Vol. 24, No. 3 (2025), IA25570 https://doi.org/10.24275/rmiq/IA25570

Influence of chemical indicators on biogas production in a bioreactor from water hyacinth using canonical correlation analysis

 

Authors

D.B. Benitez-Suarez, H. Bautista-Zaragoza, J. P. Molina-Aguilar, J. Apolinar-Cortés, M. C. Chávez-Parga

Abstract

The global energy crisis is currently a matter of great concern. With the rapid growth of the population, especially in emerging economies, energy supply often struggles to keep pace with demand. Biogas production from water hyacinth (Eichhornia crassipes) in an upflow anaerobic sludge blanket reactor offers a promising renewable energy alternative with multiple benefits. The anaerobic digestion of organic matter generates biogas, which holds significant potential for electricity and heat generation and can also be upgraded into a usable fuel. This study applied canonical correlation analysis to evaluate the relationship between sets of independent and dependent variables involved in the biogas production process. A 20 L anaerobic reactor upflow fed with water hyacinth pretreated with calcium oxide. Physicochemical variables were measured for the substrate, inoculum, effluent, and the biogas produced. The analysis yielded a canonical correlation coefficient of 0.8467 between the two variable sets, indicating a relatively strong relationship. Moreover, biogas production was estimated based on the input variables using the canonical variables derived from the analysis. These results demonstrate that canonical correlation analysis is a valuable tool for monitoring and optimizing the biogas production process, as it helps identify critical variables and their effects on reactor performance.

Keywords

anaerobic digestion, biogas, canonical correlation, canonical variables.

References
  • Ali, H.A., Faraj, J.J., Hussien, F.M. (2021). Effect of pH on biogas production during anaerobic digestion. Journal of University of Shanghai for Science and Technology, 23(8), 224–231. https://doi.org/10.51201/jusst/21/08369
  • Alvarado-Reyna, P., Albalate-Ramírez, A., García-Balandrán, E., Escamilla-Alvarado, C., Galván-Arzola, U., Miramontes-Martínez, L., & Rivas-García, P. (2024). Evaluation of the reaction capacity of early warning indicators to failures in biogas production systems. Revista Mexicana de Ingeniería Química, 23(3), 1-30. https://doi.org/10.24275/rmiq/bio24313
  • Alves, D., Villar, I., Mato, S. (2023). Community composting strategies for biowaste treatment: methodology, bulking agent and compost quality. Environmental science and pollution research, 31(7), 9873–9885. https://doi.org/10.1007/s11356-023-25564-x
  • Amiri, H., & Karimi, K. (2018). Pretreatment and hydrolysis of lignocellulosic wastes for butanol production: Challenges and perspectives. Bioresource Technology, 270, 702-721. https://doi.org/10.1016/j.biortech.2018.08.117
  • Armah, E. K., Boamah, B. B., & Boakye, G. O. (2018). Impact of Water Hyacinth ( Eicchornia crassipes ) as a Feedstock for Biogas Production. Chemical And Biomolecular Engineering, 2(4), 184. https://doi.org/10.11648/j.cbe.20170204.13
  • Badii, M. H., & Castillo, J. (2017). Análisis de correlación canónica (ACC) e investigación científica. Revista Innovaciones de Negocios, 4(8). https://doi.org/10.29105/rinn4.8-9
  • Callegari, A., Tucci, M., Aulenta, F., Viggi, C. C., & Capodaglio, A. G. (2025). Anaerobic sludge digestion enhancement with bioelectrochemical and electrically conductive materials augmentation: A state of the art review. Chemosphere, 372, 144101. https://doi.org/10.1016/j.chemosphere.2025.144101
  • Cao, Z., Jung, D., Olszewski, M. P., Arauzo, P. J., & Kruse, A. (2019). Hydrothermal carbonization of biogas digestate: Effect of digestate origin and process conditions. Waste Management, 100, 138-150. https://doi.org/10.1016/j.wasman.2019.09.009
  • Chang, C., Chang, C., Lu, H., Hsieh, C., & Wu, J. (2025). Bioenergetically constrained dynamical microbial interactions govern the performance and stability of methane-producing bioreactors. Npj Biofilms And Microbiomes, 11(1). https://doi.org/10.1038/s41522-025-00668-z
  • Chen, B., Azman, S., Crauwels, S., Dewil, R., & Appels, L. (2024). Mild alkaline conditions affect digester performance and community dynamics during long-term exposure. Bioresource Technology, 406, 131009. https://doi.org/10.1016/j.biortech.2024.131009
  • Chew, K. R., Leong, H. Y., Khoo, K. S., Vo, D. N., Anjum, H., Chang, C., & Show, P. L. (2021). Effects of anaerobic digestion of food waste on biogas production and environmental impacts: a review. Environmental Chemistry Letters, 19(4), 2921-2939. https://doi.org/10.1007/s10311-021-01220-z
  • Chiemchaisri, C., & Visvanathan, C. (2008). Greenhouse Gas Emission Potential of the Municipal Solid Waste Disposal Sites in Thailand. Journal Of The Air & Waste Management Association, 58(5), 629-635. https://doi.org/10.3155/1047-3289.58.5.629
  • El-Araby, R. (2024). Biofuel production: exploring renewable energy solutions for a greener future. Biotechnology For Biofuels And Bioproducts, 17(1). https://doi.org/10.1186/s13068-024-02571-9
  • González, M. M. R., De León, E. M. D., Luque, L., Pitty, N., Arias, J., & Chen, A. (2024). Codigestión Anaeróbica de Lodos y Residuos Orgánicos Municipales en Clima Tropical. I+D Tecnológico, 20(1), 82-93. https://doi.org/10.33412/idt.v20.1.3902
  • Goux, X., Calusinska, M., Lemaigre, S., Marynowska, M., Klocke, M., Udelhoven, T., Benizri, E., & Delfosse, P. (2015). Microbial community dynamics in replicate anaerobic digesters exposed sequentially to increasing organic loading rate, acidosis, and process recovery. Biotechnology For Biofuels, 8(1). https://doi.org/10.1186/s13068-015-0309-9
  • Gupta, P., Kurien, C., & Mittal, M. (2022). Biogas (a promising bioenergy source): A critical review on the potential of biogas as a sustainable energy source for gaseous fuelled spark ignition engines. International Journal Of Hydrogen Energy, 48(21), 7747-7769. https://doi.org/10.1016/j.ijhydene.2022.11.195
  • Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C. (2009). Multivariate data analysis (7th ed.). Prentice Hall, Upper Saddle River, NJ.
    Hasani, Z.A., Nayak, J.K., Balushi, N.J.A., Al-Mamun, A., Samal, K. (2025). Prospect of conductive materials in the anaerobic digester matrix for methane production: electron transfer and microbial communication. Water, 17(9), 1321. https://doi.org/10.3390/w17091321
  • Helmer, M., Warrington, S., Mohammadi-Nejad, A., Ji, J.L., Howell, A., Rosand, B., Anticevic, A., Sotiropoulos, S.N., Murray, J.D. (2024). On the stability of canonical correlation analysis and partial least squares with application to brain-behavior associations. Communications biology, 7(1). https://doi.org/10.1038/s42003-024-05869-4
  • Hernández-Eugenio, G., Espinosa-Solares, T., López-Ortiz, C., Meneses-Reyes, J.C., Ochoa-Bernal, T.G. (2025). Changes in microbial diversity and methane yield caused by overloading in systems of chicken litter, microalgae oil-free and glycerol in co-digestion. Revista mexicana de ingeniería química, 24(2), IA25488. https://doi.org/10.24275/rmiq/IA25488
  • Hotelling, H. (1936). Relations between two sets of variants. Biometrika, 28(3/4), 321–377.
  • Jameel, M. K., Mustafa, M. A., Ahmed, H. S., Mohammed, A. J., Ghazy, H., Shakir, M. N., Lawas, A. M., Mohammed, S. K., Idan, A. H., Mahmoud, Z. H., Sayadi, H., & Kianfar, E. (2024). Biogas: Production, properties, applications, economic and challenges: A review. Results In Chemistry, 7, 101549. https://doi.org/10.1016/j.rechem.2024.101549
  • Karouach, F., Bakrim, W.B., Ezzariai, A., Mnaouer, I., Ibourki, M., Kibret, M., Sobeh, M., Hafidi, M., Kouisni, L. (2023). Valorization of water hyacinth to biomethane and biofertilizer through anaerobic digestion technology. Fuel, 358, 130008. https://doi.org/10.1016/j.fuel.2023.130008
  • Khalil, B., Ouarda, T., & St-Hilaire, A. (2011). Estimation of water quality characteristics at ungauged sites using artificial neural networks and canonical correlation analysis. Journal Of Hydrology, 405(3-4), 277-287. https://doi.org/10.1016/j.jhydrol.2011.05.024  
  • Khan, I. U., Othman, M. H. D., Hashim, H., Matsuura, T., Ismail, A., Rezaei-DashtArzhandi, M., & Azelee, I. W. (2017). Biogas as a renewable energy fuel – A review of biogas upgrading, utilisation and storage. Energy Conversion And Management, 150, 277-294. https://doi.org/10.1016/j.enconman.2017.08.035
  • Kumar, V., Singh, J., Nadeem, M., Kumar, P., & Pathak, V. V. (2018). Experimental and Kinetics Studies for Biogas Production Using Water Hyacinth (Eichhornia crassipes [Mart.] Solms) and Sugar Mill Effluent. Waste And Biomass Valorization, 11(1), 109-119. https://doi.org/10.1007/s12649-018-0412-9
  • Martínez, E. J., Gil, M. V., Fernandez, C., Rosas, J. G., & Gómez, X. (2016). Anaerobic Codigestion of Sludge: Addition of Butcher’s Fat Waste as a Cosubstrate for Increasing Biogas Production. PLoS ONE, 11(4), e0153139. https://doi.org/10.1371/journal.pone.0153139
  • Mohammed, M., Belkair, A., Hamad, T., Jirhiman, I., Hassan, R., & Ahmeedah, A. (2022). Improving biogas production from animal manure by batch anaerobic digestion. Algerian Journal of Engineering and Technology, 6, 79–84. https://doi.org/10.5281/zenodo.6561086 
  • Molina-Aguilar, J. P., Gutiérrez-López, A., & Cruz-Paz, I. M. (2019). Correlación canónica entre volúmenes de almacenamiento en presas e intensidades de precipitación durante huracanes. Tecnología y Ciencias del Agua, 10(6), 25-56. https://doi.org/10.24850/j-tyca-2019-06-02
  • Nakasima-López, M., Taboada-González, P., Aguilar-Virgen, Q., & Velázquez-Limón, N. (2017). Adaptación de Inóculos Durante el Arranque de la Digestión Anaerobia con Residuos Sólidos Orgánicos. InformacióN TecnolóGica, 28(1), 199-208. https://doi.org/10.4067/s0718-07642017000100020
  • Negi, S., Chai, J., Tjhin, A. C. T., & Pan, S. (2025). Electro-anaerobic digestion as carbon–neutral solutions. Chemical And Biological Technologies In Agriculture, 12(1). https://doi.org/10.1186/s40538-025-00776-0
  • Otto, P., Puchol-Royo, R., Ortega-Legarreta, A., Tanner, K., Tideman, J., De Vries, S., Pascual, J., Porcar, M., Latorre-Pérez, A., & Abendroth, C. (2024). Multivariate comparison of taxonomic, chemical and operational data from 80 different full-scale anaerobic digester-related systems. Biotechnology For Biofuels And Bioproducts, 17(1). https://doi.org/10.1186/s13068-024-02525-1
  • Pottipati, S., Yadav, K. D., & Kalamdhad, A. S. (2021). The Potential of Biogas Production from Water Hyacinth by Using a Floating Drum Biogas Reactor. Springer eBooks, pp. 215-223. https://doi.org/10.1007/978-3-030-70463-6_20
  • Rolewicz-Kalińska, A., Lelicińska-Serafin, K., Manczarski, P. (2020). The circular economy and organic fraction of municipal solid waste recycling strategies. Energies, 13(17), 4366. https://doi.org/10.3390/en13174366
  • Soto, M., Ruiz, I. (2021). Co-digestión anaerobia para la obtención de biogás a partir de residuos forestales. Tesis de doctorado, Universidad de A Coruña. https://ruc.udc.es/dspace/handle/2183/29172
  • Statista. (2024). Global natural gas consumption 1998–2023. Statista. Disponible en: https://www.statista.com/statistics/282717/global-natural-gas-consumption/
  • Stylianou, M., Laifi, T., Bennici, S., Dutournie, P., Limousy, L., Agapiou, A., Papamichael, I., Khiari, B., Jeguirim, M., & Zorpas, A. A. (2023). Tomato waste biochar in the framework of circular economy. The Science Of The Total Environment, 871, 161959. https://doi.org/10.1016/j.scitotenv.2023.161959
  • Themelis N.J. y Ulloa P.A. (2007). Methane generation in landfills. Renew. Energy, 32 (7), 1243-1257. https://doi.org/10.1016/j.renene.2006.04.020
  • Triviño-Pineda, J., Sanchez-Rodriguez, A., & Peláez, N. P. (2024). Biogas production from organic solid waste through anaerobic digestion: A meta-analysis. Case Studies In Chemical And Environmental Engineering, 9, 100618. https://doi.org/10.1016/j.cscee.2024.100618
  • Walker, M., Zhang, Y., Heaven, S., & Banks, C. (2009). Potential errors in the quantitative evaluation of biogas production in anaerobic digestion processes. Bioresource Technology, 100(24), 6339-6346. https://doi.org/10.1016/j.biortech.2009.07.018
  • Zhuang, X., Yang, Z., & Cordes, D. (2020). A technical review of canonical correlation analysis for neuroscience applications. Human Brain Mapping, 41(13), 3807-3833. https://doi.org/10.1002/hbm.25090