食品科学

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基于近红外光谱法的鱼粉快速判别

宋 涛,宋 军,刘耀敏,米学林,饶瑾瑜,赵 艳,范秀丽   

  1. 通威股份有限公司,水产畜禽营养与健康养殖农业部重点实验室,四川 成都 610041
  • 出版日期:2015-12-25 发布日期:2015-12-24
  • 基金资助:

    四川省科技支撑计划项目(2011NZ0071)

Rapid Discrimination of Different Fishmeals with Near-Infrared Spectroscopy

SONG Tao, SONG Jun, LIU Yaomin, MI Xuelin, RAO Jinyu, ZHAO Yan, FAN Xiuli   

  1. Key Laboratory of Aquatic, Livestock, Poultry Nutrition and Healthy Culturing, Ministry of Agriculture,
    Tongwei Co. Ltd., Chengdu 610041, China
  • Online:2015-12-25 Published:2015-12-24

摘要:

基于近红外漫反射光谱分析技术对市场上常见的淡水鱼粉、进口鱼粉和国产鱼粉3 类商品化的鱼粉样品进行自动化判别实验。通过分析鱼粉样品光谱之间的差异,采用主成分分析法建立鱼粉种类的定性判别的分类模型,光谱范围为波长1 100~2 498 nm,交互定标决定系数为0.913 5,交互定标标准误差为0.133 8。通过对验证样品的分析,建立的判别模型预判准确率达到84.6%,外部验证准确率达到100%。结果表明,近红外光谱技术结合化学计量学法可以作为一种快速、无损、可靠的方法用于鱼粉种类的判别。

关键词: 近红外光谱, 鱼粉, 判别, 种类, 主成分分析

Abstract:

A method was established for the automatic discrimination of three varieties of fishmeal by means of near infrared
spectroscopy (NIRS). Through analysis of the spectral differences of fishmeal samples, a discrimination model for different
types of fishmeal was developed by using t principal component analysis (PCA). The spectra were scanned from 1 100 nm
to 2 498 nm. The 1 minus variance ratio (1-VR) was 0.913 5 and the standard error of cross validation (SECV) was 0.133 8.
The accuracy rates of discriminate for calibration and external validation were 84.6% and 100%, respectively. The
results of the study indicate that NIRS combined with chemometrics is rapid, nondestructive, reliable and suitable for the
discrimination of three varieties of fishmeal.

Key words: near-infrared spectroscopy, fishmeal, discrimination, varieties, principal component analysis

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