Yeast Detection in Apple Juice Using Raman Spectroscopy and Chemometric Methods

Abstract

Yeast (Saccharomyces cerevisiae spp.) causes unwanted fermentation in apple juice production. Current methods for detecting yeast in the fermentation process are labor intensive and time consuming; therefore, a rapid, reliable method will help ensure consumers a safe and high-quality product. Raman spectroscopy, an advanced optical technique based on light scattering, was investigated as a rapid on-site detection method for yeasts contained in an apple juice droplet. In this study, a dispersive spectrophotometer with a 785 nm diode laser was employed. Chemometric methods such as single linear regression (SLR), partial least squares regression (PLS), principle components regression (PCR), and classification analysis were used to evaluate low-concentration solutions of yeasts in apple juice drops smeared on glass plates. Apple juice samples containing yeast in various concentrations, along with pure samples, were analyzed to predict yeast detection thresholds. Yeast was detected in 85% to 100% of the contaminated samples. The best detection (100%) was achieved at the predicted concentration of 10 CFU mL-1. The results suggest that Raman spectroscopy could be used in apple juice industries as a quality-control tool for rapid, accurate, on-line detection of yeast where a zero tolerance to yeast at 10 CFU mL-1 of pasteurized final product is required.