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Effect of freezing and thawing on the quality of durian (Durio zibethinus Murray) pulp

mishoumu Papers, papers-after-2016 , , , , , , ,

Tagubase, J. L., Ueno, S., Yoshie, Y., and Araki, T. 2016. Effect of freezing and thawing on the quality of durian (Durio zibethinus Murray) pulp ⇒_pdf ⇒J-STAGE Transactions of the Japan Society of Refrigerating and Air Conditioning Engineers 33: 267-272. （査読有） Summary The effect of freezing, and iced and hot water thawing on the quality of durian pulp was investigated. Mature durian pulp was removed with seeds, vacuum-packed, and frozen at -20°C. Thawing in iced water (~0°C) and hot water (~90°C) was then applied and the quality of the pulp was assessed based on physicochemical properties (pH, moisture content, soluble solids concentration (SSC), color, sugar content (sucrose, glucose, and fructose), and organic acid content (succinic acid and citric acid ), texture and smell profile. Overall, the freezing and thawing conditions, particularly the hot water thawing, posed an effect to the moisture content, color, and smell profile of the durian pulp. A significant increase in the moisture content, as well as a decrease in the color brightness was observed. Furthermore, the hot water-thawing process also induced slight variation to the smell attribute and strength of the entirety of smell. Although the …

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ANN modeling for optimum storage condition based on viscoelastic characteristics and sensory evaluation of frozen cooked rice

mishoumu Papers, papers-after-2016 , , , , , ,

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 …

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Coupled stepwise PLS-VIP and ANN modeling for identifying and ranking aroma components conforming palatability of cheddar cheese

mishoumu Papers, papers-2011-2015 , , , , , ,

Morita, A., Araki, T., Ikegami, S., Okaue, M., Sumi, M., Ueda, R., and Sagara, Y. 2015. Coupled stepwise PLS-VIP and ANN modeling for identifying and ranking aroma components conforming palatability of cheddar cheese ⇒_pdf ⇒CiNii ⇒J-STAGE Food Science and Technology Research 21: 175-186. （査読有） Abstract A consumer-oriented methodological approach for the quality evaluation of Cheddar cheese as a typical fermented food was developed. Datasets were obtained from gas chromatography/olfactometry (GC/O) analysis and sensory evaluation of 10 Cheddar cheese samples. The GC/O analysis identified 43 aroma components under the categories of 14 aroma descriptors. Consumer evaluation of palatability was performed by 59 housewives. Factor analysis of the GC/O data identified aroma descriptors that have positive or negative correlations with palatability scores. Twelve aroma components were prioritized using stepwise partial least-squares regression with variable importance in projection (PLS-VIP). An artificial neural network (ANN) model was constructed to demonstrate the nonlinear relationships among the raw GC/O data of the samples and the palatability scores. Coupling stepwise PLS-VIP and ANN resulted in successful identification and ranking of aroma components contributing to the palatability of Cheddar cheese, and in modeling their nonlinear relationships.

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