Unmanned aerial vehicle digital image and hyperspectral data for estimating the comparison of leaf area index and biomass of potato at different growth stages

[1] Esposito, M., Crimaldi, M., Cirillo, V., Sarghini, F., & Maggio, A. (2021). Drone and sensor technology for sustainable weed management: A review. Chemical and Biological Technologies in Agriculture, 8, 1-11. Search in Google Scholar

[2] Lin, Y., Li, S., Duan, S., Ye, Y., Li, B., Li, G., ... & Liu, J. (2023). Methodological evolution of potato yield prediction: a comprehensive review. Frontiers in Plant Science, 14, 1214006. Search in Google Scholar

[3] Maes, W. H., & Steppe, K. (2019). Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture. Trends in plant science, 24(2), 152-164. Search in Google Scholar

[4] Dutta, G., & Goswami, P. (2020). Application of drone in agriculture: A review. International Journal of Chemical Studies, 8(5), 181-187. Search in Google Scholar

[5] Ahmad, U., & Sharma, L. (2023). A review of best management practices for potato crop using precision agricultural technologies. Smart Agricultural Technology, 100220. Search in Google Scholar

[6] Canicattì, M., & Vallone, M. (2024). Drones in Vegetable Crops: A Systematic Literature Review. Smart Agricultural Technology, 100396. Search in Google Scholar

[7] Vidican, R., Mălinaș, A., Ranta, O., Moldovan, C., Marian, O., Ghețe, A., ... & Cătunescu, G. M. (2023). Using Remote Sensing Vegetation Indices for the Discrimination and Monitoring of Agricultural Crops: A Critical Review. Agronomy, 13(12), 3040. Search in Google Scholar

[8] Abbas, A., Zhang, Z., Zheng, H., Alami, M. M., Alrefaei, A. F., Abbas, Q., ... & Zhou, L. (2023). Drones in plant disease assessment, efficient monitoring, and detection: a way forward to smart agriculture. Agronomy, 13(6), 1524. Search in Google Scholar

[9] Sweet, D. D., Tirado, S. B., Springer, N. M., Hirsch, C. N., & Hirsch, C. D. (2022). Opportunities and challenges in phenotyping row crops using drone‐based RGB imaging. The Plant Phenome Journal, 5(1), e20044. Search in Google Scholar

[10] Roslim, M. H. M., Juraimi, A. S., Che’Ya, N. N., Sulaiman, N., Manaf, M. N. H. A., Ramli, Z., & Motmainna, M. (2021). Using remote sensing and an unmanned aerial system for weed management in agricultural crops: A review. Agronomy, 11(9), 1809. Search in Google Scholar

[11] Kaivosoja, J., Hautsalo, J., Heikkinen, J., Hiltunen, L., Ruuttunen, P., Näsi, R., ... & Salonen, J. (2021). Reference measurements in developing UAV systems for detecting pests, weeds, and diseases. Remote sensing, 13(7), 1238. Search in Google Scholar

[12] Abrahams, M., Sibanda, M., Dube, T., Chimonyo, V. G., & Mabhaudhi, T. (2023). A systematic review of UAV applications for mapping neglected and underutilised crop species’ spatial distribution and health. Remote Sensing, 15(19), 4672. Search in Google Scholar

[13] Nowakowski, A., Spiller, D., Cremer, N., Bonifacio, R., Marszalek, M., Garcia-Herranz, M., ... & Kim, D. H. (2021, July). Ai opportunities and challenges for crop type mapping using Sentinel-2 and drone data. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 258-261). IEEE. Search in Google Scholar