Grape stalks, an inedible lignocellulosic residue from winemaking and agro-industrial grape juice production, can be valorized as a source of bioactive compounds and as feedstock for the saccharification and bioconversion of soluble sugars. Solid-state fermentation (SSF) by six white-rot fungi was applied as pretreatment. Fiber composition, free radical scavenging activity, four ligninolytic, and three hydrolytic enzyme activities were determined. Saccharification kinetics, yield, and productivity were evaluated and complemented with scanning electron microscopy (SEM), high performance liquid chromatography (HPLC) quantification of monosaccharides, and principal component analysis (PCA). After SSF, the biomass exhibited a drastic free radical scavenging activity decrease and the main enzymes produced were manganese-dependent peroxidase and xylanase. Scanning electron microscopy revealed the erosion of cell walls, and PCA exhibited a negative correlation between saccharification, and neutral detergent fiber and acid detergent lignin. Phlebia rufa pretreated biomass gave the highest sugars yield and productivity, representing a nearly three-fold increase compared to untreated samples. Also, monosaccharides quantification revealed that the 1:1 ratio of glucose to the sum of xylose plus galactose changes to the value of 2:1 after pretreatment. In this work, and for the first time, P. rufa proved to be an effective pretreatment of grape stalks for the saccharification and further bioconversion into value-added chemicals. In addition, lignocellulolytic enzymes were also produced through SSF.

The Michaelis–Menten equation (MME) has been extensively used in biochemical reactions, but it is not appropriate when the reaction product inhibits the enzyme. Under these circumstances, each determined initial velocity, v₀, is one experimental point that actually belongs to a different MME because enzymatic product inhibition occurs as the reaction starts. Furthermore, the inhibition effect is not constant, since the concentration of the product inhibitor rises as time increases. To unveil the hidden enzyme inhibition and to simultaneously demonstrate the superiority of an integrated Michaelis–Menten equation (IMME), the same range of data points, assuming product inhibition and the presence of a second different inhibitor, was used for kinetic analysis with both methodologies. This study highlights the superiority of the IMME methodology for when the enzyme is inhibited by the reaction product, giving a more coherent inhibition model and more accurate kinetic constants than the classical MME methodology.