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Evaluation of dual-frequency multi-angle ultrasound on physicochemical properties of tofu gel and its finished product by TOPSIS-entropy weight method.

ABSTRACT: The effects of dual-frequency (40 + 20 kHz) and multi-angle ultrasound (0°, 30°, 45°) on the coagulation state, network structure, flavor and protein conformation of tofu gel were studied. The results showed that the gel flavor of 40 + 20 kHz 0° group was the best and fluorescence intensity was low. The gel flavor in the 40 + 20 kHz 30° group was better than the group without ultrasound, and hydrophobic interaction and disulfide bond content was the largest. Meanwhile, the degree of protein cross-link was increased. The gel in 40 + 20 kHz 45° group had tightly gel state, high thermal stability, but poor flavor. Combined with The Order Preference by Similarity to Ideal Solution (TOPSIS)-entropy weight method, the 40 + 20 kHz 30° group, was the best ultrasonic treatment of gel. It can change the interaction between proteins, promote protein cross-link, and form a uniform and dense gel network. Finally, the hardness and moisture content of finished tofu were increased significantly, and the quality was improved.

SUBMITTER: Zhang L

PROVIDER: S-EPMC9579706 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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Evaluation of dual-frequency multi-angle ultrasound on physicochemical properties of tofu gel and its finished product by TOPSIS-entropy weight method.

Zhang Lei L Wang Xue X Qu Wenjuan W Zhang Ao A Wahia Hafida H Gao Xianli X Ma Haile H Zhou Cunshan C

Ultrasonics sonochemistry 20221010

The effects of dual-frequency (40 + 20 kHz) and multi-angle ultrasound (0°, 30°, 45°) on the coagulation state, network structure, flavor and protein conformation of tofu gel were studied. The results showed that the gel flavor of 40 + 20 kHz 0° group was the best and fluorescence intensity was low. The gel flavor in the 40 + 20 kHz 30° group was better than the group without ultrasound, and hydrophobic interaction and disulfide bond content was the largest. Meanwhile, the degree of protein cros ...[more]

PMID: 36252385

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Project description:Context and backgroundCorona virus (COVID) has rapidly gained a foothold and caused a global pandemic. Particularists try their best to tackle this global crisis. New challenges outlined from various medical perspectives may require a novel design solution. Asymptomatic COVID-19 carriers show different health conditions and no symptoms; hence, a differentiation process is required to avert the risk of chronic virus carriers.ObjectivesLaboratory criteria and patient dataset are compulsory in constructing a new framework. Prioritisation is a popular topic and a complex issue for patients with COVID-19, especially for asymptomatic carriers due to multi-laboratory criteria, criterion importance and trade-off amongst these criteria. This study presents new integrated decision-making framework that handles the prioritisation of patients with COVID-19 and can detect the health conditions of asymptomatic carriers.MethodsThe methodology includes four phases. Firstly, eight important laboratory criteria are chosen using two feature selection approaches. Real and simulation datasets from various medical perspectives are integrated to produce a new dataset involving 56 patients with different health conditions and can be used to check asymptomatic cases that can be detected within the prioritisation configuration. The first phase aims to develop a new decision matrix depending on the intersection between 'multi-laboratory criteria' and 'COVID-19 patient list'. In the second phase, entropy is utilised to set the objective weight, and TOPSIS is adapted to prioritise patients in the third phase. Finally, objective validation is performed.ResultsThe patients are prioritised based on the selected criteria in descending order of health situation starting from the worst to the best. The proposed framework can discriminate among mild, serious and critical conditions and put patients in a queue while considering asymptomatic carriers. Validation findings revealed that the patients are classified into four equal groups and showed significant differences in their scores, indicating the validity of ranking.ConclusionsThis study implies and discusses the numerous benefits of the suggested framework in detecting/recognising the health condition of patients prior to discharge, supporting the hospitalisation characteristics, managing patient care and optimising clinical prediction rule.

Dataset Information

Evaluation of dual-frequency multi-angle ultrasound on physicochemical properties of tofu gel and its finished product by TOPSIS-entropy weight method.

Publications

Evaluation of dual-frequency multi-angle ultrasound on physicochemical properties of tofu gel and its finished product by TOPSIS-entropy weight method.

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