Vol 33, No 4 (2023)

Introduction. The implementation of the decree of the President of the Russian Federation is aimed at ensuring the food security of the country and requires the industrialization of the agro-industrial sector. The effectiveness of industrialization depends on the use of automated, intelligent solutions at all stages of implementing technological processes. Livestock is an agro-industrial sector generating the largest amount of organic waste materials, which are potential energy carriers: litter, liquid manure, process effluents, etc. According to the data from the Russian Statistics Committee and the research results, the annual volume of manure generated from farms is from 43.3 to 45.1 million tons, while there is an upward trend. The used energy potential from the entire volume does not exceed 40%. It is possible to increase the efficiency of using the energy potential of organic animal waste materials through implementing digitalized solutions. A strategic tool for the effective industrialization of livestock is the implementation of application software products that ensure the growth of ecological and energy effects.

Aim of the Article. The aim of the study is a counterfactual evaluation of the efficiency of the model for decontaminating liquid pig manure in the decontamination activator.

Materials and Methods. Counterfactual analysis is a tool for formalizing complex, multifactorial processes to ensure their subsequent digitalization. The essence of the analysis consists in a “surveyˮ of the analyzed model through which the values of variables are determined providing changes that lead to a deviation of the response beyond the boundary conditions during interpretation. The advantage of counterfactual analysis is the stability and transparency of the model to external influences during machine learning.

It is known that the representative pathogenic markers of the decontamination efficiency of liquid pig manure are helminth eggs and the number of colony-forming units of common coliform bacteria (CFU CCB). However, for testing and implementing an algorithm for counterfactual analysis of a mathematical model, it is acceptable to use the number of CFU CCB.

The object of the study was liquid pig manure with a humidity from 88% to 98%, the subject was a counterfactual analysis of the dependence of the number of CFU CCB on the exposure time in the activator, the concentration of active chlorine, the mass of working bodies, magnetic induction, and liquid manure humidity.

Results. The results of counterfactual evaluation and analysis carried with the use of the Python programming language and the PyCharm 2022.2 environment are presented in the tables. The counterfactual evaluation made it possible to identify ranges of variation of factors, the use of which can represent the potential of boundary conditions in solving the optimization problem. The cells of these values are highlighted in grey-blue. The most preferred ranges based on counterfactual evaluation are in the cells highlighted in green.

Discussion and Conclusions. There has been substantiated the prospects of using active chlorine in combination with the influence of ferromagnetic working bodies moving in an alternating rotating electromagnetic field as a decontamination activator. On the basis of counterfactual evaluation it was established that the most significant factors for determining the efficiency of decontamination of liquid pig manure by the number of CFU CCB are: magnetic induction in the working zone of the activator inductor, active chlorine concentration and exposure time.

Introduction. The amino acid composition of compound feed is of great importance in feeding all kinds of animals. The lack of one or another amino acid limits the assimilation of other amino acids, resulting in excessive compound feed consumption, deterioration of the metabolism in the bodies of animals and increasing of their susceptibility to diseases. The use of grain heaps of wheat in the early ripening stages as feed raw materials is a promising direction for the development of the fodder base that will provide a balanced amino acid composition of compound feed with a lower content of expensive fish meal, which is the main source of protein in compound feeds.

Aim of the Article. The article is aimed at determining the optimal ripening stage of spiked cereals, at which a high content of protein and proteinogenic amino acids is observed. The proposed technology and technological tools for early harvesting of spiked cereals will reduce agrotechnical terms of harvesting, reducing losses from shatter losses, and get grain of enhanced nutritive value.

Materials and Methods. To study the amino acid composition, 4 samples of a winter wheat grain heap were taken: the winter wheat varieties Admiral and Luchezar, the perennial winter wheat (trititrigia) variety Pamyati Lyubimovoy and the gray wheatgrass variety Sova. Harvesting the wheat of these varieties was carried out by a combing-threshing unit in 5 phenological stages (growth stages are presented on the BBCH scale): 77 – late milk ripeness, 83 – early phase of wax ripeness, 87 – gold wax ripeness, 89 – full ripeness, 92 – overripeness.

Results. The results of analyzing amino acid composition of 4 samples of wheat grain heap showed a high content of almost all the amino acids studied in the phase of gold wax ripeness, except of aspartic acid and asparagine, glutamic acid and glutamine, and tryptophan.

Discussion and Conclusion. Grain heap of waxy ripeness wheat is a promising grain raw material for the production of compound feeds, which will reduce the amount of expensive components, such as fishmeal.

Introduction. To improve the efficiency of harvesting crops, it is necessary to improve the existing tools of mowers and headers of combine harvesters that will ensure their versatility and multifunctionality. The increased power availability per the industry in the current economic and political conditions can be achieved by applying the principles of resource conservation and using alternative designs of reaper and headers. The existing cutting units of these agricultural machines do not provide simultaneous cutting, harvesting and chopping of corn stalks, sunflower stalks, reed steams and branches for the purpose of futher incorporation into the soil or collection of plant mass to use in liverstock. Therefore, substantiating the design and technological scheme and determinating the parameters and modes for the universal cutting and chopping apparatus is relevant.

Aim of the Article. The aim of the work is to increase the efficiency of cutting and chopping plants by substantiating the structural and functional scheme of the unit and the ration parameters and operating modes of the cutting unit.

Materials and Methods. The physics of the kinematic mode indicator is substantiated in terms of the probability-based approach. The research was carried out in the laboratory of the Department of Operation and Technical Service and in the training park of Kuban State Agrarian University.

Results. There is substantiated the structural and functional scheme of the chopper unit with a cutterbar of cutting and chopping type. The physics of the kinematic mode index characterizing the intensity of interaction of a certain number of knives with plants on the root and stems distributed over the area with different density, is substantiated for the accepted conditions of the unit operation, in terms of probabilistic approach to the interaction of knives with stems in the form of plants on the root.

Discussion and Conclusion. The obtained data are necessary for designing universal machines of a new type, providing not only cutting, but also collecting of cut stems, chopping and possible collecting of the chopped crop or spreading chopped crop on the field. Depending on the rotational speed of the auger tool, an indicator of the kinematic mode, the power varies from 4.99 kW to 11.02 kW, productivity from 0.5 kg/s to 1.22 kg/s, and energy consumption from 11.02 to 4.99 kW-s/kg.

Introduction. During one-stage mincing of frozen meat by milling, a change in the temperature of the boundary layer occurs resulting in plastic deformations of the raw meat and an increase in the size of the meat chips. The problem of regulating the operating parameters for the raw meat mincing process depending on its temperature can be solved through computer calculations of the temperature forecast of the meat boundary layer for several time intervals using fuzzy logic. The aim of the study was to develop an algorithm for hybrid control of single-stage mincing of frozen meat using fuzzy and clear mathematical control models.

Aim of the Article. The article is aimed at developing a hybrid control algorithm for single-stage grinding of frozen meat using fuzzy and clear mathematical control models.

Materials and Methods. The object of the study was the process of mincing frozen meat block (beef) with the use of a laboratory installation for a single-stage mincing with a capacity of 400 kg/hour. The E. Mamdani algorithm was used to develop a fuzzy mathematical control model. Mathematical modeling was carried out in the MATLAB, the Fuzzy Logic Toolbox package.

Results. There was developed a model for fuzzy control of the operation of an intelligent control system (ICS) when forming a task for setting the operating parameters of the meat mincing process with the use of adaptive forecasting of meat temperature. For this model, the membership functions of the input and output variables and a rule base (knowledge base) were created. There was proposed a functional scheme of temperature control, which reflects the structure of a fuzzy control model for single-stage mincing. The advantages of this control include the fact that the system is given the function of continuous automated control of the temperature regime of mincing raw meat under the control of an industrial computer.

Discussion and Conclusion. The results of temperature control can be used for further technological processing of meat. Using information about the temperature and chemical composition of raw meat, the ICS can realize the optimal mixing of minced meat ingredients. Artificial intelligence calculates all these characteristics of meat without the participation of a human operator. It makes it possible to fully automate the technological processing of meat in order to produce finished products of guaranteed high quality.

Introduction. Lighting is one of the key factors influencing the efficient greenhouse cultivation. In this context, LED grow lights are an innovative solution that allows users to precisely adjust the light parameters necessary for optimal photosynthetic processes.

Aim of the Article. The aim of the work is developing and testing the LED grow light with optimal spectrum and light intensity to ensure efficient growth, development and photosynthesis of plants in greenhouses.

Materials and Methods. The LED grow light was developed in accordance with the regulatory standards that define the basic requirements in light technology for plant growth: GOST R 57671-2017 and GOST R 58461-2019. There is presented the sequence of development stages, according to which this grow light was developed.

Results. As the light source, there was chosen the Full Spectrum-1 LED (China) with two prominent emission peaks at 440 nm and 642 nm. For the grow light, a spotlight housing was selected to direct light precisely onto the plants, thereby ensuring maximum efficiency of photosynthesis and growth. The analysis of ray tracing results in TracePro showed that the LED grow light model has a light distribution close to the cosine type. The radiant flux of emission was 4.14 watts, and the photosynthetic photon flux was 16.6 µmol/s.

Discussion and Conclusion. The developed LED grow light has a photosynthetic photon flux of 16.2 µmol/s at a power consumption of 8.8 watts. The photosynthetic efficiency of the grow light was 1.84 µmol/J. Thus, this grow light can be used for the efficient greenhouse cultivation, providing optimal lighting conditions and contributing to increased crop yield and the quality of agricultural crops.