The choice of suitable online analytical techniques and data processing for monitoring of bioprocesses.

With increasing pressure from regulatory authorities on industry to develop processes embracing process analytical technology (PAT) initiatives, there is a growing demand to establish reliable tools and systems capable of meeting this need. With regard to monitoring and control of bioprocesses, this need translates to a search for robust instrumentation capable of monitoring the critical process parameters in real time. The application of such technologies at all stages of the process, from the initial R&D phase to process optimisation and production, enhances process understanding and paves the way for the development of control platforms. An examination of the PAT concept and selected tools (NIR, MIR, Raman, dielectric spectroscopy and calorimetry) are presented here. A description of each tool is given, with particular emphasis on the nature of the signal produced and how these relate to measurements of biomass, metabolites and product. A description of the signal processing that is necessary to gain meaningful results from the different tools is also given, together with online data reconciliation techniques based on mass and energy balances. Many techniques such as those based on vibrational spectroscopy are of particular interest, since they are capable of monitoring several critical process parameters which are typically controlled in a bioprocess. A window of application for each of the techniques, when used in the area of bioprocessing, is suggested based on their uses and inherent limitations.

Attempted confirmation of the provenance of Corsican PDO honey using FT-IR spectroscopy and multivariate data analysis.

This study investigated the potential of Fourier-transform infrared (FT-IR) spectroscopy and chemometric techniques to produce a mathematical model that would confirm or refute the provenance of honeys claiming to be Corsican. Authentic honey samples from two harvest seasons (2004/2005 and 2005/2006) were collected from Ireland (n=2), Italy (n=30), Austria (n=40), Germany (n=36), mainland France (n=46), and Corsica (n=219). Prior to scanning, samples were diluted with distilled water to a standard solids content (70 degrees Brix). Spectra (2500-12500 nm) were recorded at room temperature using a FT-IR spectrometer equipped with a germanium attenuated total reflectance (ATR) accessory. Standard normal variate (SNV) and first- and second-derivative data pretreatments were applied to the recorded spectra, which were processed using factorial discriminant analysis (FDA) and partial least-squares (PLS) regression analysis. Overall correct classification figures of 82% (FDA) and 87% (PLS) were obtained for a separate validation set comprising samples from both harvests.

Confirmation of food origin claims by fourier transform infrared spectroscopy and chemometrics: extra virgin olive oil from Liguria.

The aim of this study was to explore the potential of Fourier transform infrared spectroscopy and various chemometric tools for confirming the geographic origin of olive oil from Liguria (northern Italy). Authentic extra virgin olive oil samples (n = 913) from three harvests (2004-2007) were collected from Italy, France, Spain, Greece, Cyprus, and Turkeyapproximately one-fourth of all samples originated in Liguria. Attenuated total reflectance spectra were recorded at room temperature; the analytical challenge was to confirm that an oil which claimed to be from Liguria originated there. Derivative and standard normal variate data pretreatments were applied to the recorded spectra, which were subsequently analyzed by a number of multivariate proceduresprincipal component analysis, factorial discriminant analysis, and partial least-squares regression analysis. Prediction models created using samples from all three harvests had sensitivities and selectivities of approximately 0.80.

Multivariate analysis of attenuated total reflection-Fourier transform infrared spectroscopic data to confirm the origin of honeys.

Fourier transform infrared (FT-IR) spectroscopy and chemometrics were used to verify the origin of honey samples (n=150) from Europe and South America. Authentic honey samples were collected from five sources, namely unfiltered samples from Mexico in 2004, commercially filtered samples from Ireland and Argentina in 2004, commercially filtered samples from the Czech Republic in 2005 and 2006, and commercially filtered samples from Hungary in 2006. Samples were diluted with distilled water to a standard solids content (70 degrees Brix) and their spectra (2500-12 500 nm) recorded at room temperature using an FT-IR spectrometer equipped with a germanium attenuated total reflection (ATR) accessory. First- and second-derivative and standard normal variate (SNV) data pretreatments were applied to the recorded spectra, which were analyzed using partial least squares (PLS) regression analysis, factorial discriminant analysis (FDA), and soft independent modeling of class analogy (SIMCA). In general, when an attenuated wavelength range (6800-11 500 nm) rather than the whole spectrum (2500-12 500 nm) was studied, higher correct classification rates were achieved. An overall correct classification of 93.3% was obtained for honeys by PLS discriminant analysis, while FDA techniques correctly classified 94.7% of honey samples. Correct classifications of up to 100% were achieved using SIMCA, but models describing some classes had very high false positive rates.