The measurement and analysis of fifty-two elements by quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were applied to origin discrimination of Italian traditional cuttlefish (Chioggia, Venice lagoon) from Mediterranean and Atlantic samples. A total 68 specimens were analyzed in triplicates to generate 204 mass spectra profiles which were statistically processed by different chemometric techniques. Loading weights from principal component analysis as input for linear discriminant analysis (LW-LDA), stepwise-LDA (S-LDA) and variable influence of projection-partial least square discriminant analysis (VIP-PLS-DA) were used to classify samples while retaining the lowest possible number of key variables. VIP-PLS-DA was found to be the best variable selection-discriminant tool combo since the selected Na–Co–B–K–Cd–V–U–Rb–Ni–Ba–Cu–As–Sr–Mn–Mo–Li–Ca–Mg–Se–Bi–Cs–P–Y elemental pattern allowed the samples to be classified with 100% sensitivity, specificity and accuracy.
Multi-element signature of cuttlefish and its potential for the discrimination of different geographical provenances and traceability / Varrà, Maria Olga; Husáková, Lenka; Patočka, Jan; Ghidini, Sergio; Zanardi, Emanuela. - In: FOOD CHEMISTRY. - ISSN 0308-8146. - 356:(2021), pp. 129687.129687-129687.129697. [10.1016/j.foodchem.2021.129687]
Multi-element signature of cuttlefish and its potential for the discrimination of different geographical provenances and traceability
Varrà, Maria Olga;Ghidini, Sergio;Zanardi, Emanuela
2021-01-01
Abstract
The measurement and analysis of fifty-two elements by quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were applied to origin discrimination of Italian traditional cuttlefish (Chioggia, Venice lagoon) from Mediterranean and Atlantic samples. A total 68 specimens were analyzed in triplicates to generate 204 mass spectra profiles which were statistically processed by different chemometric techniques. Loading weights from principal component analysis as input for linear discriminant analysis (LW-LDA), stepwise-LDA (S-LDA) and variable influence of projection-partial least square discriminant analysis (VIP-PLS-DA) were used to classify samples while retaining the lowest possible number of key variables. VIP-PLS-DA was found to be the best variable selection-discriminant tool combo since the selected Na–Co–B–K–Cd–V–U–Rb–Ni–Ba–Cu–As–Sr–Mn–Mo–Li–Ca–Mg–Se–Bi–Cs–P–Y elemental pattern allowed the samples to be classified with 100% sensitivity, specificity and accuracy.File | Dimensione | Formato | |
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