2025-01-07 イリノイ大学アーバナ・シャンペーン校
＜関連情報＞
- https://aces.illinois.edu/news/smart-food-drying-techniques-ai-enhance-product-quality-and-efficiency
- https://link.springer.com/article/10.1007/s12393-024-09388-0
スマートで精密な食品乾燥のためのAI対応光学センシング： 技術、応用および将来の方向性 AI-Enabled Optical Sensing for Smart and Precision Food Drying: Techniques, Applications and Future Directions
Marcus Vinicius da Silva Ferreira,Md Wadud Ahmed,Marciano Oliveira,Sanjay Sarang,Sheyla Ramsay,Xue Liu,Amir Malvandi,Youngsoo Lee & Mohammed Kamruzzaman
Food Engineering Reviews Published:20 November 2024
DOI:https://doi.org/10.1007/s12393-024-09388-0
Abstract
Recent developments in alternative drying techniques have significantly heightened interest in innovative technologies that improve the yield and quality of dried goods, enhance energy efficiency, and facilitate continuous monitoring of drying processes. Artificial intelligence (AI)-enabled optical sensing technologies have emerged as promising tools for smart and precise monitoring of food drying processes. Food industries can leverage AI-enabled optical sensing technologies to gain a comprehensive understanding of drying dynamics, optimize process parameters, identify potential issues, and ensure product consistency and quality. This review systematically discusses the application of selected optical sensing technologies, such as near-infrared (NIR) spectroscopy, hyperspectral imaging, and conventional imaging (i.e., computer vision) powered by AI. After covering the basics of optical sensing technologies for smart drying and an overview of different drying methods, it explores various optical sensing techniques for monitoring and quality control of drying processes. Additionally, the review addresses the limitations of these optical sensing technologies and their prospects in smart drying.
