Application of E-nose technology for ultra-high temperature processed partly skimmed milk production batches monitoring

In our work we present a case study of the capability of one electronic nose (P.E.N. 2 sensor array by Airsense Analytics, Germany) in discriminating different qualities of milk samples by sensing their aroma. All the analyzed milk samples, belonging both to different production batches and to different brands, were ultra-high temperature (UHT) processed, partly skimmed, and commercially available at retailers. Milk samples showing off-flavors were compared with other samples of the same kind of milk belonging to the same brand (but to different production batches) and to different brands. The comparison was performed by comparing the smell of the samples just after opening of the packaging and again two hours later. In all cases, principal component analysis carried out on sensor’s output was able to discriminate samples into two different groups characterized by normal and anomalous odour. Moreover, the analysis of the olfactory fingerprints showed that two hours after the opening of the packaging, the flavor of anomalous samples evolved in a different way from that of the normal ones. With reference to this last scenario, the classification of milk odour carried out on sensors’ output by Linear Discriminant Analysis (LDA) exhibit 98.8 % correct assignation and 98.61% correct prediction. The obtained results confirm the utility of the e-nose approach in monitoring the quality of UHT partly skimmed milk production batches, especially if combined with chemical, physical, and sensory techniques).