Pyrolysis-GC-MS to assess the fungal pretreatment efficiency for wheat straw anaerobic digestion

- High protein and carbohydrate amounts in mycelium of P. brumalis BRFM 985.
- Suitability of Py-GC-MS to study S/G ratio.
- Fungal biomass amount on WRF pretreated straws estimated by Py-GC-MS.
- Pretreatment efficiency linked to polysaccharides/lignin ratio determined by Py-GC-MS.
- Py-GC-MS polysaccharides/lignin ratio may allow efficient strain selection.

Cost-effective and environment-friendly pretreatments, such as fungal pretreatments, are required for anaerobic digestion of lignocellulosic biomass particularly because the amount of methane produced is often limited by the lignin content. Anaerobic digestibility is estimated using a Biochemical Methane Potential (BMP) test, which lasts several weeks. Since the Py-GC-MS technique is considered to be a rapid method for obtaining information on various organic components, its suitability for the study of fungal pretreatment efficiency in anaerobic digestion was investigated here, to our knowledge for the first time. In this goal, mycelium of the white-rot fungi Polyporus brumalis BRFM 985, untreated wheat straw and straw pretreated with different fungal strains and under different conditions were analysed with Py-GC-MS. In the mycelium pyrolysate, diverse compounds, often considered as unspecific, probably derive from proteins (toluene, etc.). A strong presence of tyrosine and phenylalanine among the fungus amino acids was also suspected.As for pretreated straw samples, a correlation was observed between the amount of fungal biomass determined by qPCR (used as a reference method) and the sum of relative areas of toluene, styrene and ethylbenzene in the pyrograms, showing that it is feasible to estimate the fungal biomass amount on pretreated straws using Py-GC-MS.In addition, the H/L-Py (Holocelluloses/Lignin) ratio, determined by dividing the sums of areas of pyrolysis compounds that have a polysaccharide (PS) and lignin (LIG) origin, was correlated to the BMP values of pretreated straws, thus showing that the pretreatment efficiency can be rapidly estimated with Py-GC-MS in the tested conditions.