From Reproduction to Resilience: New Frameworks for Managing Crop Diversity

Clicks: 19
ID: 326608
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #216 of 406 articles by views in Journal of experimental botany

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 406 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Plant breeding has progressed from phenotype-based selection to increasingly precise genetic and agronomic interventions. Advances in molecular breeding, genome engineering, and crop management have improved productivity, but have also promoted the widespread use of genetically uniform cultivars optimized for controlled production systems. While uniformity facilitates predictability and mechanization, it may constrain adaptive capacity under increasingly variable environmental conditions. In parallel, recent developments in digital agriculture, including high-resolution phenotyping, remote-sensing, molecular diagnostics, and AI-assisted decision support, are transforming the ability to monitor and manage biological variation across spatial and temporal scales. In this review, we examine how these technological advances intersect with emerging concepts in crop diversity and reproductive biology. We discuss how digital agriculture enables improved characterization of genotype-environment interactions and consider reproductive mechanisms that expand the accessible breeding space beyond conventional biparental crossing schemes, including haploid induction and multi-parental breeding. These approaches provide opportunities to accelerate trait introgression, generate novel genetic combinations, and overcome reproductive barriers. We argue that digital and diagnostic agriculture provide an informational framework for the deployment and evaluation of genetically heterogeneous plant populations. Together, recent advances suggest that technological precision and biological diversity can be integrated into breeding strategies that improve productivity and resilience.
Reference Key
openalex_W7204566795 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Saurabh Joshi, Yanbo Mao, Rita Groß‐Hardt
Are you one of these authors? Claim your profile
Journal Journal of experimental botany
Year 2026
DOI
10.1093/jxb/erag421
URL
https://doi.org/10.1093/jxb/erag421
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.