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New Trends in Incidence and Control of Fruit Crop Bacterial/Viral...
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New Trends in Incidence and Control of Fruit Crop Bacterial/Viral Diseases in Asia

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Protection and Biotic Interactions".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1757

Special Issue Editors

Dr. Toru Iwanami

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Guest Editor
Faculty of Agriculture, Tokyo University of Agriculture, Funako 1737, Atsugi, Kanagawa 243-0034, Japan
Interests: diseases of fruit crops and industrial crops
Dr. Takashi Fujikawa

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Guest Editor
Institute of Plant Protection, National Agricultural Research Organization, Kannondai, Japan
Interests: diseases of fruit crops and industrial crops

Special Issue Information

Dear Colleagues,

Fruit crops are important cash crops across Asia, but their production is constantly threatened by many diseases; bacterial diseases and viral diseases are particularly common in tropical temperate regions of Asia, respectively. Recently, the incidence and prevalence of bacterial diseases are increasing, apparently in association with climate change, while new viral epidemics are spreading in relation to the introduction of new popular cultivars. Some of these diseases are spreading over borders, and international collaboration is indispensable for taking countermeasures efficiently. On the other hand, the appearance of new advanced tools including qRT-PCR, NGS, RNAi, drones, image analysis, machine learning, modeling, and DNA editing has significantly enhanced precision of diagnosis and efficacy of control. This Special Issue of Plants will highlight new trends in the incidence of bacterial and viral diseases of fruit crops and disease control in Asia.

Dr. Toru Iwanami
Dr. Takashi Fujikawa
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bacterial/viral diseases of fruit crops
  • epidemiology
  • transboundary diseases
  • disease control

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Published Papers (1 paper)

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Research

20 pages, 8244 KiB  
Article
Diagnosis of Citrus Greening Using Artificial Intelligence: A Faster Region-Based Convolutional Neural Network Approach with Convolution Block Attention Module-Integrated VGGNet and ResNet Models
by Ruihao Dong, Aya Shiraiwa, Achara Pawasut, Kesaraporn Sreechun and Takefumi Hayashi
Plants 2024, 13(12), 1631; https://doi.org/10.3390/plants13121631 - 13 Jun 2024
Cited by 2 | Viewed by 1248
Abstract
The vector-transmitted Citrus Greening (CG) disease, also called Huanglongbing, is one of the most destructive diseases of citrus. Since no measures for directly controlling this disease are available at present, current disease management integrates several measures, such as vector control, the use of [...] Read more.
The vector-transmitted Citrus Greening (CG) disease, also called Huanglongbing, is one of the most destructive diseases of citrus. Since no measures for directly controlling this disease are available at present, current disease management integrates several measures, such as vector control, the use of disease-free trees, the removal of diseased trees, etc. The most essential issue in integrated management is how CG-infected trees can be detected efficiently. For CG detection, digital image analyses using deep learning algorithms have attracted much interest from both researchers and growers. Models using transfer learning with the Faster R-CNN architecture were constructed and compared with two pre-trained Convolutional Neural Network (CNN) models, VGGNet and ResNet. Their efficiency was examined by integrating their feature extraction capabilities into the Convolution Block Attention Module (CBAM) to create VGGNet+CBAM and ResNet+CBAM variants. ResNet models performed best. Moreover, the integration of CBAM notably improved CG disease detection precision and the overall performance of the models. Efficient models with transfer learning using Faster R-CNN were loaded on web applications to facilitate access for real-time diagnosis by farmers via the deployment of in-field images. The practical ability of the applications to detect CG disease is discussed. Full article
(This article belongs to the Special Issue New Trends in Incidence and Control of Fruit Crop Bacterial/Viral Diseases in Asia)
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