<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The second-generation liquid biofuels are fuels derived from non-food raw materials, i.e. waste cooking oils and animal fats. They are waste raw materials from the agri-food industry, hence their quantity is limited, and their quality depends, <italic>inter alia</italic>, on the place of their acquisition. Considering the fact that rheological properties of liquid biofuels are closely correlated with the quality of raw materials from which they are obtained, the industrial production of biofuels from waste fats requires development of new analytical methods, allowing for a quick assessment of the quality of the obtained products. The aim of the study was to confirm the possibility of using near infrared spectrometry to assess the content of methyl palmitate in biofuels produced from waste cooking oil. The calibration models were based on 41 absorbance spectra recorded in the range of 400-2170 nm for samples containing from 0 to 5 % of methyl palmitate. The obtained results confirmed that there is a possibility of effective detection of the concentration of this ester in biofuel using the spectrum in the range of 1644-1778 nm. The developed PLS calibration models are characterized by a determination co-efficient (R<sup>2</sup>) exceeding the value of 0.99.</p></abstract>

The second-generation liquid biofuels are fuels derived from non-food raw materials, i.e. waste cooking oils and animal fats. They are waste raw materials from the agri-food industry, hence their quantity is limited, and their quality depends, inter alia, on the place of their acquisition. Considering the fact that rheological properties of liquid biofuels are closely correlated with the quality of raw materials from which they are obtained, the industrial production of biofuels from waste fats requires development of new analytical methods, allowing for a quick assessment of the quality of the obtained products. The aim of the study was to confirm the possibility of using near infrared spectrometry to assess the content of methyl palmitate in biofuels produced from waste cooking oil. The calibration models were based on 41 absorbance spectra recorded in the range of 400-2170 nm for samples containing from 0 to 5 % of methyl palmitate. The obtained results confirmed that there is a possibility of effective detection of the concentration of this ester in biofuel using the spectrum in the range of 1644-1778 nm. The developed PLS calibration models are characterized by a determination co-efficient (R2) exceeding the value of 0.99.

Spectrometric Determination of Content of Methyl Palmitate in Methyl Esters of Waste Cooking Oils

Institute of Technology and Life Sciences

Agricultural Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The second-generation liquid biofuels are fuels derived from non-food raw materials, i.e. waste cooking oils and animal fats. They are waste raw materials from...

Spectrometric Determination of Content of Methyl Palmitate in Methyl Esters of Waste Cooking Oils

Data publikacji: 13 maj 2019

Zakres stron: 59 - 68

Otrzymano: 01 gru 2018

Przyjęty: 01 mar 2019

DOI: https://doi.org/10.1515/agriceng-2019-0006

Słowa kluczowe
Biodiesel, Biofuels, Waste Cooking Oils, Spectroscopy, Calibration Models

© 2019 Damian Marcinkowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Spectrometric Determination of Content of Methyl Palmitate in Methyl Esters of Waste Cooking Oils

Data publikacji: 13 maj 2019

Zakres stron: 59 - 68

Otrzymano: 01 gru 2018

Przyjęty: 01 mar 2019

DOI: https://doi.org/10.1515/agriceng-2019-0006

Słowa kluczoweBiodiesel, Biofuels, Waste Cooking Oils, Spectroscopy, Calibration Models

© 2019 Damian Marcinkowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Biodiesel, Biofuels, Waste Cooking Oils, Spectroscopy, Calibration Models