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Fast Determination of Biodiesel Content in Commercial Diesel/Biodiesel Blends by Using Digital Images and
Mayara Ferreira Barbosa1, Danielle Silva DO Nascimento2, Marcos Grünhut2
1Universidade Federal da Paraíba, Departamento de Química, Laboratório de Automação e Instrumentação em Química Analítica/Quimiometria (LAQA).
Summary
A new method uses digital images from a scanner to quickly and affordably determine biodiesel content in diesel blends. This technique accurately quantifies biodiesel percentages, offering a practical solution for fuel analysis.
Area of Science:
- Analytical Chemistry
- Green Chemistry
- Materials Science
Background:
- Biodiesel is a renewable fuel source derived from vegetable oils or animal fats.
- Accurate quantification of biodiesel in blends is crucial for quality control and regulatory compliance.
- Existing analytical methods can be complex, time-consuming, or expensive.
Purpose of the Study:
- To develop a simple, rapid, and inexpensive analytical method for determining biodiesel percentage in biodiesel/diesel blends.
- To utilize digital imaging and chemometrics for fuel analysis.
- To establish a cost-effective and accessible method for biodiesel quantification.
Main Methods:
- Samples of soybean biodiesel and petroleum diesel were blended in varying percentages (1.5-12.0%).
- Digital images of the blends were captured using a commercial scanner.
- Image data was processed using different color systems (RGB, HSV, HLS, CMYK, Grayscale).
- Chemometric models, specifically Partial Least Squares (PLS), were employed for quantification.
Main Results:
- The developed method achieved a Root Mean Square Error of Prediction (RMSEP) of 0.9% (w/w) for biodiesel.
- A high correlation (0.96) was observed between predicted and reference biodiesel values.
- The method demonstrated accuracy with a prediction range significantly smaller than the calibration range.
Conclusions:
- Digital image analysis combined with chemometrics provides a viable and accurate method for biodiesel quantification in blends.
- This approach offers a simple, rapid, and inexpensive alternative to traditional analytical techniques.
- The method holds potential for widespread application in the fuel industry for quality assessment.
