• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Cogent Food & Agriculture >Study of adulteration of extra virgin olive oil with peanut oil using FTIR spectroscopy and chemometrics
【24h】

Study of adulteration of extra virgin olive oil with peanut oil using FTIR spectroscopy and chemometrics

机译：FTIR光谱和化学计量学研究特级初榨橄榄油与花生油的掺假

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A methodology based on Fourier transform infrared spectroscopy with attenuated total reflectance sampling technique, combined with multivariate analysis, was developed to monitor adulteration of extra virgin olive oil (EVOO) with peanut oil (PEO). Principal components regression (PCR), partial least squares regression (PLS-R), and linear discriminant analysis (LDA) allowed quantification of percentage of adulteration based on spectral data of 192 samples. Wavenumbers associated with the biochemical differences among several types of edible oils were investigated by principal component analysis. Two sets of frequencies were selected in order to establish a robust regression model. Set A consisted on the frequency regions from 600 to 1,800?cm~(?1) and from 2,750 to 3,050?cm~(?1). Set B comprised 17 discrete peak absorbance frequencies for which the communality value was higher than 0.6. Analysis of an external set of 25 samples allowed the validation and evaluation of the predictability of the models. When using a specific set of discrete peak absorbance frequencies, the R ~(2) coefficients for the prediction were 0.960 and 0.977, and the root mean square error (RMSE) were 1.49 and 1.05% V/V when using the PCR or PLS-R models, respectively. LDA was successful in the binary classification presence/absence of PEO in adulterated EVOO (with 5% V/V of less of PEO). LDA provided 92.3% correct classification for the calibration set and 88.3% correct classification when cross-validated. The lowest detectable concentration of PEO in EVOO was the lowest adulteration level studied, 0.5% V/V.
机译：开发了一种基于傅立叶变换红外光谱技术和衰减全反射采样技术的方法，并结合多变量分析，以监测特级初榨橄榄油（EVOO）与花生油（PEO）的掺假情况。主成分回归（PCR），偏最小二乘回归（PLS-R）和线性判别分析（LDA）允许基于192个样品的光谱数据对掺假百分比进行定量。通过主成分分析研究了与几种食用油之间生化差异相关的波数。选择两组频率以建立鲁棒的回归模型。集合A包括从600到1,800？cm〜（？1）和从2,750到3,050？cm〜（？1）的频率区域。 B组包含17个离散的峰值吸收频率，其社区值高于0.6。对一组25个样本的外部分析可以验证和评估模型的可预测性。当使用一组特定的离散峰值吸收频率时，使用PCR的预测的R〜（2）系数为0.960和0.977，均方根误差（RMSE）为1.49和1.05％V / V或PLS-R型号。 LDA在掺假EVOO中以二元分类存在/不存在PEO的情况下成功完成（PEO减少5％V / V）。当交叉验证时，LDA为校准集提供了92.3％的正确分类，并为88.3％提供了正确的分类。 EVOO中PEO的最低可检测浓度是研究的最低掺假水平，即0.5％V / V。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号