Published December 2019
| Version v1
Journal article
Neutron activation analysis and data mining techniques to discriminate between beef cattle diets
Creators
- 1. University of São Paulo, Nuclear Energy Center for Agriculture (Brazil)
- 2. College of Agriculture Luiz de Queiroz (Brazil)
Description
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%.
Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Radioanalytical and Nuclear Chemistry
- Journal Volume
- 322
- Journal Issue
- 3
- Journal Page Range
- p. 1571-1578
- ISSN
- 0236-5731
- CODEN
- JRNCDM
INIS
- Country of Publication
- Hungary
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55001588
- Subject category
- S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY; S38: RADIATION CHEMISTRY, RADIOCHEMISTRY AND NUCLEAR CHEMISTRY;
- Descriptors DEI
- ACCURACY; CATTLE; CLASSIFICATION; LAYERS; MACHINE LEARNING; MINERALS; NEUTRON ACTIVATION ANALYSIS; TRACE AMOUNTS
- Descriptors DEC
- ACTIVATION ANALYSIS; ALGORITHMS; ANIMALS; ARTIFICIAL INTELLIGENCE; CHEMICAL ANALYSIS; DOMESTIC ANIMALS; LEARNING; MAMMALS; MATHEMATICAL LOGIC; NONDESTRUCTIVE ANALYSIS; RUMINANTS; VERTEBRATES
Optional Information
- Copyright
- Copyright (c) 2019 Akad#Latin Small Letter E With Acute#miai Kiad#Latin Small Letter O With Acute#, Budapest, Hungary