Analysis demonstrates improved crop yields in horticulture, highlighting AI's role in addressing pest outbreaks and data overload.
The application of Artificial Intelligence (AI) in the horticultural sector has become increasingly prominent, addressing key challenges such as poor soil management, pest and disease outbreaks, data overload, low crop yields, and the knowledge gap between farmers and advanced technologies. To overcome these obstacles, innovative solutions are needed, and AI offers a promising approach due to its flexibility, precision, cost-efficiency, and superior performance. By mimicking human problem-solving abilities, AI enhances decision-making in agricultural processes, making them more efficient while minimizing human intervention. One of the major advantages of AI in agriculture lies in its diverse applications, such as in irrigation, weeding, and pesticide spraying. These technologies, often integrated into robots and drones, enable precise control over water, pesticide, and herbicide usage, conserve soil fertility, and optimize labor utilization, ultimately boosting both the quantity and quality of agricultural output.
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Santhosha et al. (2025) studied this question.
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