Field Crop 2025, Vol.8, No.6, 293-300 http://cropscipublisher.com/index.php/fc 300 Parida P., Somasundaram E., Krishnan R., Radhamani S., Sivakumar U., Parameswari E., Raja R., Rangasami S., Sangeetha S., and Selvi R., 2024, Unmanned aerial vehicle-measured multispectral vegetation indices for predicting LAI, SPAD chlorophyll, and yield of maize, Agriculture, 14(7): 1110. https://doi.org/10.3390/agriculture14071110 Qader S., Utazi C., Priyatikanto R., Najmaddin P., Hama-Ali E., Khwarahm N., Tatem A., and Dash J., 2023, Exploring the use of Sentinel-2 datasets and environmental variables to model wheat crop yield in smallholder arid and semi-arid farming systems, Science of the Total Environment, 869: 161716. https://doi.org/10.1016/j.scitotenv.2023.161716 Shahid M., Wakeel A., Ullah M., and Gaydon D., 2024, Identifying changes to key APSIM-wheat constants to sensibly simulate high temperature crop response in Pakistan, Field Crops Research, 307: 109265. https://doi.org/10.1016/j.fcr.2024.109265 Shanmugapriya P., Latha K., Pazhanivelan S., Kumaraperumal R., Karthikeyan G., and Sudarmanian N., 2022, Cotton yield prediction using drone derived LAI and chlorophyll content, Journal of Agrometeorology, 24(4): 348-352. https://doi.org/10.54386/jam.v24i4.1770 Sishodia R., Ray R., and Singh S., 2020, Applications of remote sensing in precision agriculture: a review, Remote Sensing, 12(19): 3136. https://doi.org/10.3390/rs12193136 Wajid A., Hussain K., Ilyas A., Habib-Ur-Rahman M., Shakil Q., and Hoogenboom G., 2021, Crop models: important tools in decision support system to manage wheat production under vulnerable environments, Agriculture, 11(11): 1166. https://doi.org/10.3390/agriculture11111166 Wang J., Wang P., Tian H., Tansey K., Liu J., and Quan W., 2023, A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variables, Computers and Electronics in Agriculture, 206: 107705. https://doi.org/10.1016/j.compag.2023.107705 Wang J., Wang Y., and Qi Z., 2024, Remote sensing data assimilation in crop growth modeling from an agricultural perspective: new insights on challenges and prospects, Agronomy, 14(9): 1920. https://doi.org/10.3390/agronomy14091920 Wu Y., Xu W., Huang H., Huang J., Yin F., Zhuo W., Gao X., Shen Q., and Wang X., 2020, Winter wheat yield estimation at the field scale by assimilating Sentinel-2 LAI into crop growth model, In: IGARSS 2020-2020 IEEE international geoscience and remote sensing symposium, pp.4383-4386. https://doi.org/10.1109/igarss39084.2020.9323941 Yang S., Li L., Fei S., Yang M., Tao Z., Meng Y., and Xiao Y., 2024, Wheat yield prediction using machine learning method based on UAV remote sensing data, Drones, 8(7): 284. https://doi.org/10.3390/drones8070284 Zare H., Weber T., Ingwersen J., Nowak W., Gayler S., and Streck T., 2022, Combining crop modeling with remote sensing data using a particle filtering technique to produce real-time forecasts of winter wheat yields under uncertain boundary conditions, Remote Sensing, 14(6): 1360. https://doi.org/10.3390/rs14061360 Zare H., Weber T., Ingwersen J., Nowak W., Gayler S., and Streck T., 2024, Within-season crop yield prediction by a multi-model ensemble with integrated data assimilation, Field Crops Research, 308: 109293. https://doi.org/10.1016/j.fcr.2024.109293 Zhang L., Li C., Wu X., Xiang H., Jiao Y., and Chai H., 2024, BO-CNN-BiLSTM deep learning model integrating multisource remote sensing data for improving winter wheat yield estimation, Frontiers in Plant Science, 15: 1500499. https://doi.org/10.3389/fpls.2024.1500499 Zhao Y., Potgieter A., Zhang M., Wu B., and Hammer G., 2020, Predicting wheat yield at the field scale by combining high-resolution Sentinel-2 satellite imagery and crop modelling, Remote Sensing, 12(6): 1024. https://doi.org/10.3390/rs12061024 Zhuo W., Huang H., Gao X., Li X., and Huang J., 2023, An improved approach of winter wheat yield estimation by jointly assimilating remotely sensed leaf area index and soil moisture into the WOFOST model, Remote Sensing, 15(7): 1825. https://doi.org/10.3390/rs15071825 Zhuo W., Huang J., Li L., Zhang X., Gao X., Huang H., Xu B., and Xiao X., 2019, Assimilating soil moisture retrieved from Sentinel-1 and Sentinel-2 data into WOFOST model to improve winter wheat yield estimation, Remote Sensing, 11(13): 1618. https://doi.org/10.3390/rs11131618
RkJQdWJsaXNoZXIy MjQ4ODYzNA==