| Issue |
BIO Web Conf.
Volume 228, 2026
Biospectrum 2025: International Conference on Biotechnology and Biological Science
|
|
|---|---|---|
| Article Number | 03006 | |
| Number of page(s) | 7 | |
| Section | Plant Biotechnology | |
| DOI | https://doi.org/10.1051/bioconf/202622803006 | |
| Published online | 11 March 2026 | |
Enhancing Crop Resilience Through Plant Biotechnology to Address Global Food Security Challenges
1 Assistant Professor, Department of Biotechnology, Kalinga University, Naya Raipur, Chhattisgarh, India.
2 Assistant Professor, Department of Biotechnology, Kalinga University, Naya Raipur, Chhattisgarh, India.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The integration of population growth, climate change, and environmental degradation continues to create global challenges to food security. This paper presents a conceptual, modeling-based framework that explores the potential of various branches of biotechnology—including genetic engineering, nanotechnology, and precision biotechnology—to enhance crop resilience against biotic and abiotic stresses. Through the development of a Biotech–Nanotech Crop Resilience Model, an integrated Crop Resilience Score (CRS) is proposed to mathematically formalize the synergy between CRISPR-based genetic editing and nanoscale delivery systems. The model was evaluated using a synthetic dataset of 100 simulated crop scenarios to assess theoretical performance in yield stability and resource optimization. Results from these in-silico simulations suggest theoretical yield improvements of 30–50% and enhanced resource optimization. It must be emphasized that these findings are derived entirely from mathematical modeling and have not been validated against real-world field data or laboratory experiments. However, as the study is primarily algorithmic and lacks empirical validation through real-world field or laboratory trials, these outcomes are presented as hypothetical benchmarks rather than verified agronomic indicators. The paper provides a theoretical foundation for subsequent studies to refine the model's parameters and evaluate the practical feasibility and safety of its components in diverse geographical regions.
Key words: Plant biotechnology / crop resilience / in-silico modeling / nanotechnology / food security / synthetic dataset / CRISPR-cas
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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