Abstract. The integration of artificial intelligence (AI) technologies in sweet corn cultivation (Zea mays saccharata) holds significant potential for enhancing production efficiency and resource management. This study explores the application of AI in various agricultural processes, including the use of computer vision and multispectral imaging for continuous crop monitoring, machine learning algorithms for yield prediction, precision agriculture for resource optimization, and autonomous systems to increase operational efficiency. The results demonstrate that AI enables early detection of crop stress, diseases, and pests, facilitating targeted interventions that improve crop quality and reduce costs. Moreover, AI-driven predictive analytics help mitigate climate-related risks, while decision support systems provide customized recommendations for optimizing agricultural practices. The widespread adoption of AI in sweet corn cultivation represents a strategic opportunity to increase the sustainability and competitiveness of this sector.

Keywords: artificial intelligence, sweet corn, precision agriculture, crop monitoring, yield prediction.

[1]PhD. Student Raul-Dacian VIDICAN, Doctoral School Engineering Sciences, Agronomy, University of Oradea. e-mail: raulvidican@yahoo.com

[2]Prof. Hab. Ph.D., Petru Radu BREJEA, University of Oradea, Corresponding Member of The Academy of Romanian Scientists. e-mail: rbrejea@yahoo.com

[3] Prof. Hab. PhD., Nicu Cornel SABĂU, University of Oradea, e-mail: nsabau@uoradea.ro