100   Artículos

 
en línea
Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si    
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Jianian Li, Zhengquan Liu and Dejin Wang    
The precise detection of diseases is crucial for the effective treatment of pear trees and to improve their fruit yield and quality. Currently, recognizing plant diseases in complex backgrounds remains a significant challenge. Therefore, a lightweight CC... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Rujia Li, Yadong Li, Weibo Qin, Arzlan Abbas, Shuang Li, Rongbiao Ji, Yehui Wu, Yiting He and Jianping Yang    
This research tackles the intricate challenges of detecting densely distributed maize leaf diseases and the constraints inherent in YOLO-based detection algorithms. It introduces the GhostNet_Triplet_YOLOv8s algorithm, enhancing YOLO v8s by integrating t... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Haiping Si, Mingchun Li, Weixia Li, Guipei Zhang, Ming Wang, Feitao Li and Yanling Li    
Apples, as the fourth-largest globally produced fruit, play a crucial role in modern agriculture. However, accurately identifying apple diseases remains a significant challenge as failure in this regard leads to economic losses and poses threats to food ... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang    
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergenc... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Zhiqing Guo, Xiaohui Chen, Ming Li, Yucheng Chi and Dongyuan Shi    
Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction me... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Teresa Romero-Cortes, Victor H. Pérez España, José A. Pescador-Rojas, Eduardo Rangel-Cortés, María M. Armendaríz-Ontiveros and Jaime A. Cuervo-Parra    
Agave genera include slow-growing plants with cultural and economic roots dating back to pre-Columbian times in Mexico. Several species have a widespread presence in the country and are cultivated and/or used directly from the field to obtain various der... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Dongxue Zhao, Yingli Cao, Jinpeng Li, Qiang Cao, Jinxuan Li, Fuxu Guo, Shuai Feng and Tongyu Xu    
Leaf blast is recognized as one of the most devastating diseases affecting rice production in the world, seriously threatening rice yield. Therefore, early detection of leaf blast is extremely important to limit the spread and propagation of the disease.... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Wolfgang Jarausch, Miriam Runne, Nora Schwind, Barbara Jarausch and Uwe Knauer    
Apple proliferation (AP) is an economically important disease in many apple-growing regions caused by ?Candidatus Phytoplasma mali? which is spread by migrating psyllid vectors on a regional scale. As infected trees in orchards are the only inoculum sour... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Isaac R. Vincent, Erin N. Rosskopf, Jeffrey K. Brecht, Nicholas S. Dufault, Germán Sandoya-Miranda and Xin Zhao    
The use of high tunnels, which allows growers to extend their season and improve yields, is increasing in the Southeastern U.S., yet growers face challenges related to weed and disease management, particularly in organic systems. On-station experiments w... ver más
Revista: Agronomy    Formato: Electrónico

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