食品科学

• 分析检测 • 上一篇    下一篇

应用近红外光谱技术快速测定葵花籽油的理化指标

卢海燕,王 欣*,赵婷婷,刘宝林   

  1. 上海理工大学食品质量与安全研究所,上海 200093
  • 出版日期:2014-11-25 发布日期:2014-12-09
  • 基金资助:

    国家自然科学基金青年科学基金项目(NSFC31201365);上海市科委重点攻关项目(11142200403);
    上海市教委科研创新项目(11YZ109)

Rapid Determination of Physicochemical Indicators of Sunflower Oil by Near-Infrared Spectroscopy

LU Hai-yan, WANG Xin*, ZHAO Ting-ting, LIU Bao-lin   

  1. Institute of Food Safety and Quality, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Online:2014-11-25 Published:2014-12-09

摘要:

应用傅里叶变换近红外光谱技术结合不同的定量分析方法建立葵花籽油4 种不同理化指标的快速预测模型。在用化学方法获得不同氧化程度葵花籽油的共轭二烯、共轭三烯、p-茴香胺值、总极性化合物的参照数据的基础上,比较不同光谱预处理方法及建模方法对预测效果的影响。结果表明,葵花籽油原始光谱不经处理、经Norris平滑和一阶导数处理或Norris平滑和二阶导数处理后应用偏最小二乘法可分别建立共轭二烯、共轭三烯、p-茴香胺值及总极性化合物的预测模型,建模决定系数均在0.98以上,交互验证均方根误差分别为1.37、0.38%、0.51、0.46,相对预测均方根误差分别为1.24、0.18%、0.40、0.16。说明利用近红外光谱技术结合化学计量法可实现不同氧化程度葵花籽油理化指标的快速、准确检测。

关键词: 葵花籽油, 理化指标, 近红外光谱, 化学计量法, 偏最小二乘法

Abstract:

In this work, near-infrared spectroscopy (NIR) was applied for the rapid determination of 4 physicochemical
indicators of sunflower oil with the aid of several quantitative methods. The basic reference values conjugated dienes
(K232) and conjugated tienes (K270), p-anisidine value (p-AV), and total polar compounds (TPC) of the oxidized sunflower
oil samples, were obtained by chemical methods. The effects of data pre-processing method and modeling method on the
accuracy of calibration models were investigated. The results indicated that the precision of analysis for K232, K270, and
p-AV could be improved when the original spectra were pre-processed by Norris smoothing algorithms combined with first
derivative or with second derivative, while the analysis for TPC could provide the best result with the original spectra. After
spectral pretreatments, the quantitative analysis calibrations of the 4 physicochemical indicators could be developed using
partial least square regression method, and the RC were 0.98, 0.99, 0.99 and 0.98, respectively, with RMSECV of 1.37, 0.38%,
0.51 and 0.46, and RMSEP of 1.24, 0.18%, 0.40 and 0.16, respectively. The predicted values were accurate and reliable.
Therefore, NIR combined with chemometric methods could be used to determine the physicochemical indicators of edible
oils with rapidity and accuracy.

Key words: sunflower oil, physicochemical indicators, near-infrared spectroscopy, chemometry, partial least squares

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