Assessment of NIR spectroscopy for predicting biochemical methane potential of agro-residues – A biorefinery approach

Abstract

Biorefinery approaches are suitable for agro-residues valorization. In this work, the integration of solid-liquid extraction followed by anaerobic digestion is explored. This study aims to assess the near-infrared (NIR) spectroscopy and multivariate regression models as reliable methods to predict the methane yield of raw and extracted agro-residues. Tomato residues (ripe semi-rotten tomato-RT, green (unripe) fruit-GT, tomato plant-TB) and grape pomace residues (GP) were extracted for phenolic compounds recovery. GP is the richest substrate in phenolic compounds (55.8 mg g−1, expressed gallic acid equivalents on a dry extract basis). The experimental values of biochemical methane potential (BMP) varied in the range128–307 NmL CH4 g−1, in volatile solid basis for tomato residues, while 115–177 NmL CH4 g−1 were determined for GP. The experimental BMP observed before and after extraction was statistically similar. The prediction based on the NIR-based model also exposes the same trend and shows a reasonable prediction error compared to other models. In conclusion, NIR spectroscopy and some multivariate regression models may be used for BMP prediction in a biorefinery context.