Preview

Vegetable crops of Russia

Advanced search

Artificial intelligence in vegetable growing in Russia: problems and prospects

https://doi.org/10.18619/2072-9146-2024-6-93-97

Abstract

Relevance. Using artificial intelligence (AI) systems is of particular importance in the transformation of modern Russian vegetable growing.

Methods. Using the monographic method, the world and Russian practice of developing and using artificial intelligence systems is considered using the example of: CropX, John Deere, IBM Watson, AgEagle Aerial Systems, Blue River Technology, Farmwise, Taranis, Naiad Irrigation, Sustainable Agriculture Technology (SAT), Leader Technology, AgroCalypso, AgroVzglyad group of companies, Russian technologies and systems, Rostec Artificial Intelligence Competence Center, AgroBot, Kaluga Astra, Agrosystems, RosAgro, SAFMAR, AgriCo management company, Sadko agrofirm, AgroEco, AgroInvest and others.

Results, A list of problems with the use of AI in vegetable growing is identified, such as: high initial costs of implementing AI; lack of qualified personnel with the necessary knowledge in the field of IT and agronomy; high probability of technical failures, leading to losses in productivity and increased costs; difficulty of integration with existing automation systems; information security of databases; difficulty of data preparation; legal and ethical risks; lack of necessary infrastructure; unfavorable climatic conditions for the operation of AI; resistance to innovations on the part of personnel. Despite the identified problems, the prospects for using AI in vegetable growing in Russia will allow: optimizing agronomic processes; improving the quality of forecasting and monitoring; increasing the level of automation; improving the quality of data processing; improving resource manageability; increasing the level of adaptation of production to market needs; increasing adaptation to storage conditions and supply chain logistics, increasing the level of information content of technological processes.

Conclusion. Expanding the practice of using AI will increase the efficiency and sustainability of vegetable growing in the strategic perspective.

About the Author

T. Yu. Shabanov
Chelyabinsk State University; South Ural State University (National Research University); Financial University under the Government of the Russian Federation
Russian Federation

Timofei Yu. Shabanov - Cand. Sci. (Economic).

129, Bratyev Kashirinykh St., Chelyabinsk, 454001



References

1. Vertakova Yu.V., Katkov Yu.N., Romanova A.Al. Formation of information and analytical support for the management of the personnel potential of agricultural organizations using artificial intelligence. Drukerovskij vestnik. 2024;1(57):112-128. https://doi.org/10.17213/2312-6469-2024-1-112-128. https://elibrary.ru/cvkiqz

2. Volov Yu.M. Influence of artificial intelligence on the development of agricultural industry. Vestnik scientific journal. 2024;2(2):64-67. https://elibrary.ru/pmqthw

3. Zatsarinny A.A., Medennikov V.I., Raikov A.N. Integration of agricultural artificial intelligence applications into a single digital platform. Information society. 2023;(1):127-138. https://doi.org/10.52605/16059921_2023_01_127. https://elibrary.ru/nmkklz

4. Artificial intelligence in the service of the agro-industrial complex: priorities, goals and objectives. Agrarian science. 2023;(8):14-15. https://elibrary.ru/keykrn

5. Nakonechnaya O.A., Solovieva A.E. Priority solutions for the use of artificial intelligence in agriculture. Economy and business: theory and practice. 2023;7(101):136-138. https://elibrary.ru/rmxnri https://doi.org/10.24412/2411-0450-2023-7-136-138

6. Fedotova G.V., Slozhenkina M.I., Mitrofanova I.V., Lamzin R.M. Artificial intelligence as an innovative vector of managing the regional agro-industrial complex. Regional economy. south of Russia. 2021;9(1):152-162. https://elibrary.ru/lmzzxd https://doi.org/10.15688/re.volsu.2021.1.13

7. Yakovleva E.V., Bykov M.O. Review of examples of artificial intelligence for labor safety management in the agro-industrial complex. Vestnik sel'skogo razvitiya i sotsial'noy politiki. 2020;4(28):26-28. https://elibrary.ru/hrucxd

8. Ilishev A.P., Tolmachev O.M. Artificial intelligence and neural network technologies in a digital platform for the breakthrough development of the Russian agricultural sector. Economics and society: contemporary models of development. 2019;9(4(26):492-507. https://doi.org/10.18334/ecsoc.9.4.100453. https://elibrary.ru/cuufov

9. Shutkov A.A., Anishchenko A.N. The future of artificial intelligence, neural networks and digital technologies in agriculture. Economics and society: contemporary models of development. 2019;9(4(26)):508-522. https://doi.org/10.18334/ecsoc.9.4.100454. https://elibrary.ru/rvwttq

10. Shelyag M.M. Application of artificial intelligence systems to study the impact of cost structure on production volumes in the agro-industrial complex. Polythematic online scientific journal of Kuban State Agrarian University. 2005;(10):36-43. https://elibrary.ru/jwxnox

11. Talaviya T., Shah D., Patel N., Yagnik H., Shah M. Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides. Artificial Intelligence in Agriculture. 2020;(4):58-73. https://doi.org/10.1016/j.aiia.2020.04.002

12. Wolfert S., Ge L., Verdouw C., Bogaardt M.-J. Big Data in Smart Farming - A Review. Agricultural System. 2017;(153):69-80. https://doi.org/10.1016/j.agsy.2017.01.023

13. Rohani A., Taki M., Bahrami G. Application of artificial intelligence for separation of live and dead rainbow trout fish eggs. Artificial Intelligence in Agriculture. 2019;(1):27-34. https://doi.org/10.1016/j.aiia.2019.03.002

14. Runowski H., Kramarz P. Trust in artificial intelligence in agriculture. Trust and Artificial Intelligence. 2024. P. 229-241. https://doi.org/10.4324/9781032627236-21

15. Sachithra V., Subhashini L.D.C.S. How artificial intelligence uses to achieve the agriculture sustainability: Systematic review. Artificial Intelligence in Agriculture. 2023;(8):46-59. https://doi.org/10.1016/j.aiia.2023.04.002

16. Subeesh A., Mehta C.R. Automation and digitization of agriculture using artificial intelligence and internet of things. Artificial Intelligence in Agriculture. 2021;(5):278-291. https://doi.org/10.1016/j.aiia.2021.11.004

17. Ahmed L., Nabi F. AI (Artificial Intelligence) Driven Smart Agriculture. Agriculture 5.0: Artificial Intelligence, IoT, and Machine Learning, 2021. P. 123-134. https://doi.org/10.1201/9781003125433-5


Review

For citations:


Shabanov T.Yu. Artificial intelligence in vegetable growing in Russia: problems and prospects. Vegetable crops of Russia. 2024;(6):93-97. (In Russ.) https://doi.org/10.18619/2072-9146-2024-6-93-97

Views: 227


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2072-9146 (Print)
ISSN 2618-7132 (Online)