Multivariate Statistical Analysis of Data and ICP-MS Determination of Heavy Metals in Different Brands of Spices Consumed in Kayseri, Turkey


Tokalıoğlu Ş. , Çiçek B. , İnanç N. , Zararsız G. , Öztürk A.

FOOD ANALYTICAL METHODS, cilt.11, ss.2407-2418, 2018 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 11 Konu: 9
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1007/s12161-018-1209-y
  • Dergi Adı: FOOD ANALYTICAL METHODS
  • Sayfa Sayıları: ss.2407-2418

Özet

The concentrations of Cr, Mn, Fe, Co, Ni, As, Cd, Pb, and Zn in 19 different spices from 11 different brands (in total 69 samples) collected from Kayseri, Turkey, were determined by inductively coupled plasma mass spectrometry (ICP-MS) after microwave digestion. Multivariate and univariate statistical techniques such as principal component analysis (PCA), cluster analysis (CA), correlation analysis, and one way ANOVA were applied for the interpretation of the obtained data. Three principal components explain 79.6% of the total variance. They are as follows: PC1 with Cr, Fe and Pb; PC2 with Mn, As, and Cd; and PC3 with Ni and Co. The spices were classified into their different types and brands by PCA and CA. The certified reference material (GBW07605 Tea Leaves) was analyzed to confirm the accuracy of the method.