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Quantification and classification of cotton biodiesel content in diesel blends, using mid-infrared spectroscopy and chemometric methods

机译：使用中红外光谱法和化学计量学方法对柴油混合物中棉花生物柴油含量进行定量和分类

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摘要

Two methodologies were developed to quantify and classify the content of cotton biodiesel in blends with diesel using medium infrared spectroscopy associated with partial least squares (PLS) and partial least squares discriminant analysis (PLS-DA). The PLS model, developed to determine the biodiesel content, was validated on the basis of some merit figures: selectivity, sensitivity, analytical sensitivity, limit of detection, limit of quantification and test for systematic error. The fit of this model was also evaluated using the correlation of current and predicted values of the calibration and prediction sets - a high correlation was observed, with correlation coefficient exceeding 0.99, and relatively low errors for the parameters. Qualitative monitoring was done using the PLS-DA model, whose efficiency was analyzed based on parameters of sensitivity and specificity. These parameters showed 100% correct classification in the samples used for calibration and prediction of biodiesel content in the Brazilian B10 fuel for diesel engines. The good results for application of the two models suggest that these analytical methodologies are feasible and efficient and can be used by inspection bodies for quantitative and qualitative control of this fuel. In addition, these methodologies are quick, of low cost and allow in-situ analysis with portable equipment.
机译：使用与偏最小二乘（PLS）和偏最小二乘判别分析（PLS-DA）相关联的中红外光谱技术，开发了两种方法来定量和分类棉柴油中棉生物柴油的含量。根据一些优点数据验证了开发用于确定生物柴油含量的PLS模型：选择性，灵敏度，分析灵敏度，检测限，定量限和系统误差测试。还使用校准集和预测集的当前值与预测值的相关性来评估此模型的拟合度-观察到较高的相关性，相关系数超过0.99，并且参数误差相对较低。使用PLS-DA模型进行定性监测，并基于敏感性和特异性参数分析其效率。这些参数显示了用于校准和预测巴西B10柴油发动机燃料中生物柴油含量的样品中100％正确的分类。应用这两种模型的良好结果表明，这些分析方法是可行和有效的，并且可以被检查机构用于对该燃料进行定量和定性控制。此外，这些方法快速，低成本，并允许使用便携式设备进行现场分析。

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