The X-loading plot for the first two axes was constructed and is shown in Fig. 2b. PC-1 was mainly correlated with m/z 61, 75, 85, 89, 103, 117, 131, 145 and 159, these are well known parent and fragment ions of common alkylesters ( Aprea,
Biasioli, Saracatinib manufacturer Märk, & Gasperi, 2007). Similar fragments have also been reported in other DIMS studies. PC1 can therefore be tentatively identified as being related to the relative abundance of esters, and therefore the axis would be correlated to flavour notes such as fruity, ethereal, and fresh. Indeed, Jazz and Braeburn samples were clustered in the left side of the PCA map whilst the Granny Smith and Golden Delicious in the right. The second PC axis was also correlated with fragments of esters
and alcohols, of which m/z 61 or 85 are tentatively attributed as fragments of acetates and 1-hexanol ( Soukoulis et al., 2013), and 101 and 99 are proposed to be the parent ions of carbonyl compounds e.g. 1-hexanal (m/z 101) or trans-2-hexenal (m/z 99). Furthermore, m/z 83 was strongly discriminating and could be attributed to a dehydration product of 1-hexanal. According to the X-loading plot for PC-1 and PC-3 (Fig. 3b) the peaks at m/z 47 and 45, which correspond to see more ethanol and acetaldehyde respectively ( Davies et al., 2011), allowed the discrimination between Jazz and Braeburn apples supporting the classification data displayed in Table 2. Acetaldehyde is one of the most abundant volatile compounds present in the headspace of fresh cut apples ( Ting et
al., 2012). Apples juices extracted from Braeburn, Golden Delicious and Pink Lady were characterised by higher levels of acetaldehyde and ethanol which is in accordance with previously published data ( Ting et al., 2012). Ethanol is considered as an indicator of post harvesting conditions e.g. exposure to hypoxia, stage of climacteric ripening ( Dixon, 1999). According to Fig. 3a, juices extracted from Braeburn and Pink Lady had higher amounts of ethanol compared to Jazz and Granny Smith. The former observation the implies that the APCI-MS fingerprinting may also provide important information associated not only with the genetic diversity of the samples but also with the adopted post-harvest practices, although further studies are recommended in this area. For the further evaluation of APCI-MS as a viable method for food authenticity testing and classification, the geographical provenance of the apples tested previously was also modelled. As it can be seen in Fig. 4a, effective clustering for the three apple juices was obtained, with New Zealand and South Africa being most clearly discriminated. The first two principle component axes accounted for 48% of total variability. For the PLS-DA models, five principle components were used which accounted for 79.7% of the total variability. The most robust classification performance was obtained in the case of internally validated PLS-DA models (97.
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