Methodological Fundamentals of Information System Design in Crop Production

Introduction. The creation of new technologies for precision agriculture is intended to increase productivity, labor efficiency and improve production processes. According the World Food Program (WFP), 811 million people are chronically hungry, 283 in a state starvation or close starvation. An estimated 45 more 43 countries around world on brink Today's conditions require feed planet with an ever-growing population, minimize costs, develop that do not pollute planet. Therefore, modeling biological objects, research design intelligent systems great interest scientists today. purpose paper development main approaches building full-scale experiment from point view planning methodology, data processing, model selection. methodical basics, principles practical component crop disclosed. results automatic decision-making system basic mathematical models construction information presented. Results. basis study plant organism natural experiment. Field experiments difficult reproduce face number difficulties related accuracy methods used, which consist reliability measurement results. For first time, multi-level monitoring condition needs plants, contains wireless sensor network, ontologically controlled node, global database, knowledge base, explanatory module, control computer, human-machine interface, allows taking management decisions, was used research. decision. Our algorithm able take into account variability changes multivariate environment. where chlorophyll fluorescence induction parameter, induction, measured real acts as module. This promising way adjusting irrigation regimes, plants caring perennial plantations. Conclusions. important part this work effect methodology photosynthesis. very sensitive many plant. advantage method requirement specifics its conduct. objects faces difficulties. Of special composition soil influence characteristics growth profile maps. Due fact object only collection individual inside organism, but also exposed constant external factors environment, climate soil, must be taken when creating systems, productivity. Keywords: biosensors, system, model, agriculture, physiology.