Assessment of high pressure processed mandarin juice in the headspace by using electronic nose and chemometric analysis

High Pressure Processing (HPP) is a high efficient method for food preservation. As an innovative inspection method, electronic nose (E-nose) was applied to assess the HPP mandarin juices in the headspace. In this work, mandarin juices were processed by HPP at range of 0-500 MPa and diagnosed by E-nose. To improve the efficiency of E-nose, locality preserving projections (LPP) was introduced to extract information of E-nose data and compared with principal component analysis (PCA) and linear discriminant analysis (LDA). Three data extractions (stable value, max value and area value), three data reductions (PCA, LDA and LPP) and two classification algorithms (support vector machine and extreme learning machine) were applied to improve the diagnostic accuracy of E-nose. This study shows that the performance of E-nose can be enhanced by appropriate data extraction and data reduction and also gives a hint of E-nose inspection for HPP fruit juice. Industrial relevance: HHP is a high efficient technology for food preservation, including volatile compounds and solid contents. E-nose, which detect the components changes in sample's headspace, has been widely applied for the food inspection as an innovative detection method. According to authors' best knowledge, researches about E-nose detection for HHP products are not very common. In this study, E-nose is applied to detect the HHP-processed mandarin juices in the headspace. Besides, three data extractions, three data reductions and two classification algorithms were applied to improve the accuracy of E-nose determination in two HHP-process cases. This paper describes the possible application of E-nose to discriminate HHP-processed juices at different pressures. E-nose combined with appropriate pattern recognition could be used as a rapid and high efficient method to discriminate HHP-processed fruit juices.