Neutron activation analysis and data mining techniques to discriminate between beef cattle diets

Neutron activation analysis and data mining techniques were combined for assessing the mineral composition of diets commonly used to feed beef cattle in Brazil. Among twenty chemical elements determined, Br, Ca, Cs, La, Sc, Se, Sr, Th and Zn showed statistically significant differences between the t...

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Bibliographic Details
Published in:Journal of radioanalytical and nuclear chemistry 2019-12, Vol.322 (3), p.1571-1578
Main Authors: Tejeda Mazola, Yuniel, De Nadai Fernandes, Elisabete A., Sarriés, Gabriel A., Bacchi, Márcio A., Gonzaga, Cláudio L.
Format: Article
Language:English
Subjects:
Activation analysis
Analysis
Beef
Beef cattle
Beef industry
Calcium
Cattle
Chemical elements
Chemistry
Chemistry and Materials Science
Data analysis
Data mining
Diagnostic Radiology
Diet
Food and nutrition
Hadrons
Heavy Ions
Inorganic Chemistry
Methods
Multilayer perceptrons
Neutron activation analysis
Neutrons
Nuclear Chemistry
Nuclear energy
Nuclear Physics
Optimization
Organic chemistry
Physical Chemistry
Strontium
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Summary:Neutron activation analysis and data mining techniques were combined for assessing the mineral composition of diets commonly used to feed beef cattle in Brazil. Among twenty chemical elements determined, Br, Ca, Cs, La, Sc, Se, Sr, Th and Zn showed statistically significant differences between the two cattle diets studied. Chi square indicated that Cs, Se and Sc provided better diets discrimination. The highest classification performances using these elements were achieved for multilayer perceptron and sequential minimal optimization with prediction accuracy of 100%.
ISSN:0236-5731
1588-2780
DOI:10.1007/s10967-019-06874-2