  The processing of agricultural wastes towards extraction of renewable
resources is recently being considered as a promising alternative to
conventional biofuel production processes. Agricultural residues represent an
abundant and unexploited raw material that intrinsically contains chemical
energy in the form of polysaccharides. The degradation procedure is a complex
chemical process that is currently time intensive and costly. Various
pre-treatment methods are being investigated to determine the subsequent
modification of the material and the main obstacles in increasing the enzymatic
saccharification yield. In this study, we present a computational model that
complements the experimental approaches. We decipher how the three-dimensional
structure of the substrate impacts the saccharification yield. We model a cell
wall microfibril composed of cellulose and surrounded by hemicellulose and
lignin, with various relative abundances and arrangements. This substrate is
subjected to digestion by different enzyme cocktails of well characterized
enzymes. The saccharification dynamics is mimicked \textit{in silico} using a
stochastic simulation procedure based on a Gillespie algorithm. As we
additionally implement a fitting procedure that optimizes the parameters of the
simulation runs, we are able to reproduce experimental saccharification time
courses for corn stover. Our results challenge the hypothesis of hemicellulose
content being a substantial factor in saccharification yield, and instead
propose the crystallinity of the substrate having a much higher impact.
