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通过傅里叶变换(FT)近红外光谱法和傅里叶变换拉曼光谱法测定植物油对柴油/生物柴油混合物的掺假情况。

Adulteration of diesel/biodiesel blends by vegetable oil as determined by Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy.

作者信息

Oliveira Flavia C C, Brandão Christian R R, Ramalho Hugo F, da Costa Leonardo A F, Suarez Paulo A Z, Rubim Joel C

机构信息

Laboratório de Materiais e Combustíveis (LMC), Instituto de Química da Universidade de Brasília, CP 04478, 70919-970, DF, Brazil.

出版信息

Anal Chim Acta. 2007 Mar 28;587(2):194-9. doi: 10.1016/j.aca.2007.01.045. Epub 2007 Jan 21.

Abstract

In this work it has been shown that the routine ASTM methods (ASTM 4052, ASTM D 445, ASTM D 4737, ASTM D 93, and ASTM D 86) recommended by the ANP (the Brazilian National Agency for Petroleum, Natural Gas and Biofuels) to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils. Considering the previous and actual problems with fuel adulterations in Brazil, we have investigated the application of vibrational spectroscopy (Fourier transform (FT) near infrared spectrometry and FT-Raman) to identify adulterations of B2 and B5 blends with vegetable oils. Partial least square regression (PLS), principal component regression (PCR), and artificial neural network (ANN) calibration models were designed and their relative performances were evaluated by external validation using the F-test. The PCR, PLS, and ANN calibration models based on the Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples. Other 62 samples were used in the validation and external validation, for a total of 182 samples. The results have shown that among the designed calibration models, the ANN/FT-Raman presented the best accuracy (0.028%, w/w) for samples used in the external validation.

摘要

在本研究中,已表明巴西国家石油、天然气和生物燃料局(ANP)推荐的用于测定柴油/生物柴油混合物质量的常规ASTM方法(ASTM 4052、ASTM D 445、ASTM D 4737、ASTM D 93和ASTM D 86)不适用于防止B2或B5混合物被植物油掺假。考虑到巴西以往和当前燃料掺假的问题,我们研究了振动光谱法(傅里叶变换(FT)近红外光谱法和FT-拉曼光谱法)在识别B2和B5混合物被植物油掺假方面的应用。设计了偏最小二乘回归(PLS)、主成分回归(PCR)和人工神经网络(ANN)校准模型,并使用F检验通过外部验证评估了它们的相对性能。基于傅里叶变换(FT)近红外光谱法和FT-拉曼光谱法的PCR、PLS和ANN校准模型是使用120个样品设计的。另外62个样品用于验证和外部验证,总共182个样品。结果表明,在所设计的校准模型中,ANN/FT-拉曼对外部验证中使用的样品呈现出最佳准确度(0.028%,w/w)。

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