Ultrasound-assisted thawing accelerates the thawing of common carp (Cyprinus carpio) and improves its muscle quality

鲤鱼 鲤鱼 挑剔 微观结构 超声波传感器 超声波 材料科学 解剖 渔业 生物 动物科学 复合材料 声学 物理
作者
Qinxiu Sun,Baohua Kong,Shucheng Liu,Zheng Ouyang,Chao Zhang
出处
期刊:Lebensmittel-Wissenschaft & Technologie [Elsevier BV]
卷期号:141: 111080-111080 被引量:97
标识
DOI:10.1016/j.lwt.2021.111080
摘要

The effects of different power (0, 100, 300, and 500 W) ultrasonic-assisted immersion thawing (UT) on the thawing time and muscle quality (thawing/cooking loss, shear force, colour, water distribution and microstructure) of common carp (Cyprinus carpio) were investigated. The results showed that the thawing time decreased gradually with the increase of ultrasonic power, and the thawing time of ultrasonic thawing at 500 W (UT-500) was the shortest among all the thawing methods (P < 0.05). However, the thawing and cooking losses of UT-500 samples were the largest among all thawed samples, while those of UT-300 samples were the smallest (P < 0.05). In addition, the result of fish colour indicated that UT-300 was beneficial for maintaining the colour of fish muscle after thawing. Low field nuclear magnetic resonance analysis showed that UT-300 effectively reduced the fluidity and loss of immobilised and free water. Microstructure analysis showed that the microstructure of UT-300 sample was more complete than that of other thawing treatment samples. Therefore, appropriate ultrasonic power (300 W) during thawing could accelerate the thawing process of frozen common carp, and maintain its muscle quality.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
2秒前
Naranja完成签到 ,获得积分10
2秒前
3秒前
情怀应助khalil采纳,获得10
3秒前
干净的琦完成签到,获得积分0
4秒前
牛太虚发布了新的文献求助10
4秒前
5秒前
汉堡包应助耍酷橘子采纳,获得10
5秒前
6秒前
6秒前
A3886987发布了新的文献求助10
6秒前
xuan发布了新的文献求助10
7秒前
NexusExplorer应助PhDL1采纳,获得10
7秒前
汉堡包应助飞不出个future采纳,获得20
7秒前
充电宝应助书记采纳,获得10
7秒前
kk发布了新的文献求助10
7秒前
黄瓜橙橙完成签到,获得积分0
8秒前
英姑应助川川采纳,获得10
8秒前
xiaojin完成签到,获得积分10
8秒前
Ava应助MDsi采纳,获得10
8秒前
万金油完成签到,获得积分10
9秒前
shiroki发布了新的文献求助80
9秒前
10秒前
10秒前
在水一方应助沧海云帆采纳,获得10
10秒前
10秒前
wangyu发布了新的文献求助10
10秒前
songkoro发布了新的文献求助10
11秒前
Ming完成签到,获得积分10
11秒前
11秒前
白子墨发布了新的文献求助10
11秒前
一念之间发布了新的文献求助10
12秒前
12秒前
星辰大海应助得到采纳,获得10
13秒前
天天快乐应助地精术士采纳,获得10
13秒前
今后应助sin30cos60采纳,获得10
13秒前
13秒前
xuan发布了新的文献求助10
13秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
How to Use Machine Learning in Chemistry: An Introduction 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7583093
求助须知:如何正确求助?哪些是违规求助? 9161776
关于积分的说明 19604859
捐赠科研通 7165133
什么是DOI,文献DOI怎么找? 3266207
关于科研通互助平台的介绍 2431164
邀请新用户注册赠送积分活动 2257518