The article presents the results of modeling using neural network technologies and augmented reality technology in the interdisciplinary field of agricultural production: for assessing, predicting and visualizing the growth and development of agricultural plants, as well as for assessing adaptive scenarios for managing territories under the conditions of the greenhouse effect dynamics. The prospects of using digital technologies as an important tool for the formation of information support for decision makers in crop production are substantiated. In this paper, a prototype of the developed model-algorithmic toolkit is proposed, which can be used to improve the efficiency of the sowing planning process and obtain high plant yields.