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Latest Reviews in Molecular Plant Science 2025

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Plant Sciences".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 660

Special Issue Editors

Special Issue Information

Dear Colleagues,

Humans depend on plants to provide them with food, medicine, and clothing. Being curious about plants allows for unbiased observations to take place to understand the general principles that they perform to provide the substances that humans need. Over the past decade, great advances in research into plants have been achieved, covering every aspect of plant growth and development, beginning from seed germination to the senescence of the plant body. For agricultural plants, such as rice, wheat, maize, rapeseed, soybean, cotton, fruits and vegetables, understanding the molecular mechanisms for the formation of the yield, quality, and resistant to biotic and abiotic stresses is important to improve those traits of agronomical importance. Meanwhile, for model plants, important clues have been found to help us understand the basic biological mechanisms underlying plant growth, development, senescence, and adapting to stresses.

This Special Issue aims to provide a platform for the timely collection of the most recent advances made in molecular plant sciences and provide readers with a panoramic view of these advances. Review papers covering the topics related to molecular plant sciences are welcome to be submitted to this Special Issue.

Prof. Dr. Maoteng Li
Prof. Dr. Jinsong Bao
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • gene cloning and gene functional analysis
  • gene editing
  • QTL mapping
  • multi-omics integration analysis
  • agronomically characteristics
  • plant development
  • metabolic pathway
  • biotic and abiotic stresses

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Published Papers (1 paper)

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Review

17 pages, 1573 KiB  
Review
Artificial Intelligence-Assisted Breeding for Plant Disease Resistance
by Juan Ma, Zeqiang Cheng and Yanyong Cao
Int. J. Mol. Sci. 2025, 26(11), 5324; https://doi.org/10.3390/ijms26115324 - 1 Jun 2025
Viewed by 229
Abstract
Harnessing state-of-the-art technologies to improve disease resistance is a critical objective in modern plant breeding. Artificial intelligence (AI), particularly deep learning and big model (large language model and large multi-modal model), has emerged as a transformative tool to enhance disease detection and omics [...] Read more.
Harnessing state-of-the-art technologies to improve disease resistance is a critical objective in modern plant breeding. Artificial intelligence (AI), particularly deep learning and big model (large language model and large multi-modal model), has emerged as a transformative tool to enhance disease detection and omics prediction in plant science. This paper provides a comprehensive review of AI-driven advancements in plant disease detection, highlighting convolutional neural networks and their linked methods and technologies through bibliometric analysis from recent research. We further discuss the groundbreaking potential of large language models and multi-modal models in interpreting complex disease patterns via heterogeneous data. Additionally, we summarize how AI accelerates genomic and phenomic selection by enabling high-throughput analysis of resistance-associated traits, and explore AI’s role in harmonizing multi-omics data to predict plant disease-resistant phenotypes. Finally, we propose some challenges and future directions in terms of data, model, and privacy facets. We also provide our perspectives on integrating federated learning with a large language model for plant disease detection and resistance prediction. This review provides a comprehensive guide for integrating AI into plant breeding programs, facilitating the translation of computational advances into disease-resistant crop breeding. Full article
(This article belongs to the Special Issue Latest Reviews in Molecular Plant Science 2025)
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