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Information × Registration Number 0220U100831, 0119U001042 , R & D reports Title Improvement of meat productivity of pigs and sheep on the basis of innovative technological and breeding solutions popup.stage_title Head Kramarenko Serhii S., Registration Date 28-01-2020 Organization Mykolayiv National Agrarian University popup.description2  The object of the study is the process of improving the performance of meat production of pigs and sheep, depending on natural and economic factors. The purpose of the work is to substantiate, develop and implement innovative techniques for increasing the meat productivity of pigs and sheep, by optimizing technological factors (conditions of keeping and feeding) and applying traditional and marker-dependent (MAS) breeding methods and forecasting meat productivity based on predictive mathematical models of random sequences with economic justification. Research methods - analytical (literature review, discussion of research results), laboratory (histological structure of muscle tissue), mathematical and statistical analysis, fractal analysis. As a result of the research work, it was proved the feasibility of complex use of the preparations "Pro-Mack" and "Ultimate Light Acid" for suckling pigs (farrowing shop) four days before weaning and seven days after weaning pigs (growing shop) with periodicity every other day. in turn. It is established that the complex application of these drugs is more effective. Also, when assessing the impact of social rank on pigs' own performance, it was found that in order to reduce the level of aggression, animals should be maintained and raised for breed and breed combinations, since increased levels of aggression adversely affect the health and productivity of pigs. It is proved that the use of fractal analysis for histological specimens of the longest muscle of the back of pigs allows to estimate both the shape and size of the muscle fibers, as well as the peculiarities of the filling of the space between them layers of fat and / or connective tissue. It can then be used to develop an integrated meat quality assessment. A method for predicting the size of a sow's nest has been developed based on the use of a nonlinear canonical model of a random sequence of nest size change. Product Description popup.authors Atamaniuk Ihor P. Kramarenko Olexander S. Kramarenko Serhii S. Lykhach Vadym Ya. Luhovyi Serghii I. Faustov Rostyslav V. popup.nrat_date 2020-04-02 Close