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

Abstract 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 ( R 2 0.95), apparent ( R 2 0.89) and real ( R 2 0.95) extracts, real and apparent degrees of fermentation ( R 2 0.91 and 0.89), alcohol content ( R 2 0.94) and energetic value ( R 2 0.95). Good results ( R 2 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.