Espectrometria no infravermelho médio e métodos quimiométricos PLS-DA E PLS: classificação e previsão do teor de biodiesel na mistura de biodiesel/diesel de mafurra, moringa e algodão - Máquina, Ademar Domingos Viagem (2017)
Biodiesel is a renewable fuel derived from vegetable oils or animal fats that have been highlighted in the agendas of Governments of Mozambique, Brazil and several countries such as energy option and dependence counterpoint on fossil fuels. This fuel was introduced in the mozambican and brazilian energy matrix in 2009 and 2005, respectively, where it is marketed in combination with diesel in the proportion established in the laws of both countries. Given the above, it is necessary to develop methodologies that provide rapid and efficient responses to control the quality of this fuel. However, this study presents methodologies to quantify and classify the content of methyl biodiesels of Mafurra, Moringa and cotton mixed with diesel, using Mid-Infrared Spectroscopy associated with chemometric methods of multivariate calibration by Partial Least Squares (PLS) and Partial Least Squares – Discriminant Analysis (PLS-DA). The PLS models developed for the determination of the content has been validated based on the following figures of merit: selectivity, sensitivity, analytical sensitivity, detection limit, quantification limit, test to systematic error (bias e tbias). Was also made the assessment of the adjustment of the models through the correlation of actual and forecast values of the sets of calibration and prediction, where were noted a high correlation between the two, with a correlation coefficient higher than 0, 99 and satisfactory results for the evaluated figures of merit. For the qualitative monitoring, PLS-DA models were developed. The efficiency of these models was analyzed based on the criteria of true answers statistics, this is, sensitivity and specificity parameters. These parameters showed values of 1, which signify 100% correct classification of the calibration samples and forecast in all models. The good results of the models show that in fact, these analytical methods are feasible and effective for the quantitative and qualitative control of these fuels.