Issues of complex research in digitalization of adaptive viticulture when implementing artificial intelligence tools

In recent years, digital technologies and modern computer technologies capable of processing large amounts of data have been intensively adopted. At present, specialists deal with the latest technological advances, including neural networks, the Internet of Things, and artificial intelligence. This creates the need to consider the prospects of introducing artificial intelligence in the scientific process and production in the viticulture industry, as well as to highlight the problems associated with its use. This paper reviews the prospects of introducing elements of artificial intelligence in the scientific process and agricultural production. Over the last 15 years, this direction has received insufficient attention in scientific literature, with such publications in the field of viticulture not exceeding 2 %. This requires intensification of research on the adoption of artificial intelligence in agriculture, including viticulture, particularly in the Russian Federation. Lagging behind in this issue can lead to dependence on foreign developers of such products, which threatens the loss of independent development of unique algorithms to control the processes of plant development, the influence of abiotic and biotic factors, and the selection of optimal technologies ensuring sustainable development of agriculture in general and viticulture in particular. In addition, the use of foreign artificial intelligence tools may pose bioterrorism threats through algorithms covertly decreasing plant productivity and soil fertility as well as by promotion of foreign plant protection products and plant growth regulators, which ignore domestic import-substituting production, equipment, and fertilizers. In this regard, the need to implement cooperative research programs to accumulate research material and develop domestic artificial intelligence software products to eliminate the above issues is substantiated.

1. El Jarroudi M., Kouadio L., Delfosse P., Bock C., Mahlein A., Mercatoris B., Adams F., Lenn J., Hamdioui S. Leveraging edge artificial intelligence for sustainable agriculture, Nat Sustain. 2024;7:846-854. DOI: 10.1038/s41893-024-01352-4.

2. Cockburn I., Henderson R., Stern S. The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis, in Ajay Agrawal, Joshua Gans, and Avi Goldfarb (eds). The Economics of Artificial Intelligence: An Agenda (Chicago, IL, 2019; online edn, Chicago Scholarship Online, 23 Jan. 2020). 2019: 115-148. DOI: 10.7208/chicago/9780226613475.003.0004.

3. Avadhesh G., Rao G., Purti B., Shruthi N., Raju S. Role of Artificial Intelligence in Agriculture-A Paradigm Shift. In book: International Conference on Cyber Security, Privacy and Networking. 2023:356-360. DOI: 10.1007/978-3-031-22018-0_33.

4. Frolov D., Radziewicz W., Saienko V., Kuchuk, N., Gnusov Y., Onishchenko Y. Theoretical And Technological Aspects Of Intelligent Systems: Problems Of Artificial Intelligence. 2021;21(5):35-38. DOI: 10.22937/IJCSNS.2021.21.5.6.

5. Sullivan C., Gemtou M., Anastasiou E., Fountas S. Building Trust: A Systematic Review of the Drivers and Barriers of Agricultural Data Sharing, Smart Agricultural Technology. 2024;8:100477. DOI: 10.1016/j.atech.2024.100477.

6. Tardaguila J., Stoll M., Gutirrez S., Proffi tt T., Diago M.-P. Smart applications and digital technologies in viticulture: A review, Smart Agricultural Technology. 2021;1:100005. DOI: 10.1016/j.atech.2021.100005.

7. Khan M., Khan W., Wang S., Wang J., Ahmar S., Saeed S., Khan S., Xu X., Chen H., Bhat J., Feng X. Applications of Artificial Intelligence in Climate-Resilient Smart-Crop Breeding, International Journal of Molecular Sciences. 2022;23(19):11156. DOI: 10.3390/ijms231911156.

8. Tzachor A., Devare M., King B., Avin S. Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities, Nature Machine Intelligence. 2022;4:104-109. DOI: 10.1038/s42256-022-00440-4.

9. Bastard A., Chaillet A. Digitalization from vine to wine: Successes and remaining challenges – A review. BIO Web of Conferences. 2023;68:01034. DOI: 10.1051/bioconf/20236801034.

10. Apeinans I., Litavniece L., Kodors S., Zarembo I., Lacis G., Deksne J. Smart Fruit Growing Through Digital Twin Paradigm: Systematic Review and Technology Gap Analysis, Engineering Management in Production and Services. 2023;15:128-143. DOI: 10.2478/emj-2023-0033.

11. Poblete-Echeverra C., Tardaguila J. Digital Technologies: Smart Applications in Viticulture. In book: Encyclopedia of Digital Agricultural Technologies. 2023; 336-348. DOI: 10.1007/9783-031-24861-0_206.

12. Xu Y., Wang Q., Zhulin A., Wang F., Libo Z., Wu Y., Dong F., Qiu C.-W., Liu X., Qiu J., Hua K., Su W., Xu H., Han Y., Cao X., Liu E., Fu C., Yin Z., Liu M., Zhang J. Artificial Intelligence: A Powerful Paradigm for Scientifi c Research, The Innovation. 2021;2(4):100179. DOI: 10.1016/j.xinn.2021.100179.

13. Aithal S., Aithal S. Use of AI-Based GPTs in Experimental, Empirical, and Exploratory Research Methods, SSRN Electronic Journal. 2024:14 DOI: 10.2139/ssrn.4673846.

14. Cuntz A., Fink C., Stamm H. Artificial Intelligence and Intellectual Property: An Economic Perspective. SSRN Electronic Journal. 2024:33. DOI: 10.2139/ssrn.4757971.

15. Ayris K., Rose D. Social and ethical considerations for agricultural robotics. In book: Advances in agri-food robotics Publisher: Burleigh Dodds Science Publishing. 2023. DOI: 10.19103/AS.2023.0124.20.

16. Eastwood C., Turner J., Romera A., Selbie D., Henwood R., Espig M., Wever M. A review of multi-scale barriers to transitioning from digital agriculture to a digital bioeconomy, CABI Reviews. 2023. DOI: 10.1079/cabireviews.2023.0002.

17. Zhou R., Yin Y. Digital Agriculture: Mapping Knowledge Structure and Trends, IEEE Access. 2023;11. DOI: 10.1109/ACCESS.2023.3315606.

18. Rudrakar S., Rughani P. IoT based Agriculture (AgIoT): A detailed study on Architecture, Security and Forensics, Information Processing in Agriculture. 2024;11(4):524-541. DOI: 10.1016/j.inpa.2023.09.002.

19. Bouhouita-Guermech S., Gogognon P., Blisle-Pipon J.C. Specific challenges posed by artificial intelligence in research ethics, Frontiers in Artificial Intelligence. 2023;6. DOI: 10.3389/frai.2023.1149082.

20. Sikander B., Baker J., Deveci C., Lund L., Rosenberg J. ChatGPT-4 and Human Researchers Are Equal in Writing Scientific Introduction Sections: A Blinded, Randomized, Non-inferiority Controlled Study, Cureus. 2023. DOI: 10.7759/cureus.49019.

21. Fabio F. ChatGPT: A Threat or an Opportunity for Scientists? Perspectives of Earth and Space Scientists. 2023;4(1). DOI: 10.1029/2023CN000212.

22. Ivanova M. I. Prospects for the development of digital models of grape varieties for predicting the effectiveness of technological processes, Fruit growing and viticulture in the South of Russia. 2024;85(1):157-173. DOI: 10.30679/2219-5335-2024-1-85-157173. – EDN WDAYHA. (in Russ.).

23. Potanin D. V. Scientific substantiation of digital modeling of adaptive gardening: dissertation for the degree of Doctor of Agricultural Sciences / Potanin Dmitry Valerievich, 2023, 335. – EDN FOPQRI. (in Russ.).

24. Stoeva K. D. Physiology of grapes and the basics of its cultivation. Vol. 1. Ecological and soil prerequisites for the growth and development of the vine. Nutrition of the grape plant. The physiology of grapes and the basics of its cultivation / Bolg. akad. nauk, Vsesoyuz. V. I. Lenin Academy of Agricultural Sciences; Under the direction of and ed. Academician K. Stoeva. Sofia: Publishing House of Bolg. akad. sciences, 1981, 332. (in Russ.).

25. Negrul A. M. Viticulture with the basics of ampelography and breeding. Moscow: Selkhozgiz, 1956, 399. (in Russ.).

26. Kuznetsov P. N., Kotelnikov D. Yu. Automated technological complex for monitoring and diagnostic vineyard, Don agrarian science bulletin. 2021;4 (56):16-23. (in Russ.).

27. Orlov V. A. Digitalization in the monitoring system of grape plantations, Russian grapes. 2023;25:116-124. DOI: 10.32904/2712-8245-2023-25-116-124. – EDN OHGSCQ. (in Russ.).

28. Likhovskoy V. V. Implementation of priority areas of scientific and technical activities of «Vniiviv «Magarach» RAS» in the fi eld of viticulture in 2023, Fruit growing and viticulture in the South of Russia. 2024;85(1):92-112. DOI: 10.30679/2219-53352024-1-85-92-112. – EDN CWMMJR. (in Russ.).

29. ArcGIS URL: https://ru.wikipedia.org/wiki/ArcGIS Ссылка активна на 09.01.2025.