1 Citation 286 Views 41 Downloads
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 predictors selection
(OPS) algorithm was performed to select feasible wavelength regions for
the construction of PLS and identification models. The identification
model was developed by the principal component analysis combined with
Mahalanobis distance (PCA-MD) and Scaling to the first range algorithms.
In the test set of the optimum PLS models, the root mean square errors of
prediction (RMSEP) was 0.45, and correlation coefficients (R2) was 0.90.
The correct classification rates of 100% were obtained both in
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.
286 views reported since publication in 2017.