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Rapid and non-destructive freshness evaluation of squid by FTIR coupled with chemometric techniques.
Xu, Zheng; Zhu, Shichen; Wang, Wenjie; Liu, Shulai; Zhou, Xuxia; Dai, Wangli; Ding, Yuting.
Afiliação
  • Xu Z; College of Food Science and Technology, Zhejiang University of Technology, Hangzhou, China.
  • Zhu S; Key Laboratory of Marine Fishery Resources Exploitment & Utilization of Zhejiang Province, Hangzhou, China.
  • Wang W; National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou), Hangzhou, China.
  • Liu S; College of Food Science and Technology, Zhejiang University of Technology, Hangzhou, China.
  • Zhou X; Key Laboratory of Marine Fishery Resources Exploitment & Utilization of Zhejiang Province, Hangzhou, China.
  • Dai W; National R&D Branch Center for Pelagic Aquatic Products Processing (Hangzhou), Hangzhou, China.
  • Ding Y; Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian, China.
J Sci Food Agric ; 102(7): 3000-3009, 2022 May.
Article em En | MEDLINE | ID: mdl-34773403
ABSTRACT

BACKGROUND:

Freshness is an important quality of squid with respect to determining the market price. The methods of evaluation of freshness fail to be widely used as a result of the lack of rapidity and quantitation. In the present study, a rapid and non-destructive quantification of squid freshness by Fourier transform infrared spectroscopy (FTIR) spectra combined with chemometric techniques was performed.

RESULTS:

The relatively linear content change of trimethylamine (TMA-N) and dimethylamine (DMA-N) of squid during storage at 4 °C indicated their feasibility as a freshness indicator, as also confirmed by sensory evaluation. The spectral changes were mainly caused by the degradation of proteins and the production of amines by two-dimensional infrared correlation spectroscopy, among which TMA-N, DMA-N and putrescine were the main amines. The successive projections algorithm (SPA) was employed to select the sensitive wavenumbers to freshness for modeling prediction including partial least-squares regression, support vector regression (SVR) and back-propagation artificial neural network. Generally, the SPA-SVR model of the selected characteristic wavenumber showed a higher prediction accuracy for DMA-N (R2 P  = 0.951; RMSEP  = 0.218), whereas both SPA-SVR (R2 P  = 0.929; RMSEP  = 2.602) and Full-SVR (R2 P  = 0.941; RMSEP  = 2.492) models had a higher predictive ability of TMA-N.

CONCLUSION:

The results of the present study demonstrate that FTIR spectroscopy coupled with multivariate calibration shows significant potential for the prediction of freshness in squid. © 2021 Society of Chemical Industry.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Decapodiformes / Alimentos Marinhos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Decapodiformes / Alimentos Marinhos Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2022 Tipo de documento: Article