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Near‐Infrared Spectrum Analysis to Determine Relationships between Biochemical Composition and Anaerobic Digestion Performances
Author(s) -
Charnier Cyrille,
Latrille Eric,
Roger Jean-Michel,
Miroux Jérémie,
Steyer Jean-Philippe
Publication year - 2018
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201700581
Subject(s) - anaerobic digestion , organic matter , partial least squares regression , methane , chemistry , biogas , anaerobic exercise , composition (language) , biodegradation , infrared , yield (engineering) , chemical oxygen demand , environmental chemistry , biological system , environmental science , ecology , materials science , organic chemistry , mathematics , environmental engineering , biology , statistics , physiology , linguistics , philosophy , physics , wastewater , optics , metallurgy
Near‐infrared spectrum analysis coupled with partial least squares regression can predict anaerobic digestion performances. Nonetheless, due to the complexity and diversity of organic matter, a detailed assessment of the effects of the composition of organic matter on biogas production remains a great challenge. Based on 275 samples representing a wide diversity of substrates, the application of the partial least square b coefficients to assess the effects of the involved molecules on the performances of anaerobic digestion processes is discussed. In particular, to accurately predict variables, there is a need to account for the whole near‐infrared spectrum. The characterization of organic matter involving proteins, carbohydrate and lipid contents, chemical demand in oxygen, biodegradability, methane yield, and methane production kinetics data is demonstrated.