Scholarly Article
Applications of Artificial Intelligence in the Sugar Industry: The Past, Present, and Future
Iwuozor, Kingsley O., Chinyere, Ejidike Lynda, Iwuozor, John, Emenike, Ebuka, Egbemhenghe, Abel U., Amadi, Marycynthia Ebere, Adeniyi, Adewale George
2025-12-12 · Journal of Computational Systems and Applications · Cultech Publishing Sdn. Bhd.
Abstract
The sugar industry faces unprecedented challenges including climate variability, sustainability demands, and operational efficiency requirements, necessitating innovative technological solutions. While artificial intelligence (AI) applications are transforming various agricultural sectors, there is a lack of comprehensive analysis examining AI implementation across the entire sugar industry value chain from cultivation to supply chain management. This review aims to provide a comprehensive analysis of AI applications in the sugar industry, examining current implementations, economic and environmental impacts, regional variations in adoption, and identifying future research directions and implementation challenges. The study showed that AI is revolutionizing sugarcane and sugar beet cultivation through precision agriculture, optimizing resource management, and enabling early disease detection with high accuracy. In manufacturing, AI optimizes mill processes, enhances quality control, and facilitates predictive maintenance, leading to increased efficiency and reduced waste. Furthermore, AI improves supply chain management by enhancing demand forecasting and logistics. The adoption of AI yields substantial economic benefits, including increased production and reduced costs, while also promoting environmental sustainability through efficient resource utilization. Key challenges include data availability, infrastructure limitations, and the skills gap, but future trends point towards the integration of generative AI, advancements in robotics, and the development of smart farms and mills. In summary, AI offers significant potential to transform the sugar industry, driving efficiency, sustainability, and economic growth, but its successful implementation requires addressing key challenges and embracing future technological advancements.
Keywords
Agriculture, Algorithm, ChatGPT, Sugarcane, Sustainability
Citation Details
Journal of Computational Systems and Applications, pp. 20-29