Authentication of beef cuts by multielement and machine learning approaches.

Background: Brazil has consolidated a relevant position in the world market, being the largest exporter and second producer of beef. Genetics, feeding system, geographic origin and climate influence the multielement profile of beef. The feasibility of combining classification algorithms with major and trace elements was evaluated as a tool for authentication of beef cuts.

Elemental profile of dietary supplements and agricultural byproducts evaluated by neutron activation analysis.

Dietary supplements and agricultural byproducts were characterized by neutron activation analysis. The nutritional potential of supplements was evaluated according to alternative and commercial categories, using analysis of variance and cluster analysis, and recommended dietary intake for children. The results indicated statistically significant differences between both categories for the elements Cs, K, Na, and Rb.

Trace elements and machine learning for Brazilian beef traceability.

Brazilian livestock with a herd of more than 215 million animals is distributed over a vast area of 160 million hectares, leading the country to the first position in the world beef exports and second in beef production and consumption. Animals risen in the biomes Amazônia, Caatinga, Cerrado, Pampa and Pantanal were selected for this study. Beef samples were analyzed for their elemental content by neutron activation analysis and classified according to their origin by three machine learning algorithms (Multilayer Perceptron, Random Forest and Classification and Regression Tree).

Arsenic and cadmium contents in Brazilian rice from different origins can vary more than two orders of magnitude.

Brazil is a major producer of rice, but there is not enough information about As and Cd in rice grown under different conditions in this country. Here, As and Cd were determined by ICP-MS and species of As by HPLC-ICP-MS in Brazilian husked rice, covering diverse cultivars and regions, as well as upland and flooded production systems. Significant differences were observed for contents of both elements according to the origin of rice.

Trace element measurement for assessment of dog food safety.

The quality of dog diets depends on adequate ingredients capable of providing optimal nutrition and free of contaminants, for promoting long-term health. Trace elements in 95 samples of dry food for dog puppies (n = 32) and adults (n = 63) of various brands were measured using instrumental neutron activation analysis (INAA). The mass fractions of most elements were within the permissible limits for dogs.

Elemental characterization of single-wall carbon nanotube certified reference material by neutron and prompt γ activation analysis.

Instrumental neutron activation analysis with both relative and k0 standardization was used in four experienced laboratories to determine element mass fractions in single-wall carbon nanotube certified reference material (CRM) SWCNT-1. Results obtained were evaluated using the National Institute of Standards and Technology (NIST) "Type B On Bias" approach and yielded consensus values in agreement with National Research Council Canada (NRCC) certified values for Fe, Co, Ni, and Mo and provided mass fraction values for 13 additional elements, namely, Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Br, La, W, and Au. In addition, prompt γ neutron activation analysis was employed to determine mass fractions of H, B, Co, Ni, and Mo.

Chemical elements in organic and conventional sweet oranges.

This work focuses on the determination of chemical elements in sweet oranges of variety Valencia produced under organic and conventional systems using instrumental neutron activation analysis and inductively coupled plasma mass spectrometry. The distribution of chemical elements was variable among the fruit parts with usually higher concentrations of Br, Ca, Ce, K, La, Na, Rb, and Sc in the peel. However, K, Na, and Rb also presented high values in the juice samples, while Fe and Zn were higher in the seeds.