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利用近红外光谱结合化学计量学方法对海参进行无损地理溯源

Non-destructive geographical traceability of sea cucumber () using near infrared spectroscopy combined with chemometric methods.

作者信息

Guo Xiuhan, Cai Rui, Wang Shisheng, Tang Bo, Li Yueqing, Zhao Weijie

机构信息

School of Pharmaceutical Science and Technology, Dalian University of Technology, No.2 Linggong Road, Hi-Tech Industry Zone District, Dalian 116023, People's Republic of China.

State Key Laboratory of Fine Chemicals, Dalian University of Technology, No.2 Linggong Road, Hi-Tech Industry Zone District, Dalian 116023, People's Republic of China.

出版信息

R Soc Open Sci. 2018 Jan 17;5(1):170714. doi: 10.1098/rsos.170714. eCollection 2018 Jan.

DOI:10.1098/rsos.170714
PMID:29410795
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5792872/
Abstract

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 () 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.

摘要

海参是全球主要的滋补海产品,地理来源可追溯性是其质量和安全控制的重要组成部分。在本研究中,提出了一种利用近红外光谱(NIRS)和多元分析方法对中国北海和东海海参进行无损产地溯源的方法。测定了189个新鲜海参样品的总脂肪含量,并采用偏最小二乘法(PLS)回归建立了定量NIRS模型。运用有序预测变量选择算法选择可行的波长区域来构建PLS和鉴别模型。鉴别模型通过主成分分析结合马氏距离和缩放到第一范围算法建立。在最优PLS模型的测试集中,预测均方根误差为0.45,相关系数为0.90。鉴别校准模型和测试模型的正确分类率均达到100%。总体结果表明,NIRS方法结合化学计量分析是一种适用于中国九个产地新鲜海参样品产地溯源和鉴别的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/6c48d3ee5e8f/rsos170714-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/7aa0878d6f9f/rsos170714-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/e168f5d03634/rsos170714-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/87da14e9fdbb/rsos170714-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/fa2187b20183/rsos170714-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/6c48d3ee5e8f/rsos170714-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/7aa0878d6f9f/rsos170714-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/e168f5d03634/rsos170714-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/87da14e9fdbb/rsos170714-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/fa2187b20183/rsos170714-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4486/5792872/6c48d3ee5e8f/rsos170714-g5.jpg

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