Special Issue "Omics Approaches for Crop Improvement—Volume II"

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: 31 March 2024 | Viewed by 83

Special Issue Editors

AGROSAVIA (Corporación Colombiana de Investigación Agropecuaria), Tibaitatá 250047, Colombia
Interests: genetic diversity; plant genetics; genomics and transcriptomics; plant–pathogen interaction
Special Issues, Collections and Topics in MDPI journals
Campus Rabanales, University of Cordoba, Cordoba, Spain
Interests: forest species; biotic and abiotic stresses; molecular markers; omics approaches; systems biology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The growing human population and climate change are imposing unprecedented challenges for the global food supply. To cope with these pressures, crop improvement demands enhancing agronomical important traits such as yield, resistance, and nutritional value by pivoting direct and indirect genetically assisted approaches. The development of last-generation high-throughput screening technologies, known as omics, promises to speed up trait improvement in plants. Large-scale techniques such as genomics, transcriptomics, proteomics, metabolomics, and phenomics have already retrieved large volumes of data as never before that, merged through bioinformatics and machine-learning approaches, are helping us understand the mechanisms behind crop features. Omics datasets are not only being generated from tissues of a single genotype but are also permeating macro-scale interactions to deepen our knowledge of crop behavior across the microbial and environmental continua. However, despite these massive technological and computational developments, cohesive efforts to combine contrasting omics studies within common pathways and cellular networks of crop systems are in their infancy. Therefore, this Special Issue envisions offering updated views on multidimensional large-scale omics-based approaches. Specifically, we welcome studies that explore the uses of the omics paradigm, and their integration through trans-disciplinary bioinformatics, as tools to improve qualitative and quantitative traits in crop species.

Dr. Roxana Yockteng
Dr. Andrés J. Cortés
Dr. María Ángeles Castillejo
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. Agronomy is an international peer-reviewed open access monthly 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 2600 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.


  • crop improvement
  • genomics
  • transcriptomics
  • proteomics
  • metabolomics
  • metagenomics
  • metatranscriptomics
  • nutrigenomics
  • ionomics
  • lipidomics
  • phenomics
  • environmental omics
  • bioinformatics
  • machine learning

Related Special Issue

Published Papers

This special issue is now open for submission.
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