251   Artículos

 
en línea
Minychl G. Dersseh, Aron A. Kibret, Seifu A. Tilahun, Abeyou W. Worqlul, Mamaru A. Moges, Dessalegn C. Dagnew, Wubneh B. Abebe and Assefa M. Melesse    
Water hyacinth is a well-known invasive weed in lakes across the world and harms the aquatic environment. Since 2011, the weed has invaded Lake Tana substantially posing a challenge to the ecosystem services of the lake. The major factors which affect th... ver más
Revista: Water    Formato: Electrónico

 
en línea
Sadia Alam Shammi, Yanbo Huang, Gary Feng, Haile Tewolde, Xin Zhang, Johnie Jenkins and Mark Shankle    
The application of remote sensing, which is non-destructive and cost-efficient, has been widely used in crop monitoring and management. This study used a built-in multispectral imager on a small unmanned aerial vehicle (UAV) to capture multispectral imag... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Dimitris C. Gkikas, Marios C. Gkikas and John A. Theodorou    
The specific application of this work involves the development of an intelligent system for diagnosing and treating fish diseases in Greek fish farming. The project aims to enhance the competitiveness of Greek fish farming by addressing the increasing mo... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Meiling Sheng, A-Xing Zhu, Tianwu Ma, Xufeng Fei, Zhouqiao Ren and Xunfei Deng    
Global climate change is a serious threat to food and energy security. Crop growth modelling is an important tool for simulating crop food production and assisting in decision making. Planting date is one of the important model parameters. Larger-scale s... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Lingjiang Tao    
With an El Niño prediction model, an advanced approach of conditional nonlinear optimal perturbation (CNOP) is used to reveal the maximum impacts of the errors occurring in initial conditions (ICs) and model parameters (MPs) on the El Niño predictions. T... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Wangyang Li, Youzhen Xiang, Xiaochi Liu, Zijun Tang, Xin Wang, Xiangyang Huang, Hongzhao Shi, Mingjie Chen, Yujie Duan, Liaoyuan Ma, Shiyun Wang, Yifang Zhao, Zhijun Li and Fucang Zhang    
Applying hyperspectral remote sensing technology to the prediction of soil moisture content (SMC) during the growth stage of soybean emerges as an effective approach, imperative for advancing the development of modern precision agriculture. This investig... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Zengyu Cai, Chunchen Tan, Jianwei Zhang, Liang Zhu and Yuan Feng    
As network technology continues to develop, the popularity of various intelligent terminals has accelerated, leading to a rapid growth in the scale of wireless network traffic. This growth has resulted in significant pressure on resource consumption and ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Wanli Yang, Song Jiang, Qibin Yang, Jianhua Huang, Jianzhi Shi, Yundong Li, Yukai Yang and Falin Zhou    
The effects of three feed additives in a low fish meal diet on growth, antioxidant capacity and intestinal microbiota of Penaeus monodon were studied to enhance the understanding of these effects and to provide basic data and a reference for the formulat... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti    
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ... ver más
Revista: Agronomy    Formato: Electrónico

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