Ana Cláudia Nascimento

Characterisation of nutrient profile of quinoa (Chenopodium quinoa), amaranth (Amaranthus caudatus), and purple corn (Zea mays L.) consumed in the North of Argentina: proximates, minerals and trace elements.

Quinoa, amaranth and purple corn are Andean cereals largely consumed in North of Argentina. Nutrient analysis with the purpose of inclusion in the Argentinean FCDB and e-search EuroFIR has become urgent matter. In this work proximate and mineral profile of Andean cereals cultivated in the North of Argentina were determined and compared with rice. Proximate analysis showed that Andean cereals have similar profile but significantly higher (p<0.05) than rice. Andean cereals are rich sources of iron, copper, manganese and zinc and better than rice. Phosphorus and magnesium quinoa content could contribute up to 55% of consumers DRI. Andean cereals and rice are poor sources of potassium. To guarantee the interchange of data among users and producers of FCDB component values were obtained in compliance with EuroFIR guidelines for compilation process. Present work provides necessary information to FCDB users who wish to have access to food reference analytical parameters.

Application of chemometric methods for multi‐elemental characterization of fruit juices and nectars analysed in the Portuguese Total Diet Studies pilot study

Multivariate analysis was applied to test the adequacy of pooling samples versus single units as a sampling strategy to estimate dietary intake and risk assessment of chemical elements in nonalcoholic beverages. The contents of 18 minerals and trace elements (Cr, Mn, Cu, Zn, As, Se, Mo, Sr, Co, Cd, Sn, Pb Fe, Mg, Ca, P, Na, and K) in fruit juices and nectars were determined by inductively coupled plasma–optical emission spectrometry and inductively coupled plasma–mass spectrometry. Arsenic speciation was done with high‐performance liquid chromatographer‐inductively coupled plasma–mass spectrometry. The data obtained in pooled samples and single units were then studied by analysis of variance and least significant difference tests, Spearmans correlation, principal component analysis, and cluster analysis. Analysis of variance and least significant difference tests were used to evaluate analytical data from pooled samples and single units. Values of individual units and pooled samples were statistically different with the exception of Se (P < .05), illustrating pooling as an inadequate strategy. Spearmans correlation displayed significant correlations between the following pairs: P‐K (0.924), Mo‐K (0.888), Mo‐P (0.876), and Ca‐Mg (0.846), indicating that chemical elements could be from the same source, having a natural occurrence, or the same exposure sources. By applying principal component analysis and cluster analysis, it was possible to classify juices and nectars by fruit type and geographical origin. It was observed that 2 principal components accounted for 59% of the total variance in the data. Cluster analysis classified samples into 5 clusters. Combined chemometric tools are suited to select appropriate laboratory sampling strategies for risk assessment. Application of chemometric methods to analytical data may be useful to group samples by similar characteristics for the purpose of Total Diet Studies.