Near-infrared spectrum analysis to determine relationships between biochemical composition and anaerobic digestion performances
Résumé
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.
Mots clés
PARTIAL LEAST SQUARE (PLS)
NEAR-INFRARED WAVELENGTH
NEAR INFRARED SPECTRUM ANALYSIS
DIGESTION PERFORMANCE
ANAEROBIC DIGESTION PROCESS
PRINCIPAL COMPONENT ANALYSIS
ORGANIC COMPOUNDS
NEAR INFRARED SPECTROSCOPY
LEAST SQUARES APPROXIMATIONS
INFRARED DEVICES
CHEMICAL OXYGEN DEMAND
CHEMICAL ANALYSIS
SIGNAL ANALYSIS
PARTIAL LEAST SQUARES REGRESSION
NEAR-INFRARED WAVELENGTHS
BIOGEOCHEMISTRY
BIOLOGICAL MATERIALS
BIODEGRADABILITY