Milk-sense: a volatile sensing system recognises spoilage bacteria and yeasts in milk

An electronic nose unit including 14 conducting polymer sensors, was used to detect the volatile profiles produced by uninoculated skimmed milk media or that inoculated with bacteria (Pseudomonas aureofaciens, P. fluorescens, Bacillus cereus) or yeasts (Candida pseudotropicalis, Kluyveromyces lactis) when grown for 5 h at 30°C. Using discriminant function analyses (DFA) it was possible to separate unspoiled milk and that containing spoilage bacteria or yeasts. The sensor array used was a useful discriminator of microbial volatile profiles. Quantitative differentiation between three different concentrations of P. aureofaciens (106, 3.5×108, 8×108 CFUs ml−1) was also investigated and showed that the system could effectively differentiate between treatments. Using an initial inoculum of about 103–104 CFUs ml−1 it was possible to discriminate between unspoiled milk, yeasts and bacterial species (S. aureus, B. cereus and the Pseudomonas spp.) using principal component analyses (PCA), and also between the bacteria, the unspoiled milk, and the two yeasts C. pseudotropicalis and K. lactis with 85% of the data accounted for. The potential for differentiation between four of the five individual bacterial and yeast species was analysed after 5 h growth at 25°C by using a three-layer back propagation neural network (NN) of 46 input sensor parameters. This showed that it was possible to recognise, and differentiate, between species, the butanol and milk medium controls. Cross validation using labelled individual replicates of treatments as unknowns demonstrated that it was possible to differentiate between (a) butanol controls; (b) unspoiled milk medium; (c) S. aureus; (d) K. lactis; (e) C. psuedotropicalis; and (f) B. cereus. The potential for using an electronic nose system for early detection of microbial spoilage of milk-based products is discussed.