IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i11p4312-d1155038.html
   My bibliography  Save this article

Use of Artificial Neural Networks to Model Biomass Properties of Miscanthus ( Miscanthus × giganteus ) and Virginia Mallow ( Sida hermaphrodita L.) in View of Harvest Season

Author

Listed:
  • Jona Šurić

    (Department of Agricultural Technology, Storage and Transport, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

  • Neven Voća

    (Department of Agricultural Technology, Storage and Transport, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

  • Anamarija Peter

    (Department of Agricultural Technology, Storage and Transport, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

  • Nikola Bilandžija

    (Department of Agricultural Engineering, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

  • Ivan Brandić

    (Department of Agricultural Technology, Storage and Transport, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

  • Lato Pezo

    (Institute of General and Physical Chemistry, University of Belgrade, Studentski trg 12/V, 11000 Belgrade, Serbia)

  • Josip Leto

    (Department of Field Crops, Forage and Grassland, Faculty of Agriculture, University of Zagreb, Svetošimunska Cesta 25, 10000 Zagreb, Croatia)

Abstract

Miscanthus and Virginia Mallow are energy crops characterized by high yields, perenniality, and low agrotechnical requirements and have great potential for solid and liquid biofuel production. Later harvest dates result in lower yields but better-quality mass for combustion, while on the other hand, when biomass is used for biogas production, harvesting in the autumn gives better results due to lower lignin content and higher moisture content. The aim of this work was to determine not only the influence of the harvest date on the energetic properties but also how accurately artificial neural networks can predict the given parameters. The yield of dry matter in the first year of experimentation for this research was on average twice as high in spring compared to autumn for Miscanthus (40 t/ha to 20 t/ha) and for Virginia Mallow (11 t/ha to 8 t/ha). Miscanthus contained 52.62% carbon in the spring, which is also the highest percentage determined in this study, while Virginia Mallow contained 51.51% carbon. For both crops studied, delaying the harvest date had a positive effect on ash content, such that the ash content of Miscanthus in the spring was about 1.5%, while in the autumn it was 2.2%. Harvest date had a significant effect on the increase of lignin in both plants, while Miscanthus also showed an increase in cellulose from 47.42% in autumn to 53.5% in spring. Artificial neural networks used to predict higher and lower heating values showed good results with lower errors when values obtained from biomass elemental composition were used as input parameters than those obtained from proximity analysis.

Suggested Citation

  • Jona Šurić & Neven Voća & Anamarija Peter & Nikola Bilandžija & Ivan Brandić & Lato Pezo & Josip Leto, 2023. "Use of Artificial Neural Networks to Model Biomass Properties of Miscanthus ( Miscanthus × giganteus ) and Virginia Mallow ( Sida hermaphrodita L.) in View of Harvest Season," Energies, MDPI, vol. 16(11), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4312-:d:1155038
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/11/4312/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/11/4312/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kartal, Furkan & Özveren, Uğur, 2020. "A deep learning approach for prediction of syngas lower heating value from CFB gasifier in Aspen plus®," Energy, Elsevier, vol. 209(C).
    2. Nikola Bilandžija & Tajana Krička & Ana Matin & Josip Leto & Mateja Grubor, 2018. "Effect of Harvest Season on the Fuel Properties of Sida hermaphrodita (L.) Rusby Biomass as Solid Biofuel," Energies, MDPI, vol. 11(12), pages 1-13, December.
    3. Šiaudinis, Gintaras & Jasinskas, Algirdas & Šarauskis, Egidijus & Steponavičius, Dainius & Karčauskienė, Danutė & Liaudanskienė, Inga, 2015. "The assessment of Virginia mallow (Sida hermaphrodita Rusby) and cup plant (Silphium perfoliatum L.) productivity, physico–mechanical properties and energy expenses," Energy, Elsevier, vol. 93(P1), pages 606-612.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jankowski, Krzysztof Józef & Dubis, Bogdan & Sokólski, Mateusz Mikołaj & Załuski, Dariusz & Bórawski, Piotr & Szempliński, Władysław, 2019. "Biomass yield and energy balance of Virginia fanpetals in different production technologies in north-eastern Poland," Energy, Elsevier, vol. 185(C), pages 612-623.
    2. Jasinskas, Algirdas & Streikus, Dionizas & Vonžodas, Tomas, 2020. "Fibrous hemp (Felina 32, USO 31, Finola) and fibrous nettle processing and usage of pressed biofuel for energy purposes," Renewable Energy, Elsevier, vol. 149(C), pages 11-21.
    3. Marcin Jewiarz & Marek Wróbel & Krzysztof Mudryk & Szymon Szufa, 2020. "Impact of the Drying Temperature and Grinding Technique on Biomass Grindability," Energies, MDPI, vol. 13(13), pages 1-22, July.
    4. Śliz, Maciej & Wilk, Małgorzata, 2020. "A comprehensive investigation of hydrothermal carbonization: Energy potential of hydrochar derived from Virginia mallow," Renewable Energy, Elsevier, vol. 156(C), pages 942-950.
    5. Owen Sedej & Eric Mbonimpa & Trevor Sleight & Jeremy Slagley, 2022. "Application of Machine Learning to Predict the Performance of an EMIPG Reactor Using Data from Numerical Simulations," Energies, MDPI, vol. 15(7), pages 1-22, March.
    6. Šuhaj, Patrik & Husár, Jakub & Haydary, Juma & Annus, Július, 2022. "Experimental verification of a pilot pyrolysis/split product gasification (PSPG) unit," Energy, Elsevier, vol. 244(PA).
    7. Stolarski, Mariusz J. & Krzyżaniak, Michał & Warmiński, Kazimierz & Tworkowski, Józef & Szczukowski, Stefan & Olba–Zięty, Ewelina & Gołaszewski, Janusz, 2017. "Energy efficiency of perennial herbaceous crops production depending on the type of digestate and mineral fertilizers," Energy, Elsevier, vol. 134(C), pages 50-60.
    8. Xie, Xinyu & Wang, Xiaofang & Zhao, Pu & Hao, Yichen & Xie, Rong & Liu, Haitao, 2023. "Learning time-aware multi-phase flow fields in coal-supercritical water fluidized bed reactor with deep learning," Energy, Elsevier, vol. 263(PD).
    9. Sabarathinam Srinivasan & Suresh Kumarasamy & Zacharias E. Andreadakis & Pedro G. Lind, 2023. "Artificial Intelligence and Mathematical Models of Power Grids Driven by Renewable Energy Sources: A Survey," Energies, MDPI, vol. 16(14), pages 1-56, July.
    10. Kwiatkowski, Jacek & Graban, Łukasz & Stolarski, Mariusz J., 2023. "The energy efficiency of Virginia fanpetals biomass production for solid biofuel," Energy, Elsevier, vol. 264(C).
    11. Andrzej Bryś & Agnieszka Kaleta & Krzysztof Górnicki & Szymon Głowacki & Weronika Tulej & Joanna Bryś & Piotr Wichowski, 2021. "Some Aspects of the Modelling of Thin-Layer Drying of Sawdust," Energies, MDPI, vol. 14(3), pages 1-16, January.
    12. Ivan Brandić & Lato Pezo & Nikola Bilandžija & Anamarija Peter & Jona Šurić & Neven Voća, 2023. "Comparison of Different Machine Learning Models for Modelling the Higher Heating Value of Biomass," Mathematics, MDPI, vol. 11(9), pages 1-14, April.
    13. Nikola Bilandžija & Tajana Krička & Ana Matin & Josip Leto & Mateja Grubor, 2018. "Effect of Harvest Season on the Fuel Properties of Sida hermaphrodita (L.) Rusby Biomass as Solid Biofuel," Energies, MDPI, vol. 11(12), pages 1-13, December.
    14. Izabela Gołąb-Bogacz & Waldemar Helios & Andrzej Kotecki & Marcin Kozak & Anna Jama-Rodzeńska, 2021. "Content and Uptake of Ash and Selected Nutrients (K, Ca, S) with Biomass of Miscanthus × giganteus Depending on Nitrogen Fertilization," Agriculture, MDPI, vol. 11(1), pages 1-16, January.
    15. Algirdas Jasinskas & Ramūnas Mieldažys & Eglė Jotautienė & Rolandas Domeika & Edvardas Vaiciukevičius & Marek Marks, 2020. "Technical, Environmental, and Qualitative Assessment of the Oak Waste Processing and Its Usage for Energy Conversion," Sustainability, MDPI, vol. 12(19), pages 1-14, October.
    16. Kurucz, Erika & Fári, Miklós G. & Antal, Gabriella & Gabnai, Zoltán & Popp, József & Bai, Attila, 2018. "Opportunities for the production and economics of Virginia fanpetals (Sida hermaphrodita)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 824-834.
    17. Algirdas Jasinskas & Vytautas Kleiza & Dionizas Streikus & Rolandas Domeika & Edvardas Vaiciukevičius & Gvidas Gramauskas & Marvin T. Valentin, 2022. "Assessment of Quality Indicators of Pressed Biofuel Produced from Coarse Herbaceous Plants and Determination of the Influence of Moisture on the Properties of Pellets," Sustainability, MDPI, vol. 14(3), pages 1-16, January.
    18. Ajorloo, Mojtaba & Ghodrat, Maryam & Scott, Jason & Strezov, Vladimir, 2022. "Modelling and statistical analysis of plastic biomass mixture co-gasification," Energy, Elsevier, vol. 256(C).
    19. Algirdas Jasinskas & Dionizas Streikus & Egidijus Šarauskis & Mečys Palšauskas & Kęstutis Venslauskas, 2020. "Energy Evaluation and Greenhouse Gas Emissions of Reed Plant Pelletizing and Utilization as Solid Biofuel," Energies, MDPI, vol. 13(6), pages 1-14, March.
    20. Dumitru Peni & Mariusz Jerzy Stolarski & Anna Bordiean & Michał Krzyżaniak & Marcin Dębowski, 2020. "Silphium perfoliatum —A Herbaceous Crop with Increased Interest in Recent Years for Multi-Purpose Use," Agriculture, MDPI, vol. 10(12), pages 1-22, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:11:p:4312-:d:1155038. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.