There is an ongoing research effort at the United States Department of Agriculture to improve an existing spectral database, where botanical cotton trash samples are identified through mid-infrared spectroscopy. Leaf, hull, shale, stem, seed, and other trash samples have been reported to be problematic in the efficiency and quality of cotton throughout the textile spinning processes. Currently, several techniques are being employed to detect the presence of trash in cotton (ex. Shirley Analyzer, AFIS, and HVI) based on physical size and weight. However, more innovative methods need to be explored in order to classify specific types of trash found in cotton during different segments of ginning and textile processing. This research simulated ginning and textile processes by subjecting botanical trash samples to various size reductions and thermal conditions. Prior to performing extractions, trash samples were reduced from their raw sample size using a Wiley Mill with 20 and 80 meshes, and then subjected to heat treatments. Fourier –transform infrared (FT-IR) spectrometry was used for the fundamental analysis of these different trash extractions under simulated ginning and textile processing conditions. Collected IR data indicate this technique to be a potential approach in locating definite regions for evaluating any differences that might occur during processing.