Defense of the dissertation of Esenova Moldir Balkairovna for the degree of Doctor of Philosophy (PhD) in the educational program «8D06103 - Information systems»

L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Esenova Moldir Balkairovna on the topic «Development of an intelligent information system for monitoring the development of diseases and pests of agricultural crops in the steppe regions of Kazakhstan» to the educational program «8D06103 - Information systems».

The dissertation was carried out at the Department of «Information Systems» of L.N. Gumilyov Eurasian National University.

The language of defense is kazakh

Official reviewers:

Bapiyev Ideyat - Doctor of Philosophy (PhD), Acting Associate Professor of the Higher School of Information Technology of the West Kazakhstan Agrarian and Technical University named after Zhangir Khan (Uralsk, Republic of Kazakhstan);

Cherikbayeva Lyailya - Doctor of Philosophy (PhD), Associate Professor of the Department of Computer Science, Al-Farabi Kazakh National University (Almaty, Republic of Kazakhstan).

Temporary members of the Dissertation Council:

Barakhnin Vladimir - Doctor of Technical Sciences, Professor, Leading Researcher at the Federal Research Center for Information and Computing Technologies (FITZ IVT) (Novosibirsk, Russian Federation);

Akanova Akerke - Doctor of Philosophy (PhD), Acting Associate Professor of the Department of Computer Science at the Kazakh Agrotechnical Research University named after S. Seifullin (Astana, Republic of Kazakhstan);

Yerimbetova Aigerim - Doctor of Philosophy (PhD), Candidate of Technical Sciences, Associate Professor, Leading Researcher, Institute of Information and Computing Technologies, Kazakh National Research University of Higher Education, Republic of Kazakhstan (Almaty, Kazakhstan).

Scientific consultants:

Abdikerimova Gulzira - Doctor of Philosophy (PhD), Associate Professor of the Department of «Information Systems» at L.N. Gumilyov Eurasian National University (Astana, Republic of Kazakhstan);

Khudoiberganov Mirzoali - Doctor of Physical and Mathematical Sciences, Acting Associate Professor, Head of the Department of «Computational Mathematics and Information Technology» at the National University of Uzbekistan named after Mirzo Ulugbek (Tashkent, Republic of Uzbekistan).

The defense will take place on December 06, 2024, at 10:00 AM in the Dissertation Council for the training direction «8D061 - Information and communication technologies» in the educational program «8D06103 - Information systems» of L.N. Gumilyov Eurasian National University. The defense meeting is planned to be held offline and online.

Link: https://clck.ru/3ELMmD

Address: Astana, st. K.Satpayeva, 2, room. 302.

Abstract (English): dissertation work of Yesenova Moldir «Development of an intelligent information system for monitoring the development of diseases and pests of agricultural crops in the steppe regions of Kazakhstan», submitted for the degree of Doctor of Philosophy (PhD) in the educational program «8D06103 - Information Systems». Relevance of the research topic. Automated monitoring of the condition of agricultural lands in Kazakhstan is one of the pressing issues. Within the framework of the State Program for the Development of the Agro-Industrial Complex (AIC) of the Republic of Kazakhstan for 2021-2025, it is envisaged to improve the quality of public services and implement digital technologies. In this dissertation, current issues related to the implementation of digital technologies in agriculture to ensure the successful execution of the program “Approval of Principles for the Rational Use of Agricultural Land” have been thoroughly examined. One of the key aspects is the use of satellite data for parameters such as biomass classification of grain crops, determination of the vegetative period, development of quantitative description methods for crop growth, and identifying factors that negatively impact their development based on spectral brightness coefficients. These measures are taken within the framework of the State Program for the Development of the Agro-Industrial Complex (AIC) of the Republic of Kazakhstan to improve the quality of public services and foster modern agricultural development. Given that grain harvest is the basis of the country’s food security, the development of agriculture is of particular importance. Forecasting the productivity of grain crops and assessing their condition at the level of large administrative units, such as a region or district, are pressing tasks. Ground-based route agrometeorological studies, despite their reliability, are limited in their regularity and coverage. Therefore, the development of remote sensing methods, including satellite monitoring, has become an integral element of effective information support for agriculture. Satellite monitoring of the condition of grain crops provides objective and continuous monitoring of crop development, as well as assessments of crop yield and the efficient use of agricultural lands. However, for the effective operation of the monitoring system, it is necessary to improve satellite data processing methods for assessing the condition of agricultural crop fields and determining planting areas within regional monitoring. This scientific task is particularly relevant, as the quality and efficiency of crop assessment depend on the accuracy of field area determination. Thus, the dissertation work is dedicated not only to the theoretical aspects of implementing digital technologies in agriculture but also to practical issues of improving monitoring methods for field conditions, which are essential elements for the successful development of Kazakhstan’s agro-industrial complex in both the current and future periods. The purpose of the dissertation research: Development of an intelligent information system for monitoring the development of diseases and pests of agricultural crops. Research objectives: 1. A review of scientific papers in the field of agriculture that study arable lands; 2. Comparative analysis of methods for determining factors that negatively affect the growth of agricultural crops; 3. Creation of a reference value for the severity of pests and diseases of agricultural crops; 4. Evaluation of the accuracy of the informativeness of a feature vector using machine learning methods; 5. Development of an intelligent information system for monitoring the development of diseases and pests of agricultural crops. Research methods: Methods of processing space images, model for classifying agricultural crops, their pests and diseases, machine learning methods, feature vectors. Description of the main results of the study: A classification model based on aerospace images and feature vectors has been developed. Justification of the novelty and importance of the results obtained: The novelty of the study is realized by creating reference values of the SBC for identifying diseases and pests of agricultural crops, a method for obtaining values in the Red Edge channel, and creating informative feature vectors. These methods make a significant contribution to the digitalization of the agro-industrial complex of Kazakhstan and allow automatic and accurate control of the growth of agricultural crops. As a result of the study, an innovative information system was formed aimed at increasing productivity and efficiency in the agro-industrial complex, as well as reducing the harmful impact on the environment, which will contribute to improving the quality of decision-making. in this area. Compliance with scientific development directions or state programs: The research work is in line with the state program for the development of the agro-industrial complex of the Republic of Kazakhstan for 2021-2025, which is aimed at introducing digital technologies in agriculture and improving the quality of public services. In addition, the research is relevant to the areas of scientific development in the field of agricultural technology in the world, especially in terms of remote monitoring of crop conditions in agriculture, early detection of pests and diseases, and improving digital monitoring systems. to increase productivity. The results of this work are in line with the areas of scientific development in digitalization, automation and improving the efficiency of agriculture. Participation of an individual author in the scientific results achieved in the dissertation: The author's personal contribution to the research results obtained during the dissertation work is as follows:  analysis of the problems studied in the work, determination of the purpose and objectives of the dissertation, substantiation of the methodology and methods for solving the tasks set, formulation of scientific principles and results proposed for defense;  creation of reference values for the prevalence of pests and diseases of agricultural crops;  create a method for obtaining the value of the SBC on the Red Edge channel using a mathematical model;  determination of the effectiveness of informative vectors of features identifying pests and diseases of agricultural crops;  verification and testing of research results in practice, that is, in industrial conditions.

Dissertation

List of Scientific Works

Consultant's Review

Foreign Consultant's Review

Conclusion of the Research Ethics Committee

Official Reviewer's Review

Official Reviewer's Review