing of parts, assembly of mechanical and electronic parts. Making a prototype using 3D printing; development of the wiring diagram of electronics, software (firmware of the microcontroller; application that controls the settings), testing of the prototype, assembly of the current model; rationale for the optimal use of Arduino and Raspberry Pi boards in this device in a pair: Raspberry Pi will allow you to control processes on the Arduino and easily interact with the Internet when the Arduino itself will perform simple operations such as interacting with electronics and reading sensor readings. The manufactured operating model showed compliance with the goals, a high degree of controllability, environmental friendliness, reduction of energy consumed, labor resources and can be used to scale this device. The developed model of the automation device for anti-weed treatment of agricultural crops can be used not only in agricultural pollination, but also as a mechanism for studying soil parameters: humidity, mineralogical composition and chemical content in the ground, using electronic sensors, as well as an automated mobile platform for any purpose requiring accurate navigation through the territory.

The article contains the results of a research work devoted to an important problem - the development, production and delivery to the consumer of fermented dairy products of a healthy diet fortified (enriched) with milk protein, a vitamin-mineral complex, and probiotics and prebiotics. Purpose is based on mathematical modeling of experimental data, to determine an effective fermented food system for use as the basis of a fortified (enriched) curd product for a healthy specialized diet; to develop a recipe and technology for its production; to study the nutritional, biological and energy value of a new product. Modern technologies and equipment were used in experimental studies: ultrafiltration, fortification, etc. The studies were carried out by standard physicochemical, microbiological methods in three to five repetitions. Mathematical and statistical processing of experimental data was carried out using the program "Statistica-6.0". A recipe and technology for the production of a curd product for a healthy specialized diet has been developed. Its nutritional, biological and energy value has been studied. The developed recipe and biotechnological parameters for the production of the curd product were tested in the industrial conditions of the leading enterprise JSC "Lyubinskiy MKK". The quality and safety of the curd product was studied in the laboratory of techno-chemical control of FGANU "VNIMI" (Moscow).

Increasing the yield of sunflower is inextricably linked with the evaluation of newly created interline hybrids and their components (parental forms) using various methods for assessing their combination ability (CА). Breeding research in this direction includes large material and practical costs when using the developed methods for assessing combination ability (CА) due to its small analytical capabilities. New approaches to the analysis of the productivity of hybrids in practical studies can significantly increase the volume of the analyzed material and evaluate not only for a short period of testing, but also for a long period of time over the years. Purpose is determination of the combination ability of parental forms of sunflower interlinear hybrids to optimize the breeding process. When analyzing the determination of the combination ability of the parental components of sunflower interlinear hybrids, the method of evaluating the CА according to a special scale developed at VNIIMK (Krasnodar, Russia) was used. This method makes it possible to analyze a large number of hybrid combinations and their parental forms and draw appropriate conclusions for further use in the breeding process. The analysis of the obtained results makes it possible to fully evaluate the obtained interline hybrid combinations by years of testing. We analyzed 1736 hybrid combinations involving 212 maternal forms and 1472 combinations involving 209 paternal pollen fertility restorer lines. 75 maternal lines with a high total combination ability (GCА) and 97 paternal forms with this trait were identified. Maternal lines with high combinational ability VKU 110 A, VKU 140 A and SV 55 A are of interest for use in practical breeding. Among the paternal forms are SV 123 V, VKU 400 V and VKU 401 V. The components of hybrid combinations with high specific combination ability (SCА) have been determined. These are lines VKU 414 A, VKU 413 A, SV 31 Rf, SP 1459. Hybrids with high adaptive properties have been identified when growing conditions change, which will make it possible to purposefully conduct practical breeding to maintain high productivity of sunflower hybrids

Phytopathological Assessment of Sunflower Genetic Resources in Relation to Vegetative Conditions in the East Kazakhstan Region during 2021-2023