Results 101 to 110 of about 12,860 (253)

Weed Detection in Sesame Seed

International Journal for Research in Applied Science and Engineering Technology
Contemporary agricultural systems encounter substantial obstacles in controlling weed proliferation, which diminishes harvest yields and escalates operational expenditures. This study introduces WeedScan AI, a novel deep learning architecture that utilizes satellite imaging and advanced computer vision methodologies for autonomous weed identification ...
openaire   +1 more source

Frontiers in transition‐metal single‐atom electrocatalysts: Design tactics, mechanistic regulation, and electrochemical sensing technologies

InfoMat, EarlyView.
This review offers an overview of recent advances in the fundamental properties, synthesis methods, and structural optimization of transition‐metal single‐atom electrocatalysts for electrochemical sensing. It also provides a comprehensive summary of the emerging applications in electrochemical assays based on these materials, along with key challenges ...
Yue Cao, Bo‐Yu Chen, Yiru Sheng, Haoyuan Song, Linan Zhu, Xiaohan Yang, Yuehe Lin, Wenlei Zhu, Yang Zhou   +8 more
wiley   +1 more source

YOLO-CornSeg: A Lightweight Segmentation Model for Corn Seedlings with an Indirect Weed Detection Strategy

Agronomy
Weed control is crucial for optimizing corn yield. In recent years, advances in computer vision and deep learning have created new opportunities for precision agriculture.
Jinglin Lei, Jialin Yu, Kang Han, Mian Li, Xiaojun Jin, Honglian Yin   +5 more
doaj   +1 more source

Towards Efficient and Intelligent Laser Weeding: Method and Dataset for Weed Stem Detection

Proceedings of the AAAI Conference on Artificial Intelligence
Weed control is a critical challenge in modern agriculture, as weeds compete with crops for essential nutrient resources, significantly reducing crop yield and quality. Traditional weed control methods, including chemical and mechanical approaches, have real-life limitations such as associated environmental impact and efficiency.
Dingning Liu, Jinzhe Li, Haoyang Su, Bei Cui, Zhihui Wang, Qingbo Yuan, Wanli Ouyang, Nanqing Dong   +7 more
openaire   +3 more sources

Towards Water, Food and Energy Security: The Global Challenges and Possible Solutions for a Holistic Vision of Sustainability

Irrigation and Drainage, EarlyView.
ABSTRACT This invited paper gives an overview of the challenges the world is facing and offers a possible solution for water and food security within the holistic integrated concept of the water–energy–food (WEF) nexus. The paper summarizes the experience the author gained through working on various research projects at national and international ...
Ragab Ragab
wiley   +1 more source

Advancing precision agriculture: A comparative analysis of YOLOv8 for multi-class weed detection in cotton cultivation

Artificial Intelligence in Agriculture
Effective weed management plays a critical role in enhancing the productivity and sustainability of cotton cultivation. The rapid emergence of herbicide-resistant weeds has underscored the need for innovative solutions to address the challenges ...
Ameer Tamoor Khan, Signe Marie Jensen, Abdul Rehman Khan   +2 more
doaj   +1 more source

Variable Rate Irrigation: A Long‐Term Simulated and Field Data Analyses of Irrigation Practices, Field Variability, Economic Feasibility and Profitability

Irrigation and Drainage, EarlyView.
ABSTRACT Long‐term economic analyses of variable rate irrigation (VRI) strategies were performed compared with uniform irrigation management (UIM) in a reference production field using the AquaCrop model. Five strategies to trigger irrigation were as follows: (Field Capacity‐VRI, Driest Soil Trigger‐VRI, Water Mining‐VRI, Conventional Uniform ...
Sahil Sharma, Suat Irmak, William Kranz
wiley   +1 more source

Key Technologies of Intelligent Weeding for Vegetables: A Review

Agriculture
Vegetables are an essential part of people’s daily diet, and weeds can cause serious losses in vegetable yield and quality. Intelligent weeding technology for vegetables will be one of the mainstream technologies in modern agricultural development.
Jinkang Jiao, Ying Zang, Chaowen Chen
doaj   +1 more source

Maize Yield, Water Productivity and Economic Analysis Under Different Irrigation and Nitrogen Management Strategies Using Field Data and CERES‐Maize Model

Irrigation and Drainage, EarlyView.
ABSTRACT There is limited integrated evaluation of nitrogen (N) and irrigation management strategies for improving maize yield and productivity using crop models. The effects of N and irrigation on maize yield and productivity under centre pivot (CPI) and subsurface drip irrigation (SDI) using the CERES‐Maize model were investigated. N treatments were (
Ebrahim Amiri, Suat Irmak, P. Aalaee Bazkiaee   +2 more
wiley   +1 more source

On‐Farm Demonstration and Economic Evaluation of an IoT Sensing System for Irrigation Management in South Carolina

Irrigation and Drainage, EarlyView.
ABSTRACT Irrigation can strongly influence agricultural productivity and sustainability. While sensor‐based irrigation has the potential to improve yield, reduce input costs and enhance resource‐use efficiency, its adoption in commercial agriculture remains limited.
J. O. Payero, U. Sekaran, D. B. Turner, S. Selvalakshmi, M. W. Marshall, N. Smith, J. Croft, A. S. Hill, R. Hitchcock‐Davis   +8 more
wiley   +1 more source