Color assessment of freeze‐dried mushrooms using Photoshop and optimization with genetic algorithm. (30th October 2018)

• Record Type: Journal Article
• Authors: Tarafdar, Ayon; Shahi, Navin Chandra; Singh, Anupama
• Is Part Of: Journal of food process engineering. Volume 43:Number 1(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-30
• Subjects: Food industry and trade -- Periodicals; Food -- Analysis -- Periodicals; 664.005
• DOI: 10.1111/jfpe.12920
• Languages: English
• ISSNs: 0145-8876

Abstract

Abstract: An image analysis and optimization technique exploiting Photoshop software coupled with genetic algorithm (GA) for a food processing application has been explored. Color characteristics ( L*, a*, b*, change in color, hue, and chroma) for freeze‐dried mushrooms were determined. Mathematical models for predicting color characteristics of dried mushrooms with change in processing conditions were obtained using second order polynomials. Freeze‐drying (FD) conditions were optimized by an evolutionary algorithm. Results indicated that the temperature of primary and secondary drying cycles during FD have a significant impact on color. The search for optimum process conditions manifesting minimum color variation in the dried product as compared with fresh mushroom samples was done. Optimized response for color change and chroma were obtained as 4.58 and 9.78, respectively, after a 10 h drying cycle. The models developed can be used to determine the drying time for desired product color and processing conditions of FD. Practical applications: Consumer preference for color is often a concern for food processing industries. Color detection of food materials in bulk needs to be performed rapidly and at low costs, which cannot be easily achieved using sophisticated color detection devices. The use of image acquisition system coupled with imaging software and modeling and optimization tools could provide a simple solution for the identification of superior food products based on image analysis.