A chemometric calibration toolbox, which contains Inverse Least Squares (ILS) regression, Principle Components Regression (PCR), Partial Least Squares Regression (PLSR), Genetic Inverse Least Squares (GILS) regression, and Ridge regression, was developed in MATLAB environment. During the development, multiple strategies to improve the calculation speed, namely vectorization and parallelization, were employed. Besides these programmatic strategies, efficient cross-validation (CV) procedures were implemented that are specifically tailored for parameter tuning of PCR and PLSR. For GILS, by constructing CV matrices in advance, the computational cost was further reduced. Additionally, a Graphical User Interface (GUI), which also includes baseline correction and variable range selection capabilities, was developed. For increased convenience, regardless of the chosen model, the toolbox returns a single vector of regression coefficients that accounts for centering and scaling of variables along with variable selection. Using the developed toolbox, quantitative determination of salep adulteration was carried out through chemometric calibration methods on Mid-IR data obtained from FTIRATR which is a fast and easy-to-use spectroscopic instrument. The main motivation was the lack of an established method for determination of adulteration of salep which can be quite common due to very high price of pure salep, despite the strict legal regulations. Using 365 samples covering a wide range of adulteration scenarios with 20 adulterants, calibration models were obtained and evaluated. Ensemble model, obtained by averaging GILS and Ridge, yielded the best RMSEP of 6.82 (w/w %). To cope with the unspecific adulterant problem, SIMCA was employed to provide an qualitative insight about the presence of such compounds.