Kalit so‘zlar
Iqtibos keltirish tartibi
Annotatsiya
Ushbu maqolada qishloq xo‘jaligi sohasida raqamli texnologiyalarni joriy etishning dolzarb yo‘nalishlari va ularning hosildorlik hamda ishlab chiqarish samaradorligiga ta’siri tahlil qilindi. Tadqiqot davomida mahalliy va xorijiy ilmiy manbalar o‘rganilib, O‘zbekiston sharoitida raqamli monitoring, masofaviy zondlash, sun’iy intellekt asosida hosil prognozi va “aqlli qishloq xo‘jaligi” tizimlarining qo‘llanish imkoniyatlari o‘rganildi. Shuningdek, ilg‘or tajribalar natijalari O‘zbekiston dehqonchilik tizimiga taqqoslab ko‘rsatildi va raqamli texnologiyalarni joriy etishning ijobiy tomonlari hamda mavjud muammolari ochib berildi. Tadqiqot natijalari raqamli texnologiyalardan foydalanish orqali suv resurslarini tejash, hosildorlikni barqaror oshirish va fermer xo‘jaliklarining raqobatbardoshligini kuchaytirish mumkinligini ko‘rsatdi. Maqola natijalari qishloq xo‘jaligi iqtisodiyotida samarali boshqaruv qarorlarini ishlab chiqishda va raqamli transformatsiya jarayonlarini jadallashtirishda muhim ilmiy-amaliy ahamiyat kasb etadi.
Adabiyotlar ro‘yxati
1. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M.-J. (2017). Big Data in Smart Farming – A review. Agricultural Systems, 153, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023 Wageningen University & Research
2. You, J., Li, X., Low, M., Lobell, D. B., & Ermon, S. (2017). Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 31(1). https://doi.org/10.1609/aaai.v31i1.11172 aaai.org
3. Fan, J., Bai, J., Li, Z., Ortiz-Bobea, A., & Gomes, C. P. (2022). A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 11873-11881. https://doi.org/10.1609/aaai.v36i11.21444 ojs.aaai.org
4. Zhu, X., Cai, F., Tian, J., Williams, T. K.-A., et al. (2025). Dynamic gating-enhanced deep learning model with multi-source remote sensing synergy for optimizing wheat yield estimation. Frontiers in Plant Science, 16:1640806. https://doi.org/10.3389/fpls.2025.1640806 Frontiers
5. Abdelbaki, A., & Udelhoven, T. (2022). A Review of Hybrid Approaches for Quantitative Assessment of Crop Traits Using Optical Remote Sensing: Research Trends and Future Directions. Remote Sensing, 14(15), 3515. https://doi.org/10.3390/rs14153515 MDPI
6. Lu, L., Tian, G., & Hatzenbuehler, P. (2022). How agricultural economists are using big data: a review. China Agricultural Economic Review, 14(3), 494-508. https://doi.org/10.1108/CAER-09-2021-0167 Emerald
7. Erdanaev, E., Kappas, M., & Wyss, D. (2022). Irrigated Crop Types Mapping in Tashkent Province of Uzbekistan with Remote Sensing-Based Classification Methods. Sensors, 22(15), 5683. https://doi.org/10.3390/s22155683 MDPI
8. Babakholov, T., Abdullaev, A., & Sharipov, S. (2024). An accuracy assessment of satellite-based cotton yield estimation using panel data regression: a case study of Uzbekistan. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-024-05220-1 SpringerLink
9. Conrad, C., Lamers, J. P. A., Ibragimov, N., Löw, F., & Martius, C. (2016). Analysing irrigated crop rotation patterns in arid Uzbekistan by the means of remote sensing: A case study on post-Soviet agricultural land use. Journal of Arid Environments, 124, 150-159. https://doi.org/10.1016/j.jaridenv.2015.08.008 CIFOR-ICRAF
10. Gerts, J., et al. (2020). Multi-temporal monitoring of cotton growth through the vegetation profile classification for Tashkent province, Uzbekistan. GeoScape, 14(1), 62-69. https://doi.org/10.2478/geosc-2020-0006 Sciendo
11. Asamov, R. B. (2025). Digital transformation and the impact of modern technologies on agricultural management in Uzbekistan. Yashil Iqtisodiyot va Taraqqiyot, 3(2). https://doi.org/10.5281/zenodo.15017273 green-eco.uz
12. Gulyamov, S. S., Mamadiyarov, D. U., & Rasulova, M. T. (2024). Application of digital technologies for ensuring agricultural productivity. British Journal of Global Ecology and Sustainable Development, 25, 6-20. journalzone.org
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