Optimum storage temperature of frozen cooked rice predicted by ice crystal measurement, sensory evaluation and artificial neural network

Effect of different freeze drying cycle in Semimembranous and Gluteus Medius bovine muscles: changes on microstructure, colour, texture and physicochemical parameters

“…An interesting alternative for analysing the surface of food products and quantifying appearance characteristics is to use computerised image analysis techniques (Mendoza et al ., ; Saini et al ., ). Computer vision analysis is a method that objectively measure colour patterns in non‐uniformly coloured surfaces, and also determine other physical features such as image texture, morphological elements and defects (Kono et al ., ). Moreover, with the advantage of superior speed, accuracy and recent advances in hardware and software, computer vision has attracted a significant amount of research aimed at replacing human inspection.…”

Texture and color analysis of freeze-dried potato (cv. Spunta) using instrumental and image analysis techniques

“…This technique makes it possible to obtain measurements from digitalized images providing objective evaluations of the morpho-colorimetric features of samples, a method that is more quantitative and less biased than the common method of visual perception, which is prone to variation due to the personal opinions of inspectors or trained panels. [7] Grey level co-occurrence matrix (GLCM) is probably one of the most frequently cited methods for the texture analysis of images. The texture of an image corresponds to the spatial organization of pixels in the image and the co-occurrence matrix describes the occurrence of grey level between two pixels separated in the image by a given distance.…”

Neural networks in food industry

“…It was found that the proposed model presented better quality predictions than the kinetic models used, this was determined by the correlation coefficients that were 0.94 and 0.96 for the taste and sensory score parameters, respectively and 0.74 and 0 , 86 for the parameters mentioned above, for the proposed kinetic model. In a study conducted by Kono et al, [16] the optimum cold storage temperature of cooked rice was predicted through RNA with a hidden layer between the input and output layers using an algorithm backpropagation type. The cooked rice samples were frozen and stored at (-5, -15, -30 and -45) °C for (1, 5, 10, 30 and 90) days.…”