caerCentral Asian Economic ReviewCentral Asian Economic Review2789-43982789-4401Университет Нархоз10.52821/2789-4401-2025-3-199-224caer-1500Research ArticleЦИФРОВАЯ ЭКОНОМИКАDIGITAL ECONOMYЦифровые двойники в агропромышленной отрасли: концепции и практикаDigital twins in the agricultural industry: concepts and practiceshttps://orcid.org/0000-0002-4915-0347АмирхановБ. С.AmirkhanovB. S.

Алматы 

Almaty 

amirkhanov.b@gmail.comhttps://orcid.org/0000-0003-3933-5476АмирхановаГ. А.AmirkhanovaG. A.

Алматы 

Almaty 

gulshat.aa@gmail.comhttps://orcid.org/0009-0001-4257-6919РаеваА. А.RaevaA. A.

Алматы 

Almaty 

alinaraevali18@gmail.comКазахский национальный университет имени аль-ФарабиКазахстанAl-Farabi Kazakh National UniversityKazakhstan20251408202503199224Copyright © Амирханов Б.С., Амирханова Г.А., Раева А.А., 20252025Амирханов Б.С., Амирханова Г.А., Раева А.А.Amirkhanov B.S., Amirkhanova G.A., Raeva A.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://caer.narxoz.kz/jour/article/view/1500

Цель исследования — всесторонне изучить потенциал технологии цифровых двойников в сфере умного сельского хозяйства и показать, как их внедрение в фермерские хозяйства способствует повышению продуктивности и устойчивости. Кроме того, в работе систематизируются ключевые понятия, типы, методы проектирования и внедрения цифровых двойников, а также анализируется их влияние на реальные производственные процессы.Методология. В исследовании использован междисциплинарный системный подход. Разработана типология цифровых двойников и предложена структурная модель на основе архитектуры Интернета вещей (IoT-A) для их проектирования. Эта модель адаптирована к конкретным технологическим процессам в фермерских хозяйствах, обеспечивая обмен данными в реальном времени, автоматизированный мониторинг и прогнозирование. Также проведен сравнительный анализ пяти реальных примеров из проекта Европейского Союза IoF2020: растениеводство, производство молока, тепличное овощеводство, органическое земледелие и животноводство.Научная новизна / ценность. Данная работа является одной из первых, комплексно систематизирующих концепцию цифровых двойников в сельском хозяйстве. В исследовании рассматриваются не только технологические инновации, но и предлагаются конкретные изменения в управленческих моделях и трансформации фермерских процессов. Полученные результаты позволяют научно обосновать значимость и перспективность цифровых двойников в будущем аграрного сектора.Результаты. Результаты исследования показали, что цифровые двойники позволяют эффективно управлять фермерскими хозяйствами на основе данных в реальном времени. В сравнении с традиционными методами предложенные модели обеспечивают более высокую эффективность прогнозирования, оптимальное распределение ресурсов и адаптацию к климатическим или рыночным изменениям. Практические итоги пилотных проектов IoF2020 подтверждают широкие перспективы применения цифровых двойников и их важную роль в ускорении цифровизации агропромышленного комплекса. Так, в пилоте Potato Data Processing Exchange картофелеводы получили сквозную видимость потоков продукции от поля до склада через IoT-устройства; урожайность возросла в среднем на 10 %, расход топлива сократился на 10 %, а общая маржа увеличилась на 5 %.

Purpose of the research. The methods and criteria for comprehensively assessing the effectiveness of a country's economic integration within the framework of the Eurasian Economic Union (EAEU) can be identified. Three main methods for evaluating the effectiveness of economic integration within the EAEU can be distinguished. The first method is the method of trade integration among EAEU member states, which assesses the dynamics, structure, and volumes of mutual trade between the countries of the union. The second method is the method of assessing the effectiveness of economic integration based on a set of strategic priorities for economic development. The third method is the method of national competitiveness, which evaluates how participation in the EAEU affects the overall competitiveness of the national economy. Despite the fact that certain aspects of evaluation, such as competitiveness analysis, are universal, these methods will require adaptation for countries outside the EAEU. This is due to differences in the specifics of regional cooperation (e.g., in the EU or ASEAN) and integration mechanisms (such as currency or customs unions with varying regulations). Thus, the proposed methods can be developed with consideration for the specifics of the EAEU, but with some adaptation, they could also be used to assess integration in other unions.Methodology. A variety of methods were used in the course of the study: macroeconomic analysis, comparative analysis of national economic models, econometric modeling, and a comprehensive approach to assessing the achievement of economic benefits, stability, and competitiveness of the country within the framework of the EAEU. A literature review of academic works on the topic of the study was conducted, which allowed for an examination of Kazakhstan's role in the development of trade and economic relations between the member states of the EAEU.Originality / value. The originality and value of the study lie in examining the impact of global and regional integration on Kazakhstan's economic stability and development, considering the changes in the country's economy since its accession to the Eurasian Economic Union (EAEU). This provides insights into the effectiveness of the integration and helps identify future development vectors for Kazakhstan, based on improving trade relations and strengthening economic ties among EAEU member states.Findings. The study’s findings demonstrate that farm enterprises can be managed efficiently in real time by leveraging digital twins. Compared with traditional approaches, these models offer superior performance in process forecasting, optimal resource allocation, and adaptation to climatic or market fluctuations. Practical results from the IoF2020 project confirm the wide applicability of digital twins and their pivotal role in the digitalisation of the agri-food sector. All five IoF2020 pilot deployments quantitatively proved that digital twins significantly enhance both operational efficiency and sustainability. For example, in the “Potato Data Processing Exchange” pilot, potato growers used IoT devices to monitor the entire flow of produce from field to storage; as a result, average crop yield increased by 10 %, fuel consumption fell by 10 %, and overall margins rose by 5 %.

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The authors declare that there are no conflicts of interest present.