Assessment of a Low-Cost Hydrogen Sensor for Detection and Monitoring of Biohydrogen Production during Sugarcane Straw/Vinasse Co-Digestion

• Published in: AgriEngineering 2024-03, Vol.6 (1), p.479-490
• Main Authors: Barrera, Andrés, Gómez-Ríos, David, Ramírez-Malule, Howard
• Format: Article
• Language: English
• Subjects: Adaptation; Alternative energy sources; Biogas; Biohydrogen; Carbon; Chemical sensors; Chromatography; Clean energy; co-digestion; dark fermentation; Digestion; Energy resources; Ethanol; Fermentation; Green energy; Hemicellulose; Hydrogen; Hydrogen production; Hydrolysates; Inoculum; Lignocellulose; Measuring instruments; Metabolism; Monitoring; MQ-8 sensor; Oxidation; Root-mean-square errors; Rural areas; Sensors; Sludge; Straw; Substrates; Sugarcane; Variance analysis; Vinasse
• ISSN: 2624-7402; 2624-7402
• DOI: 10.3390/agriengineering6010029

In this work, hydrogen production from the co-digestion of sugarcane straw and sugarcane vinasse in the dark fermentation (DF) process was monitored using a cost-effective hydrogen detection system. This system included a sensor of the MQ-8 series, an Arduino Leonardo board, and a computer. For the DF, different concentrations of sugarcane vinasse and volumetric ratios of vinasse/hemicellulose hydrolysate were used together with a thermally pretreated inoculum, while the hydrogen detection system stored the hydrogen concentration data during the fermentation time. The results showed that a higher concentration of vinasse led to higher inhibitors for the DF, resulting in a longer lag phase. Additionally, the hydrogen detection system proved to be a useful tool in monitoring the DF, showcasing a rapid response time, and providing reliable information about the period of adaptation of the inoculum to the substrate. The measurement system was assessed using the error metrics SE, RMSE, and MBE, whose values ranged 0.6 and 5.0% as minimum and maximum values. The CV (1.0–8.0%) and SD (0.79–5.62 ppm) confirmed the sensor’s robustness, while the ANOVA at the 5% significance level affirmed the repeatability of measurements with this instrument. The RMSE values supported the accuracy of the sensor for online measurements (6.08–14.78 ppm). The adoption of this straightforward and affordable method sped up the analysis of hydrogen in secluded regions without incurring the expenses associated with traditional measuring instruments while offering a promising solution for biomass valorization, contributing to the advancement of rural green energy initiatives in remote areas.