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

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. [Display omitted] •Grape pomace is a relevant agro-residue for extracting phenolic compounds.•Rotten and green tomato are attractive substrates for methane production.•Extraction process did not affect biochemical methane production of the substrates.•Multivariate regression models present better predictions for rotten and green tomato.•NIR-based model predicted the methane yield of raw and extracted substrates.