Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment

Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment

The effects of different heat treatments on abalones’ texture properties and sensory characteristics were studied. Thermal processing of abalone muscle was analyzed to determine the optimal heat treatment condition based on fuzzy evaluation. The results showed that heat treatment at 85°C for 1 hour...

Full description

Bibliographic Details
Main Authors: Jiaxu Dong, Xiaoyan Fang, Huihui Wang, Xu Zhang, Xueheng Tao
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Journal of Food Quality
Online Access:http://dx.doi.org/10.1155/2017/2069470
id doaj-89dcd9fc869d404a9cf117562d5f8c4c
record_format Article
spelling doaj-89dcd9fc869d404a9cf117562d5f8c4c2020-11-25T00:33:32ZengHindawi-WileyJournal of Food Quality0146-94281745-45572017-01-01201710.1155/2017/20694702069470Abalone Muscle Texture Evaluation and Prediction Based on TPA ExperimentJiaxu Dong0Xiaoyan Fang1Huihui Wang2Xu Zhang3Xueheng Tao4Key Laboratory for Seafood Processing Technology and Equipment of Liaoning Province, Dalian Polytechnic University, Dalian 116034, ChinaKey Laboratory for Seafood Processing Technology and Equipment of Liaoning Province, Dalian Polytechnic University, Dalian 116034, ChinaKey Laboratory for Seafood Processing Technology and Equipment of Liaoning Province, Dalian Polytechnic University, Dalian 116034, ChinaKey Laboratory for Seafood Processing Technology and Equipment of Liaoning Province, Dalian Polytechnic University, Dalian 116034, ChinaKey Laboratory for Seafood Processing Technology and Equipment of Liaoning Province, Dalian Polytechnic University, Dalian 116034, ChinaThe effects of different heat treatments on abalones’ texture properties and sensory characteristics were studied. Thermal processing of abalone muscle was analyzed to determine the optimal heat treatment condition based on fuzzy evaluation. The results showed that heat treatment at 85°C for 1 hour had certain desirable effects on the properties of the abalone meat. Specifically, a back propagation (BP) neural network was introduced to predict the equations of statistically significant sensory hardness, springiness, and smell using the texture data gained through TPA (texture profile analysis) experiments as input and sensory evaluation data as the desired output. The final outcome was that the predictability was proved to be satisfactory, with an average error of 6.93%.http://dx.doi.org/10.1155/2017/2069470
collection DOAJ
language English
format Article
sources DOAJ
author Jiaxu Dong
Xiaoyan Fang
Huihui Wang
Xu Zhang
Xueheng Tao
spellingShingle Jiaxu Dong
Xiaoyan Fang
Huihui Wang
Xu Zhang
Xueheng Tao
Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
Journal of Food Quality
author_facet Jiaxu Dong
Xiaoyan Fang
Huihui Wang
Xu Zhang
Xueheng Tao
author_sort Jiaxu Dong
title Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
title_short Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
title_full Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
title_fullStr Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
title_full_unstemmed Abalone Muscle Texture Evaluation and Prediction Based on TPA Experiment
title_sort abalone muscle texture evaluation and prediction based on tpa experiment
publisher Hindawi-Wiley
series Journal of Food Quality
issn 0146-9428
1745-4557
publishDate 2017-01-01
description The effects of different heat treatments on abalones’ texture properties and sensory characteristics were studied. Thermal processing of abalone muscle was analyzed to determine the optimal heat treatment condition based on fuzzy evaluation. The results showed that heat treatment at 85°C for 1 hour had certain desirable effects on the properties of the abalone meat. Specifically, a back propagation (BP) neural network was introduced to predict the equations of statistically significant sensory hardness, springiness, and smell using the texture data gained through TPA (texture profile analysis) experiments as input and sensory evaluation data as the desired output. The final outcome was that the predictability was proved to be satisfactory, with an average error of 6.93%.
url http://dx.doi.org/10.1155/2017/2069470
work_keys_str_mv AT jiaxudong abalonemuscletextureevaluationandpredictionbasedontpaexperiment
AT xiaoyanfang abalonemuscletextureevaluationandpredictionbasedontpaexperiment
AT huihuiwang abalonemuscletextureevaluationandpredictionbasedontpaexperiment
AT xuzhang abalonemuscletextureevaluationandpredictionbasedontpaexperiment
AT xuehengtao abalonemuscletextureevaluationandpredictionbasedontpaexperiment
_version_ 1725316296141176832

Similar Items