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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Margarita Garcia-Vila, Rodrigo Morillo-Velarde and Elias Fereres
Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past ...
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Vanessa de Arruda Souza, Débora Regina Roberti, Anderson Luis Ruhoff, Tamíres Zimmer, Daniela Santini Adamatti, Luis Gustavo G. de Gonçalves, Marcelo Bortoluzzi Diaz, Rita de Cássia Marques Alves and Osvaldo L. L. de Moraes
Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determinin...
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Reza Aghlmand and Ali Abbasi
Increasing water demands, especially in arid and semi-arid regions, continuously exacerbate groundwater resources as the only reliable water resources in these regions. Groundwater numerical modeling can be considered as an effective tool for sustainable...
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Zhongyu Yang, Zirui Yu, Xiaoyun Wang, Wugeng Yan, Shijie Sun, Meichen Feng, Jingjing Sun, Pengyan Su, Xinkai Sun, Zhigang Wang, Chenbo Yang, Chao Wang, Yu Zhao, Lujie Xiao, Xiaoyan Song, Meijun Zhang and Wude Yang
Aboveground biomass (AGB) is a key parameter reflecting crop growth which plays a vital role in agricultural management and ecosystem assessment. Real-time and non-destructive biomass monitoring is essential for accurate field management and crop yield p...
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Liming Dong, Yuchao Lu, Guoqing Lei, Jiesheng Huang and Wenzhi Zeng
Intercropping radiation interception model is a promising tool for quantifying solar energy utilization in the intercropping system. However, few models have been proposed that can simulate intercropping radiation interception accurately and with simplic...
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Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t...
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Jiuyuan Zhang, Jingshan Lu, Qiuyan Zhang, Qimo Qi, Gangjun Zheng, Fadi Chen, Sumei Chen, Fei Zhang, Weimin Fang and Zhiyong Guan
Crown diameter is one of the crucial indicators for evaluating the adaptability, growth quality, and ornamental value of garden chrysanthemums. To accurately obtain crown diameter, this study employed an unmanned aerial vehicle (UAV) equipped with a RGB ...
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Abdelkrim Lachgar, David J. Mulla and Viacheslav Adamchuk
One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to ...
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Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai and Yen-Jen Chang
Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybri...
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