Open AccessNon-destructive geographical traceability of sea cucumber ( Apostichopus japonicus ) using near infrared spectroscopy combined with chemometric methods
Author(s) -
Xiuhan Guo,
Rui Cai,
Shisheng Wang,
Bo Tang,
Yueqing Li,
Weiqian Zhao
Publication year - 2018
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.170714
Subject(s) - apostichopus japonicus , sea cucumber , traceability , partial least squares regression , principal component analysis , mahalanobis distance , correlation coefficient , calibration , multivariate statistics , mathematics , statistics , environmental science , computer science , biology , ecology
Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber ( Apostichopus japonicus ) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China.