Abstract
With the increasing global focus on food security and sustainable agriculture, the demand for genetic improvement of potatoes, as a key food crop, is becoming more urgent. Gene editing technologies such as CRISPR/Cas9 offer promising applications for enhancing potato disease resistance, drought tolerance, and nutritional quality. However, traditional gene target identification methods often face challenges such as time consumption and high costs, which limit editing efficiency. This paper presents a new perspective on gene target identification based on artificial intelligence (AI). By deeply mining genomic sequences and predicting gene functions, AI technologies accelerate the discovery and validation of gene targets, significantly improving the efficiency and precision of gene editing. This paper aims to promote the academic community's awareness of AI-driven gene target identification technologies and facilitate innovation and progress in crop improvement research.
