Precision Assistance for Crop Genetic Improvement: Big Data, Artificial Intelligence and Machine Learning
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 20
Special Issue Editor
Special Issue Information
Dear Colleagues,
The rapid growth of genomics, phenomics, and multi-omics has created unprecedented opportunities for data-driven crop breeding. However, linking genotype, phenotype, and environment remains a significant challenge. Artificial intelligence (AI), machine learning (ML), and big data analytics now provide powerful tools to accelerate genetic gain by enabling predictive modeling, intelligent decision-making, and precision breeding design.
This Special Issue, Precision Assistance for Crop Genetic Improvement: Big Data, Artificial Intelligence and Machine Learning, aims to highlight advances at the interface of computational methods and plant breeding. We particularly encourage submissions that present cutting-edge research on the follow topics:
- Multi-omics data mining and integrative analysis of complex traits.
- Genomic prediction and modeling of genotype–environment interactions.
- AI-driven high-throughput phenotyping and data analysis.
- Data-driven approaches for genome editing and intelligent breeding.
- Computational platforms, algorithms, and tools for precision crop improvement.
We welcome original research, reviews, and perspectives that present methodological innovations, translational studies, or integrative frameworks demonstrating how big data and AI can transform crop genetic improvement toward more efficient, sustainable, and precise agriculture.
Dr. Jun Yan
Guest Editor
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.
Keywords
- genomics
- phenomics
- multi-omics
- artificial intelligence
- machine learning
- big data
- precision crop breeding
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
