Advancing Genomic Prediction: Statistical Models for Crop Breeding and G×E Optimization

Dear Colleagues,

The field of genomic prediction has rapidly transformed plant breeding over the past two decades, propelled by advances in sequencing technologies, high-throughput phenotyping, and statistical modeling. As breeders increasingly leverage large multi-environment trials and diverse germplasm resources, modeling genotype-by-environment (G×E) interactions has become central to improving prediction accuracy and accelerating genetic gain. Building on foundational work in quantitative genetics and mixed-model methodology, current research is moving toward integrative, data-rich frameworks that capture biological complexity while remaining computationally efficient for breeding applications.

This Special Issue aims to showcase state-of-the-art methodological and applied research that advances genomic prediction for crop improvement, with a particular focus on statistical models that address frameworks that capture environmental variation, complex plant responses, and performance across multiple traits. We seek contributions that introduce innovative statistical or machine learning approaches, or demonstrate impactful applications in real-world breeding programs.

We welcome original research papers, methodological developments, comparative evaluation studies, and application-driven case studies. Topics of interest include—but are not limited to—novel G×E modeling strategies, integration of genomic, multi-omics, phenomics, and environmental data, scalable Bayesian and AI-based models, optimization of training populations, multi-trait and multi-environment prediction, and frameworks supporting climate-resilient crop improvements. Review articles and perspectives providing forward-looking insights are also encouraged.

Dr. Reka Howard
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 250 words) can be sent to the Editorial Office for assessment.

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.