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Biochar production from agricultural biomass through microwave-assisted pyrolysis: predictive modelling and experimental validation of biochar yield


A machine learning model for microwave-assisted pyrolysis technology was developed in this study. The data set of 112 unique experiments was created by analysing the published literature based on biochar. The linear, interactive and quadratic regression models were trained with the selected data set. Out of three regressions models, the quadratic model \({\text{Biochar Yield}} = - 601.78 + 17.336 \times {\text{VM}} + 25.338 \times {\text{AC}} - 0.26367 \times T - 0.293 \times {\text{VM}} \times {\text{AC}} - 0.10305 \times {\text{VM}}^{2} - 0.1893 \times {\text{AC}}^{2} + 1.59 \times 10^{ - 3} \times T^{2}\) was found to have highest R2 value of 0.894. The predicted model developed based on the data from literature was validated with laboratory experimental results. Prediction and validation results showed that data prediction can be a useful tool for the preview of selected feedstock and process parameters. Volatile matter, ash content and temperature were found to be the prominent factors in the trained model. Biochar yield was predicted with a minimum root mean square error of 7 when validated with experimental results. Thus, the predicted model can be used as empirical equation for future experiments to predict biochar yield.

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Microwave-assisted pyrolysis












Volatile matter


Ash content


Fixed carbon


Analysis of variance


Sum of squared errors


Sum of squares total


Root mean square error


Granular activated carbon


Silicon carbide


Higher heating value


  1. Abdi, H. (2008). Kendall rank correlation coefficient. The Concise Encyclopedia of Statistics.

    Article  Google Scholar 

  2. Akhtar, A., Krepl, V., & Ivanova, T. (2018). A combined overview of combustion, pyrolysis, and gasification of biomass. Energy and Fuels, 32(7), 7294–7318.

    CAS  Article  Google Scholar 

  3. Arafat Hossain, M., Ganesan, P., Jewaratnam, J., & Chinna, K. (2017). Optimization of process parameters for microwave pyrolysis of oil palm fiber (OPF) for hydrogen and biochar production. Energy Conversion and Management, 133, 349–362.

    CAS  Article  Google Scholar 

  4. Bagotia, N., Sharma, A. K., & Kumar, S. (2021). A review on modified sugarcane bagasse biosorbent for removal of dyes. Chemosphere, 268, 129309.

    CAS  Article  Google Scholar 

  5. Basu, P. (2018). Pyrolysis. In Biomass gasification, pyrolysis and torrefaction (pp. 155–187). Elsevier.

  6. Beneroso, D., Bermúdez, J. M., Arenillas, A., & Menéndez, J. A. (2015). Influence of carrier gas on microwave-induced pyrolysis. Journal of Analytical and Applied Pyrolysis, 113, 153–157.

    CAS  Article  Google Scholar 

  7. Biswas, B., Pandey, N., Bisht, Y., Singh, R., Kumar, J., & Bhaskar, T. (2017). Pyrolysis of agricultural biomass residues: Comparative study of corn cob, wheat straw, rice straw and rice husk. Bioresource Technology, 237, 57–63.

    CAS  Article  Google Scholar 

  8. Bushra, B., & Remya, N. (2020). Biochar from pyrolysis of rice husk biomass—Characteristics, modification and environmental application. Biomass Conversion and Biorefinery.

    Article  Google Scholar 

  9. Chatterjee, S., & Simonoff, J. S. (2013). Handbook of regression analysis. Handbook of Regression Analysis.

    Article  Google Scholar 

  10. Cherubini, F. (2010). The biorefinery concept: Using biomass instead of oil for producing energy and chemicals. Energy Conversion and Management, 51(7), 1412–1421.

    CAS  Article  Google Scholar 

  11. Dai, L., Fan, L., Duan, D., Ruan, R., Wang, Y., Liu, Y., et al. (2017). Microwave-assisted catalytic fast co-pyrolysis of soapstock and waste tire for bio-oil production. Journal of Analytical and Applied Pyrolysis, 125, 304–309.

    CAS  Article  Google Scholar 

  12. Domínguez, A., Menéndez, J. A., Fernández, Y., Pis, J. J., Nabais, J. M. V., Carrott, P. J. M., & Carrott, M. M. L. R. (2007). Conventional and microwave induced pyrolysis of coffee hulls for the production of a hydrogen rich fuel gas. Journal of Analytical and Applied Pyrolysis, 79(1–2), 128–135.

    CAS  Article  Google Scholar 

  13. Fang, S., Gu, W., Dai, M., Xu, J., Yu, Z., Lin, Y., et al. (2018). A study on microwave-assisted fast co-pyrolysis of chlorella and tire in the N 2 and CO 2 atmospheres. Bioresource Technology.

    Article  Google Scholar 

  14. Francis Prashanth, P., Burada Shravani, R., Vinu, L. M., & Ramesh Prabu, V. (2021). Production of diesel range hydrocarbons from crude oil sludge via microwave-assisted pyrolysis and catalytic upgradation. Process Safety and Environmental Protection, 146, 383–395.

    CAS  Article  Google Scholar 

  15. Haeldermans, T., Claesen, J., Maggen, J., Carleer, R., Yperman, J., Adriaensens, P., et al. (2019). Microwave assisted and conventional pyrolysis of MDF—Characterization of the produced biochars. Journal of Analytical and Applied Pyrolysis, 138, 218–230.

    CAS  Article  Google Scholar 

  16. IS:1350. (1984). Indian Standard–methods of test for coal and coke. Bureau of Indian Standards, (IS:1350), 28.

  17. Kaza Silpa, Yao Lisa, Bhada-Tata Perinaz, W. F. Van. (2018). What a waste 2.0: A global snapshot of solid waste management to 2050. Wold Bank Group.

  18. Lo, S. L., Huang, Y. F., Chiueh, P. T., & Kuan, W. H. (2017). Microwave pyrolysis of lignocellulosic biomass. Energy Procedia, 105, 41–46.

    CAS  Article  Google Scholar 

  19. Luo, J., Lin, J., Ma, R., Chen, X., Sun, S., Zhang, P., & Liu, X. (2020). Effect of different ash/organics and C/H/O ratios on characteristics and reaction mechanisms of sludge microwave pyrolysis to generate bio-fuels. Waste Management, 117, 188–197.

    CAS  Article  Google Scholar 

  20. Macarthur, E. (2020). Towards the circular economy—Economic and business rationale for an accelerated transition. Ellen macarthur foundation rethink the future, 100.

  21. Mamaeva, A., Tahmasebi, A., Tian, L., & Yu, J. (2016). Microwave-assisted catalytic pyrolysis of lignocellulosic biomass for production of phenolic-rich bio-oil. Bioresource Technology, 211, 382–389.

    CAS  Article  Google Scholar 

  22. Motasemi, F., & Afzal, M. T. (2013). A review on the microwave-assisted pyrolysis technique. Renewable and Sustainable Energy Reviews, 28, 317–330.

    CAS  Article  Google Scholar 

  23. Pathy, A., Meher, S., & Balasubramanian, P. (2020). Predicting algal biochar yield using eXtreme Gradient Boosting (XGB) algorithm of machine learning methods. Algal Research, 50, 102006.

    Article  Google Scholar 

  24. Rajasekhar Reddy, B., & Vinu, R. (2018). Microwave-assisted co-pyrolysis of high ash Indian coal and rice husk: Product characterization and evidence of interactions. Fuel Processing Technology, 178, 41–52.

    CAS  Article  Google Scholar 

  25. Ravikumar, C., Senthil Kumar, P., Subhashni, S. K., Tejaswini, P. V., & Varshini, V. (2017). Microwave assisted fast pyrolysis of corn cob, corn stover, saw dust and rice straw: Experimental investigation on bio-oil yield and high heating values. Sustainable Materials and Technologies, 11, 19–27.

    CAS  Article  Google Scholar 

  26. Sahoo, D., & Remya, N. (2020). Influence of operating parameters on the microwave pyrolysis of rice husk: Biochar yield, energy yield, and property of biochar. Biomass Conversion and Biorefinery.

    Article  Google Scholar 

  27. Salema, A. A., & Ani, F. N. (2012). Pyrolysis of oil palm empty fruit bunch biomass pellets using multimode microwave irradiation. Bioresource Technology, 125, 102–107.

    CAS  Article  Google Scholar 

  28. Shang, H., Lu, R. R., Shang, L., & Zhang, W. H. (2015). Effect of additives on the microwave-assisted pyrolysis of sawdust. Fuel Processing Technology, 131, 167–174.

    CAS  Article  Google Scholar 

  29. Sharma, K. D., & Jain, S. (2020). Municipal solid waste generation, composition, and management: The global scenario. Social Responsibility Journal, 16(6), 917–948.

    Article  Google Scholar 

  30. Shukla, N., Sahoo, D., & Remya, N. (2019). Biochar from microwave pyrolysis of rice husk for tertiary wastewater treatment and soil nourishment. Journal of Cleaner Production, 235, 1073–1079.

    CAS  Article  Google Scholar 

  31. Sun, Y., Liu, L., Wang, Q., Yang, X., & Tu, X. (2016). Pyrolysis products from industrial waste biomass based on a neural network model. Journal of Analytical and Applied Pyrolysis, 120, 94–102.

    CAS  Article  Google Scholar 

  32. Suriapparao, D. V., Boruah, B., Raja, D., & Vinu, R. (2018). Microwave assisted co-pyrolysis of biomasses with polypropylene and polystyrene for high quality bio-oil production. Fuel Processing Technology, 175, 64–75.

    CAS  Article  Google Scholar 

  33. Ubando, A. T., Felix, C. B., & Chen, W. (2020). Bioresource Technology Biore fi neries in circular bioeconomy: A comprehensive review. Bioresource Technology, 299, 122585.

    CAS  Article  Google Scholar 

  34. Wang, N., Tahmasebi, A., Yu, J., Xu, J., Huang, F., & Mamaeva, A. (2015). A Comparative study of microwave-induced pyrolysis of lignocellulosic and algal biomass. Bioresource Technology, 190, 89–96.

    CAS  Article  Google Scholar 

  35. Wu, C., Budarin, V. L., Gronnow, M. J., De Bruyn, M., Onwudili, J. A., Clark, J. H., & Williams, P. T. (2014). Conventional and microwave-assisted pyrolysis of biomass under different heating rates. Journal of Analytical and Applied Pyrolysis, 107, 276–283.

    CAS  Article  Google Scholar 

  36. Yu, H., Zou, W., Chen, J., Chen, H., Yu, Z., Huang, J., et al. (2019). Biochar amendment improves crop production in problem soils: A review. Journal of Environmental Management, 232, 8–21.

    CAS  Article  Google Scholar 

  37. Zhou, J., Liu, S., Zhou, N., Fan, L., Zhang, Y., Peng, P., et al. (2018). Development and application of a continuous fast microwave pyrolysis system for sewage sludge utilization. Bioresource Technology, 256, 295–301.

    CAS  Article  Google Scholar 

  38. Zhu, X., Li, Y., & Wang, X. (2019). Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions. Bioresource Technology, 288, 121527.

    CAS  Article  Google Scholar 

  39. Zuo, W., Tian, Y., & Ren, N. (2011). The important role of microwave receptors in bio-fuel production by microwave-induced pyrolysis of sewage sludge. Waste Management, 31(6), 1321–1326.

    CAS  Article  Google Scholar 

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Correspondence to Neelancherry Remya.

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Narde, S.R., Remya, N. Biochar production from agricultural biomass through microwave-assisted pyrolysis: predictive modelling and experimental validation of biochar yield. Environ Dev Sustain (2021).

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  • Microwave-assisted pyrolysis
  • Biochar yield
  • Regression model
  • Prediction
  • Validation