Second-derivative (DDTG) curves helped overcome the challenges of overlapping peaks in the DTG curves of wheat straw; Deconvolution methods lead to high errors in the estimation of lignin content; Curve-fitting methods lead to lower errors when determining the kinetics of biomass degradation, especially for hemicellulose; Reaction networks were modified to consider K content to describe straw pyrolysis. Highlights: Wheat straw is a renewable agricultural by-product that is currently underutilized in the production of bioenergy and bioproducts due to its high ash content, as well as high transport costs due to its low volumetric energy density. The thermogravimetric analysis of this material produces derivative curves with a single broad peak, making it difficult to identify the three conventional pseudo-components (cellulose, hemicellulose, and lignin), which is resolved using the second derivative to determine inflection points. Model-fitting methods and isoconversional methods were applied to determine the degradation kinetics of wheat straw at two different particle sizes, as well as that of a reference feedstock (beech wood), and the obtained values were used to divide the degradation curves to be compared to the experimental data. Seven different pyrolysis reaction networks from the literature were given a similar treatment to determine which provides the best estimation of the actual pyrolysis process for the case of the feedstocks under study. The impact of the potassium content in the feedstock was considered by comparing the original pathway with a modification dependent on the experimental potassium content and an estimated optimum value.