Artificial intelligence assisted technologies for controlling the drying of fruits and vegetables using physical fields: A review. (November 2020)

• Record Type: Journal Article
• Authors: Chen, Jieling; Zhang, Min; Xu, Baoguo; Sun, Jincai; Mujumdar, Arun S.
• Is Part Of: Trends in food science & technology. Volume 105(2020)
• Page Start: 251
• Page End: 260
• Publication Date: 2020-11
• Subjects: Artificial neural network -- Fuzzy logic -- Computer vision -- Microwave drying -- Advanced process control; Food industry and trade -- Periodicals; Food -- Biotechnology -- Periodicals; 664.005
• DOI: 10.1016/j.tifs.2020.08.015
• Languages: English
• ISSNs: 0924-2244

Abstract

Abstract: Background: Artificial intelligence (AI), which is characterized by ability to learn and adapt continuously, can enhance the fault tolerance and robustness in process control. Application of high-efficiency physical fields such as microwave, radio frequency, infrared radiation and ultrasonic fields can result in efficient production of dried fruit and vegetable products with high quality. Whether the combination of AI technology and efficient physical field can obtain better dried products of fruits and vegetables, and how AI can be applied in the drying process of fruit and vegetable, has attracted extensive attention. Scope and approach: The application of artificial intelligence technology to assist the efficient physical field in the drying of fruits and vegetables is the development trend of fruit and vegetable drying industry in the future. This paper aims to provide a concise overview of recent research in the rapidly emerging area of AI-assisted drying of fruits and vegetables using physical fields to provide energy for drying process. A selection of AI technologies is introduced such as sensor technology, computer vision systems as well as a few relevant AI technologies used in the drying process of fruits or vegetables. Afterwards, it summarizes the application of artificial intelligence in the physical drying of fruits and vegetables, and how to improve the shortcomings of highly efficient physical field drying of fruits and vegetables with AI. Key findings and conclusions: The application of high efficiency physical field in the drying process of fruits and vegetables can solve the problems of large energy consumption, uneven drying, poor sensory evaluation, and large nutrient loss. The drying process and the corresponding drying model of fruits and vegetables can be detected and controlled online, and the optimum drying scheme can be determined using artificial intelligence technology. The most important thing is to make up for the shortcomings of highly efficient physical field drying of fruits and vegetables. The artificial intelligence technology has a promising application prospect to assist the efficient physical field drying of fruits and vegetables. Highlights: Introduce artificial intelligence technologies, including sensor technology, computer vision system and other technologies. The application of artificial intelligence (sensor, computer vision, ANN, GA) in fruit and vegetable drying was reviewed. The application of artificial intelligence technology combined in fruit and vegetable drying using efficient physical field. The development suggestion of artificial intelligence drying technology based on efficient physical field was provided.