In this study, the problem of substantiation of Mobile Power Units (MPUs)tractors for agriculture of the fth generation{is described. The aim is to analyze agricultural tractors of the fth generation. Technogenic interaction of MPUs with production processes in agro-ecosystems of grain production in the zonal conditions of arid agriculture in Southern Russia is described. Proposals for new MPUs are developed and the technological structures of machine aggregates based on the MPUs of the fth generation of classes 3, 5{6 and 8, to determine their technical schemes, are determined. Analytical models are provided for calculating the power characteristics of MPUs of the mentioned classes in deterministic and stochastic modes in relation to the most energyintensive operations with de nitions of the mathematical expectations of Machine-Tractor Aggregate (MTA) power and performance. E ectiveness of MTAs is analyzed for the new MPUs based upon on the criterion of the time spent on cultivating crop rotations for classes 2 and 5{6 in wheeled and caterpillar performances and they are applied to the new generation of Machine-Tractor Station (MTS) of the technological services type. A comparison is carried out for the same sites with MTAs using the fourth-generation tractors. It will be observed that the time costs are reduced by 1.4{1.5 times and for the MPU of class 8, the reduction is up to 2.3 times.

Technical parameters of modern domestic and imported cultivators for continuous tillage were considered. Findings can be used for the estimation of specific technical indicators of engineered soil cultivating tools.

The probability of event occurrence can be determined by calculation, however for complex processes, accounting for multiple states is so complex that the probability of the final event cannot be determined differently than by collecting statistical data. This reduces the ability to predict outcomes in any process simulation, which affects the quality of advanced systems. The development of methods for predicting the probability of occurrence of an event when considering complex dynamic processes is a pressing task, the solution of which will help to improve the quality of modeling of technological processes and, as a result, to increase the efficiency of designing machines implementing them. The authors proposed a probability modeling method for dynamic processes, which is a special way of applying probability theory and is workable if the change in the parameters analyzed corresponds to the normal law of distribution. A study carried out on the analysis of the process of sowing corn seeds by vacuum sowing made it possible to predict with reliability more than 95% the probability of formation of “zero seed fodders” depending on their physical and mechanical properties, as well as parameters and adjustment modes of operation of the device.

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