Harnessing CRISPR Genome Editing for Sustainable Agriculture, Livestock and Food Security
Bibliographic record
Abstract
CRISPR genome editing has rapidly evolved from a bacterial immune mechanism into a powerful, programmable platform for precise genetic modification across plant and animal systems. In agriculture and livestock production, CRISPR-based tools such as Cas9, Cas12, base editors, and prime editors are enabling sustainable innovations that directly support global food security. Applications range from improving crop yield, nutritional content, and climate resilience to enhancing livestock disease resistance, productivity, and animal welfare. These advances offer transformative solutions to challenges posed by population growth, environmental stress, and limited arable resources. This review aims to critically summarizes recent technological developments, delivery strategies, and representative applications of CRISPR in crops and farm animals, while highlighting biosafety, ethical, and regulatory considerations that influence translational adoption. By integrating scientific progress with policy and sustainability perspectives, this work underscores CRISPR’s pivotal role in shaping resilient, ethical, and equitable food systems for the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".