Fourier transform infrared (FT-IR) spectroscopy and improved principal component regression (PCR) for quantification...

In bioanalytical chemistry, a detailed chemical understanding of biomaterials is often difficult to obtain due to the sheer number of analytes contained in a sample along with the samples' generally low reproducibility. This study presents a Fourier transform infrared (FT-IR) spectroscopic technique in conjunction with innovations in sample preparation and chemometric data preprocessing to overcome these limitations. These methodologies were applied to quantitative analyses of 31 representative compounds commonly found in biomaterial, which have been incorporated into a spectroscopic calibration database, that is, albumin (protein); D-alanine, glycine, histidine, valine, arginine, cysteine, phenylalanine, tyrosine, methionine, L-glutamine, and glutamic acid, (amino acids); glucose, fructose, galactose, mannose, sucrose, lactose, glycogen, agarose, and starch (carbohydrates); DNA (salmon sperm), sulphonoquinovosyl diglyceride ( sulpho-lipid ), and 1,2-diacyl-sn-glycero-3-phospho-L-serine ( phospho-lipid ); succinic acid and malic acid ( carboxylic acids ); glycolic acid (a -hydroxy acid), sodium pyruvate, b -carotene, frustules (microalgae silica-shells), and ammonium formate. Two proof-of-principle applications were based on calibration models incorporating these solids, i.e., characterization of E. coli and microalgae. The former aims for detection of bacterial contamination and the latter to enable investigations of changes in chemical composition of microalgae cells in response to shifting environmental conditions. Chemometric preprocessing steps have been developed for handling sample-to-sample fluctuations of absorption path lengths and baselines; the former incorporated mass normalization while the latter utilized a novel baseline correction method that requires no a priori information. Data preprocessing, chemometric calibration, and evaluation algorithms have been combined, together with an extensive spectral database of the aforementioned compounds (∼1500 samples), for quantitative calibration purposes through the remotely accessible Virtual Chemometrics Lab , which can be utilized for a multitude of applications through a graphical user interface.