REVIEW article

Front. Plant Sci.

Sec. Plant Biotechnology

Volume 16 - 2025 | doi: 10.3389/fpls.2025.1585826

This article is part of the Research TopicFrom Genomics to Genome Editing: Crop Improvement Innovations for Farmers WorldwideView all 6 articles

Evolution of agricultural biotechnology is the paradigm shift in crop resilience and development: A review

Provisionally accepted
Muhammad  RiazMuhammad Riaz1Erum  YasmeenErum Yasmeen1Bilal  SaleemBilal Saleem2Muhammad  Khalid HameedMuhammad Khalid Hameed1Maryam  Thani Saeed AlmheiriMaryam Thani Saeed Almheiri3Reem  Omar Saeed Al MirReem Omar Saeed Al Mir3Ghalia  AlameriGhalia Alameri3Jwaher  Salem Khamis AlghafriJwaher Salem Khamis Alghafri3Mayank  Anand GururaniMayank Anand Gururani3*
  • 1Shanghai Jiao Tong University, Shanghai, China
  • 2National Agricultural Research Center, Islamabad, Islamabad, Pakistan
  • 3College of Science, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates

The final, formatted version of the article will be published soon.

The dual challenges of climate change and population growth have intensified both biotic and abiotic stresses on crops resulting in disruptions of water dissipation patterns, lessen growth, yield, productivity and food security. Therefore, smart and sustainable agriculture practices for climate resilient and high yielding crops is the need of time. For this purpose, Innovation in biotechnological strategies is essential for sustainable agricultural development. Traditional breeding techniques have evolved through molecular approaches like marker-assisted selection (MAS) and quantitative trait loci (QTL) mapping, which accelerate the identification of trait-specific improvements. Mutational breeding, although effective in generating genetic diversity but lacks the precision, accuracy and effectiveness. Transgenic breeding allows for the transfer of beneficial genes across species, but recent advancements have shifted focus toward more refined approaches, such as RNA interference (RNAi) and genome editing tools like CRISPR-Cas9. These technologies enable precise, controlled genetic modifications to enhance traits like stress tolerance, disease resistance, and nutritional content. The integration of cutting-edge multi-omics platforms, including transcriptomics, proteomics, metabolomics combined with robust artificial intelligence (AI) based methods has revolutionizing crop genome elucidation. AI-driven analysis of large-scale biological data has revealed intricate genetic networks and regulatory pathways that underpin stress responses, growth, yield and genetics circuit patterns. These innovations in biotechnology from conventional breeding to advanced data-trait elucidation integrated methods are pushing the boundaries of climate resilient and next generation crop development. This review focused on the future of resilient and sustainable agriculture that lies in the convergence of conventional and molecular breeding, biotechnology approaches and AI’s driven strategies that enabling scientists to understand the genomics circuits of crops. These next generationally evolved crops bridging gaps from laboratory to field application with reduced reliance on chemical fertilizers, lessen yield gaps, climate resilience and promising nutritional enrichment. Such crops thrive under harsh environment paving the way for resilient and sustainable crop system development in constantly populating and warming ecosystem.

Keywords: molecular breeding, Food security, Genome editing, Climate resilience, sustainable agriculture, artificial intelligence

Received: 03 Mar 2025; Accepted: 15 May 2025.

Copyright: © 2025 Riaz, Yasmeen, Saleem, Hameed, Saeed Almheiri, Saeed Al Mir, Alameri, Khamis Alghafri and Gururani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mayank Anand Gururani, College of Science, United Arab Emirates University, AlAin, Abu Dhabi, United Arab Emirates

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