Beer quality screening by FT-IR spectrometry: Impact of measurement strategies, data pre-processings and variable selection algorithms

In the presented research three measurement strategies of Fourier transform infrared (FT-IR) spectrometry (horizontal- and micro-attenuated total reflection (HATR and μATR, respectively) and a novel high throughput transmission (HTT)) in combination with extensive chemometric approach have been applied for analysis of beer. Fifty Belgian beer samples were analyzed: lager and white beers, dark and blonde ales, lambic and Trappist beers. Partial least square (PLS) regression was used for prediction of different physicochemical parameters of beer based on mid-IR data, modified with different spectral preprocessing and variable selection algorithms for higher prediction performance. It was found that HATR and μATR have the same prediction capability with a slight advantage of μATR and excellent correlations between spectra and reference values were demonstrated for original (R2 0.95), apparent (R2 0.89) and real (R2 0.95) extracts, real and apparent degrees of fermentation (R2 0.91 and 0.89), alcohol content (R2 0.94) and energetic value (R2 0.95). Good results (R2 0.83) were obtained from the HTT experiments for prediction of real extract and allow measurement of large sample numbers in short time (1 sample/minute) with further potential increase in a sample throughput and has the possibility for automation. The obtained results indicate that mid-IR spectrometry in combination with advanced pre-processing and variable selection methods is a valuable analytical tool for high throughput measurement of beer quality attributes and thus has potential for use in product development and quality control.