Kono, S., Kawamura, I., Yamagami, S., Araki, T., and Sagara, Y. 2016. ANN modeling for optimum storage condition based on viscoelastic characteristics and sensory evaluation of frozen cooked rice. ⇒ScienceDirect ⇒ResearchGate International Journal of Refrigeration 65: 218-227.(査読有) Highlights • Optimum frozen conditions of cooked rice have been predicted by ANN. • Tensipresser was a useful tool for predicting the scores for textural evaluation. • Deterioration of cooked rice attributed to the change of viscoelasticity. • Storage conditions affected the measured values of hardness and adhesiveness • Viscoelastic deteriorations also depended on the thawing methods. Abstract The optimum frozen condition of cooked rice has been predicted by artificial neural network (ANN) based on the data obtained from sensory evaluations as well as viscoelastic measurements. Cooked rice was frozen and stored at −5, −15, and −45 °C for 0, 10, 30, 60 and 90 days. Then, after the samples were thawed by natural convection air at room temperature or microwave heating, the viscoelastic parameters were measured with the Tensipresser and sensory scores were evaluated by a 7-point scale. The sensory scores were predicted with high accuracy from the viscoelastic parameters by ANN models. In addition, the ANN model …
ANN modeling for optimum storage condition based on viscoelastic characteristics and sensory evaluation of frozen cooked rice
Optimum storage temperature of frozen cooked rice predicted by ice crystal measurement, sensory evaluation and artificial neural network
Kono, S., Kawamura, I., Yamagami, S., Araki, T., and Sagara, Y. 2015. Optimum storage temperature of frozen cooked rice predicted by ice crystal measurement, sensory evaluation and artificial neural network. ⇒ScienceDirect ⇒ResearchGate International Journal of Refrigeration 56: 165-172. (査読有) Highlights • A fluorescence staining method was used for the measurement of ice crystals. • Freezing and storage temperatures significantly affected the ice crystal morphology. • The ice crystal size varied inversely with the palatability scores. • The model provides a useful methodology to identify the quality of frozen cooked rice. Abstract Optimum temperature conditions of frozen cooked rice during storage have been predicted by artificial neural network (ANN) using the dataset of ice crystal measurement and sensory evaluation. Cooked rice samples were frozen and preserved at −5, −15, −30, and −45 °C for 1, 5, 10, 30 and 90 days. Then the cross-sectional images of the samples were captured using a fluorescence staining method to measure the equivalent diameters of ice crystals in the samples. Textural and sensory attributes of the samples thawed by microwave heating and air at room temperature were evaluated by 690 consumer panelists. The equivalent diameters of ice crystals were …