Methodological Fundamentals of Information System Design in Crop Production

Abstract

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