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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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| Published in: | Journal of radioanalytical and nuclear chemistry 2019-12, Vol.322 (3), p.1571-1578 |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c358t-73d60a531614189b5de8b18b2657d92555b6769f6ab9fe12342b94c6e4e171df3 |
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| cites | cdi_FETCH-LOGICAL-c358t-73d60a531614189b5de8b18b2657d92555b6769f6ab9fe12342b94c6e4e171df3 |
| container_end_page | 1578 |
| container_issue | 3 |
| container_start_page | 1571 |
| container_title | Journal of radioanalytical and nuclear chemistry |
| container_volume | 322 |
| creator | Tejeda Mazola, Yuniel De Nadai Fernandes, Elisabete A. Sarriés, Gabriel A. Bacchi, Márcio A. Gonzaga, Cláudio L. |
| 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%. |
| doi_str_mv | 10.1007/s10967-019-06874-2 |
| format | article |
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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%.</description><identifier>ISSN: 0236-5731</identifier><identifier>EISSN: 1588-2780</identifier><identifier>DOI: 10.1007/s10967-019-06874-2</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>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</subject><ispartof>Journal of radioanalytical and nuclear chemistry, 2019-12, Vol.322 (3), p.1571-1578</ispartof><rights>Akadémiai Kiadó, Budapest, Hungary 2019</rights><rights>COPYRIGHT 2019 Springer</rights><rights>Copyright Springer Nature B.V. 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c358t-73d60a531614189b5de8b18b2657d92555b6769f6ab9fe12342b94c6e4e171df3</citedby><cites>FETCH-LOGICAL-c358t-73d60a531614189b5de8b18b2657d92555b6769f6ab9fe12342b94c6e4e171df3</cites><orcidid>0000-0002-3414-5510</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Tejeda Mazola, Yuniel</creatorcontrib><creatorcontrib>De Nadai Fernandes, Elisabete A.</creatorcontrib><creatorcontrib>Sarriés, Gabriel A.</creatorcontrib><creatorcontrib>Bacchi, Márcio A.</creatorcontrib><creatorcontrib>Gonzaga, Cláudio L.</creatorcontrib><title>Neutron activation analysis and data mining techniques to discriminate between beef cattle diets</title><title>Journal of radioanalytical and nuclear chemistry</title><addtitle>J Radioanal Nucl Chem</addtitle><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. 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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%.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><doi>10.1007/s10967-019-06874-2</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-3414-5510</orcidid></addata></record> |
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| ispartof | Journal of radioanalytical and nuclear chemistry, 2019-12, Vol.322 (3), p.1571-1578 |
| issn | 0236-5731 1588-2780 |
| language | eng |
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| source | Springer Link |
| 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 |
| title | Neutron activation analysis and data mining techniques to discriminate between beef cattle diets |
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