Abstract
The objective of this research is to formalize the growing integration of data and management algorithms in agriculture at the advanced stage of the digital economy (DE). This has resulted in a promising innovative project for a digital management platform (DMP) for the production economy, integrating all agricultural management tasks ontologically and functionally with a unified, scientifically based approach to their design. A key element of this approach should be a universal computer-aided design (CAD) system for crop rotation (CR) structures, substantiated by mathematical modeling. The priority for developing such a CAD system in the DE is dictated by the nature and ability of scientifically based crop rotations to determine all techno-logical processes in agriculture. The DMP project, in turn, was the result of a synthesis and subsequent formalization of several key principles of digital economy that emerged during the spontaneous attempts to integrate information resources and infor-mation management systems (IMS) by large organizations in the process of computerizing their businesses, as well as the experience of implementing IMS subsystems at over 1,000 enterprises as part of the "Electronization of Agriculture" program. Thus, working with experts from the Kuban Research Institute of Agriculture, which has extensive experimental data for many years, a mathematical model for the formation of optimal CR was developed. This research is supported by global trends toward the emergence of CAD systems replacing traditional manual system design, a consequence of the development of both integra-tion technologies and the simultaneous improvement of mathematical modeling methods. This paper utilizes the mathematical apparatus of graph theory in the form of a container packaging problem while simultaneously searching for the shortest path, as well as an optimization mathematical model of the production and logistics chain for both growing and further movement of produce within and outside the farm, which is especially important for agricultural holdings. In the future, with the transition of the agro-industrial complex to a DMP with the accumulation of a sufficient volume of data, it will be possible to set the task of forming new CR that take into account the heterogeneity of fields, using artificial intelligence.