Results 51 to 60 of about 81,803 (155)

Robust Citrus Disease Diagnosis: A Hybrid CNN Framework for Multi‐Task Classification, Severity Estimation, and Cross‐Species Adaptation

Engineering Reports, Volume 8, Issue 2, February 2026.
We propose a hybrid CNN–ML approach to accurately classify diseases in lemon and orange leaves and assess their severity. Our model achieves high accuracy and demonstrates generalizability, showing promise for automated disease detection and management in citrus crops.
Sayma Akter Rupa, Khandoker Nosiba Arifin, Md Musfique Anwar   +2 more
wiley   +1 more source

Multiclass Fruit Disease and Maturity Classification Using Hybrid Deep Neural and Transformer Models With Explainable AI Techniques

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
The principal aim of this research work is to develop an efficient and explainable deep learning (DL) framework for the classification of fruit diseases. Timely and accurate detection of diseases in plants is essential in order to reduce the loss of crops and high‐quality yields.
Ranjith Kumar Anandan, Saravanan Srinivasan, A. Prathik, Jitender Tanwar, Sandeep Kumar Mathivanan, Usha Moorthy   +5 more
wiley   +1 more source

The Genome Sequence of Citrus Melanose Pathogen Diaporthe citri and Two Citrus related Diaporthe species

, 2020
The melanose diseases is one the most widespread and economically important fungal diseases of citrus worldwide. The causative agent is filamentous fungus Diaporthe citri Wolf (syn. Phomopsis citri H.S. Fawc.).
Lei Li, Xiaoe Xiao, Pudong Li, Tao Xiong, Hongye Li, Brendan K. Riely, Yunpeng Gai, Yating Zeng   +7 more
core   +1 more source

Common mycorrhizal networks enhance defense responses against pathogens in neighboring plants

iMetaOmics, Volume 2, Issue 1, March 2025.
The common mycorrhizal networks (CMNs) provide a channel for interplant communication, which enables plants of different species to prepare for pathogen infections without direct exposure. The CMNs change the microbial abundance and community structure of the neighboring plants following pathogen infection in the donor plants, which further enhances ...
Yingde Li, Yong Wei, Youlei Shen, Rongchun Zheng, Yajie Wang, Tingyu Duan, Zhibiao Nan   +6 more
wiley   +1 more source

Citrus Melanose [PDF]

, 2008
This fungal disease can affect young leaves and fruits of certain citrus species or varieties when the tissues grow and expand during extended periods of rainy or humid weather conditions.
Nelson, Scot
core   +1 more source

Selecting hyperspectral bands and extracting features with a custom shallow convolutional neural network to classify citrus peel defects

Smart Agricultural Technology, 2023
Citrus Black Spot (CBS) causes considerable damage to the Florida citrus industry. Early detection of CBS, especially in the presence of other peel blemishes, would enable better mapping and control of CBS spread, reduce wasted fruit, and permit early ...
Quentin Frederick, Thomas Burks, Adam Watson, Pappu Kumar Yadav, Jianwei Qin, Moon Kim, Mark A. Ritenour   +6 more
doaj   +1 more source

Advancements in smart agriculture: A systematic literature review on state‐of‐the‐art plant disease detection with computer vision

IET Computer Vision, Volume 19, Issue 1, January/December 2025.
Plant diseases are known to cause negative impacts and financial losses which are usually found on plant leaves and detection using traditional methods is a labor‐intensive process. Smart agriculture applications based on computer vision are being developed to detect and control of plant diseases.
Esra Yilmaz, Sevim Ceylan Bocekci, Cengiz Safak, Kazim Yildiz   +3 more
wiley   +1 more source

Citrus Diseases Exotic to Florida: Citrus Tristeza Virus– Stem Pitting (CTV-SP)

EDIS, 2006
Citrus is susceptible to a large number of diseases caused by plant pathogens. Economic losses due to plant diseases can be severe, but fortunately, not all pathogens attacking citrus are present in Florida.
Kuang Ren Chung, Ronald H. Brlansky
doaj   +5 more sources

Image‐based crop disease detection using machine learning

Plant Pathology, Volume 74, Issue 1, Page 18-38, January 2025.
Image‐based crop disease detection using machine learning provides a faster, more accurate alternative to traditional methods, with advancements in AI and imaging platforms expanding its effectiveness. Abstract Crop disease detection is important due to its significant impact on agricultural productivity and global food security.
Aria Dolatabadian, Ting Xiang Neik, Monica F. Danilevicz, Shriprabha R. Upadhyaya, Jacqueline Batley, David Edwards   +5 more
wiley   +1 more source

Species of Diaporthe on Camellia and Citrus in the Azores Islands

Phytopathologia Mediterranea, 2018
Species of Diaporthe are important plant pathogens, saprobes, and endophytes on a wide range of plant hosts. Species such as D. citri are well-known on Citrus, as agents of pre- or post-harvest infections, causing dieback, melanose and stem-end rot on ...
Vladimiro GUARNACCIA, Pedro CROUS
doaj   +1 more source