Higher heating value prediction of lignocellulosic crop based on their content of main components


  • Godin, B. , Ghysel, F. , Agneessens, R. , Gerin, P. , Stilmant, D. & Delcarte, J. (2010). Higher heating value prediction of lignocellulosic crop based on their content of main components. Biotechnology, Agronomy, Society and Environment. Proceedings in: EDT GEPROC : Le génie des procédés et les bio-industries, Gembloux, 16/12/2009, Biotechnology, Agronomy, Society and Environment,
Type Conference Proceedings
Year of conference 2010
Title Higher heating value prediction of lignocellulosic crop based on their content of main components
Editor Biotechnology, Agronomy, Society and Environment
Conference name EDT GEPROC : Le génie des procédés et les bio-industries
Conference location Gembloux
Publisher Biotechnology, Agronomy, Society and Environment
Recnumber 20
Volume 14(S2)
conference Date 16/12/2009
Abstract The efficiency of the energy recovery potential of lignocellulosic crops as solid biofuel depends on various characteristics. One of the main characteristics in this field is the higher heating value. It is defined as the amount of heat emitted by the combustion of a fuel, including the heat coming from the condensation of the water vapor. Its value depends on the content of main components of the lignocellulosic crops. Two models predicting the higher heating value have been built based on the content of main components of the following lignocellulosic crops: miscanthus (Miscanthus x giganteus J.M.Greef & Deuter ex Hodk. & Renvoize), switchgrass (Panicum virgatum L.), Jerusalem artichoke (aerial part) (Helianthus tuberosus L.), fiber sorghum (Sorghum bicolor (L.) Moench), fiber corn (Zea mays L.) and hemp (Cannabis sativa L.) [trials made at Libramont (Belgium) in 2007 and 2008]. The first model predicts the higher heating value of the lignocellulosic crops based on sum of the products between the higher heating value of each component and its amount. The second model predicts the higher heating value of the lignocellulosic crop based on a multiple linear regression using step by step least mean squares
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Authors Godin, B., Ghysel, F., Agneessens, R., Gerin, P., Stilmant, D., Delcarte, J.

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