Genetic engineering in agriculture: Evolving strategies for crop and livestock improvement
Abstract
Global food production and productivity are faced with rapid population growth, restricted arable land, climate change, diseases, and political conflicts. This resulted in a significant gap between potential and actual requirements and threatened sustainable production on a global scale. Though traditional breeding approaches successfully produced high-yielding species, the success rates have not been satisfactory. This is due to randomness, non-specificity, and the difficulty in identifying the resulting genetic changes. Also, these methods are largely time-consuming and labor-intensive. Understanding all of this is crucial for effective management in adverse agroecologies. One potential solution to this crisis is the application of Genetic Engineering (GEN) technologies to construct plants and animals with specific superior genetic traits. Integration of appropriate methods of GEN, as well as the fusion of Artificial Intelligence (AI) and Machine Learning (ML) technologies with genomic science, will herald a new era that is vital to attain and maintain food and nutritional security. Modern biotechnology, coupled with advancements in computing and computational tools, will yield valuable revelations that overcome sophisticated problems in this field. The positive results accomplished through modern genetic manipulations have gained momentum to discover more and more streamlined techniques for transferring genetic traits between organisms. Nonetheless, they ignited a heated debate between proponents and opponents. Calls aim to maximize benefits and minimize the occurrence of adverse effects while facilitating targeted and predictable enhancements in plant and animal genetics. Reasonable regulations and guidelines must be implemented while protecting against any possible misuse and preserving ethical standards.
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DOI: https://doi.org/10.18686/ppas2322
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