Ranking is one of the tools for assessing the competitiveness of universities. There are regional and world rankings of agricultural universities and agricultural sciences. The QS World University Rankings is one of the most influential global university rankings. Only universities that offer all levels of education are included in the QS rating: bachelor’s, master’s and doctoral degrees (or postgraduate studies in Russian practice). At the same time, the university should comprise at least two of the five areas of knowledge: the humanities and arts; engineering and technical sciences; natural sciences; medicine and life sciences; social sciences and management. Evaluation of the best universities in the world in the ranking is based on six criteria: academic reputation (an indicator based on a survey of professors and teachers); reputation among employers (invitations to participate in the survey are sent to companies of all industries ranging in size from one hundred employees and above); the ratio of teaching staff to the number of students (the source of this data is information provided by the universities themselves); citation index (the ratio of the number of published scientific publications to the number of teachers and researchers for whom the university is the main place of work for at least one semester); the proportion of foreign students (reflects the degree of attractiveness of an educational institution in the international arena); the proportion of foreign teachers and scientists (employees who have worked for at least three months, taking into account the percentage of the rate, are taken into account). The article analyzes the methodology of the QS World University Rankings by Subject: Agriculture & Forestry and Veterinary Science. The author gives an assessment of the best universities according to the rating agency QS. The results of this study can be used by top management of agricultural universities in the designing of growth strategy.

Currently, goat farming becomes a perspective sector focused on production of goat’s milk and its products. Volume of milk produced by goats is determined by three factors: genetic heredity; environmental conditions, animal welfare and care conditions; feeding quality. In order to increase the productivity of dairy goats, it is necessary to improve and optimize feeding rates as the feeding is an essential factor defining the development of milk productivity. Sound feeding practices result in goats producing more than1000 kg of milk containing up to 4.5% fat. This practice-oriented research is based on the decision to use the information and analytical systems “RATIONS” in order to calculate balanced rations for adequate nutrition of dairy goats. Particular attention was given to introduction of feeding rates adjusted to fulfill their nutrient requirements of Saanen goats in North-West District of Russia.

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The article deals with the main issues of product quality management and control in multidimensional inter-industry production cooperation. Regulatory requirements and industry methods for assessing the quality of agricultural raw materials and finished industrial products on the example of leather and foot-wear industry are analyzed. The article presents the structural and logical scheme of the integrated classifier of methods for comprehensive quality assessment of objects and processes in multidimensional organizational structure of interindustry production cooperation. The conditions of digital transformation of agro-industrial complex aiming at improving the quality of leather footwear production on the basis of information-organizational inter-branch interaction between industrial and agricultural enterprises are formed int he article.

In order to effectively organize the process of agricultural enterprises, it is reasonable to involve management tools to build optimal models of interaction of individual components of the production process. The most significant part concerning the technical and economic efficiency is the technological process. However, the harvesting and postharvesting process is of the highest priority. The current stage of the management paradigm development includes the attraction of mathematical modeling in the organizational process. The construction of mathematical models is necessary at the stage of planning, organization, control, and is aimed at choosing such parameters of the technological process that will ensure the highest economic efficiency. At the same time, the validation process of the optimal parameters of machines and equipment that separate the grain receiving is of the most importance. While solving this problem, it is necessary to consider various efficiency criteria, the main of which are “loss volumes” and “reduced costs”. The criteria for the efficiency of the technical equipment of postharvesting grain process are the permissible values of agrotechnical requirements that consider the time of safe storage of freshly harvested grain mass without pretreatment and grain shatter losses due to its overripe. It is necessary to consider the maximum allowable volumes of losses during the postharvesting technological process. In order to define the best organizational solutions the iteration principle is used until a solution that meets the restrictions on the reduced costs level is found. The mathematical modeling in technological processes is carried out with the involvement of regression models that allow predicting the qualitative indicators of the operation of the pre-cleaning machine. As a result, it is possible to choose such a mode of equipment operation that ensures the production of grain that meets the regulatory requirements for the quality of the resulting product. The novelty of this study lies in the development of optimal ways for combine harvesters functioning. The article presents the methodology and procedure of optimizing the technological process during the postharvesting process of grain. The characteristics received as a result of experiments allow us to organize the technological process in an agricultural enterprise in the most optimal way so that it is economically and technically efficient.