A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network.
Identifieur interne : 000253 ( PubMed/Checkpoint ); précédent : 000252; suivant : 000254A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network.
Auteurs : Shu-Tao Wang ; Dong-Ying Chen ; Xing-Long Wang ; Meng Wei ; Zhi-Fang WangSource :
- Guang pu xue yu guang pu fen xi = Guang pu [ 1000-0593 ] ; 2015.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Sorbic Acid.
- analysis : Fruit and Vegetable Juices.
- Algorithms, Citrus sinensis, Neural Networks (Computer), Spectrometry, Fluorescence.
Abstract
In this paper, fluorescence spectra properties of potassium sorbate in aqueous solution and orange juice are studied, and the result.shows that in two solution there are many difference in fluorescence spectra of potassium sorbate, but the fluorescence characteristic peak exists in λ(ex)/λ(em) = 375/490 nm. It can be seen from the two dimensional fluorescence spectra that the relationship between the fluorescence intensity and the concentration of potassium sorbate is very complex, so there is no linear relationship between them. To determine the concentration of potassium sorbate in orange juice, a new method combining Particle Swarm Optimization (PSO) algorithm with Back Propagation (BP) neural network is proposed. The relative error of two predicted concentrations is 1.83% and 1.53% respectively, which indicate that the method is feasible. The PSO-BP neural network can accurately measure the concentration of potassium sorbate in orange juice in the range of 0.1-2.0 g · L⁻¹.
PubMed: 26964248
Affiliations:
Links toward previous steps (curation, corpus...)
Links to Exploration step
pubmed:26964248Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network.</title>
<author><name sortKey="Wang, Shu Tao" sort="Wang, Shu Tao" uniqKey="Wang S" first="Shu-Tao" last="Wang">Shu-Tao Wang</name>
</author>
<author><name sortKey="Chen, Dong Ying" sort="Chen, Dong Ying" uniqKey="Chen D" first="Dong-Ying" last="Chen">Dong-Ying Chen</name>
</author>
<author><name sortKey="Wang, Xing Long" sort="Wang, Xing Long" uniqKey="Wang X" first="Xing-Long" last="Wang">Xing-Long Wang</name>
</author>
<author><name sortKey="Wei, Meng" sort="Wei, Meng" uniqKey="Wei M" first="Meng" last="Wei">Meng Wei</name>
</author>
<author><name sortKey="Wang, Zhi Fang" sort="Wang, Zhi Fang" uniqKey="Wang Z" first="Zhi-Fang" last="Wang">Zhi-Fang Wang</name>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2015">2015</date>
<idno type="RBID">pubmed:26964248</idno>
<idno type="pmid">26964248</idno>
<idno type="wicri:Area/PubMed/Corpus">000108</idno>
<idno type="wicri:Area/PubMed/Curation">000108</idno>
<idno type="wicri:Area/PubMed/Checkpoint">000108</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network.</title>
<author><name sortKey="Wang, Shu Tao" sort="Wang, Shu Tao" uniqKey="Wang S" first="Shu-Tao" last="Wang">Shu-Tao Wang</name>
</author>
<author><name sortKey="Chen, Dong Ying" sort="Chen, Dong Ying" uniqKey="Chen D" first="Dong-Ying" last="Chen">Dong-Ying Chen</name>
</author>
<author><name sortKey="Wang, Xing Long" sort="Wang, Xing Long" uniqKey="Wang X" first="Xing-Long" last="Wang">Xing-Long Wang</name>
</author>
<author><name sortKey="Wei, Meng" sort="Wei, Meng" uniqKey="Wei M" first="Meng" last="Wei">Meng Wei</name>
</author>
<author><name sortKey="Wang, Zhi Fang" sort="Wang, Zhi Fang" uniqKey="Wang Z" first="Zhi-Fang" last="Wang">Zhi-Fang Wang</name>
</author>
</analytic>
<series><title level="j">Guang pu xue yu guang pu fen xi = Guang pu</title>
<idno type="ISSN">1000-0593</idno>
<imprint><date when="2015" type="published">2015</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term>
<term>Citrus sinensis</term>
<term>Fruit and Vegetable Juices (analysis)</term>
<term>Neural Networks (Computer)</term>
<term>Sorbic Acid (analysis)</term>
<term>Spectrometry, Fluorescence</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Sorbic Acid</term>
</keywords>
<keywords scheme="MESH" qualifier="analysis" xml:lang="en"><term>Fruit and Vegetable Juices</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Algorithms</term>
<term>Citrus sinensis</term>
<term>Neural Networks (Computer)</term>
<term>Spectrometry, Fluorescence</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">In this paper, fluorescence spectra properties of potassium sorbate in aqueous solution and orange juice are studied, and the result.shows that in two solution there are many difference in fluorescence spectra of potassium sorbate, but the fluorescence characteristic peak exists in λ(ex)/λ(em) = 375/490 nm. It can be seen from the two dimensional fluorescence spectra that the relationship between the fluorescence intensity and the concentration of potassium sorbate is very complex, so there is no linear relationship between them. To determine the concentration of potassium sorbate in orange juice, a new method combining Particle Swarm Optimization (PSO) algorithm with Back Propagation (BP) neural network is proposed. The relative error of two predicted concentrations is 1.83% and 1.53% respectively, which indicate that the method is feasible. The PSO-BP neural network can accurately measure the concentration of potassium sorbate in orange juice in the range of 0.1-2.0 g · L⁻¹.</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26964248</PMID>
<DateCreated><Year>2016</Year>
<Month>3</Month>
<Day>11</Day>
</DateCreated>
<DateCompleted><Year>2016</Year>
<Month>04</Month>
<Day>26</Day>
</DateCompleted>
<DateRevised><Year>2016</Year>
<Month>3</Month>
<Day>11</Day>
</DateRevised>
<Article PubModel="Print"><Journal><ISSN IssnType="Print">1000-0593</ISSN>
<JournalIssue CitedMedium="Print"><Volume>35</Volume>
<Issue>12</Issue>
<PubDate><Year>2015</Year>
<Month>Dec</Month>
</PubDate>
</JournalIssue>
<Title>Guang pu xue yu guang pu fen xi = Guang pu</Title>
<ISOAbbreviation>Guang Pu Xue Yu Guang Pu Fen Xi</ISOAbbreviation>
</Journal>
<ArticleTitle>A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network.</ArticleTitle>
<Pagination><MedlinePgn>3549-54</MedlinePgn>
</Pagination>
<Abstract><AbstractText>In this paper, fluorescence spectra properties of potassium sorbate in aqueous solution and orange juice are studied, and the result.shows that in two solution there are many difference in fluorescence spectra of potassium sorbate, but the fluorescence characteristic peak exists in λ(ex)/λ(em) = 375/490 nm. It can be seen from the two dimensional fluorescence spectra that the relationship between the fluorescence intensity and the concentration of potassium sorbate is very complex, so there is no linear relationship between them. To determine the concentration of potassium sorbate in orange juice, a new method combining Particle Swarm Optimization (PSO) algorithm with Back Propagation (BP) neural network is proposed. The relative error of two predicted concentrations is 1.83% and 1.53% respectively, which indicate that the method is feasible. The PSO-BP neural network can accurately measure the concentration of potassium sorbate in orange juice in the range of 0.1-2.0 g · L⁻¹.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Shu-tao</ForeName>
<Initials>ST</Initials>
</Author>
<Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Dong-ying</ForeName>
<Initials>DY</Initials>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Xing-long</ForeName>
<Initials>XL</Initials>
</Author>
<Author ValidYN="Y"><LastName>Wei</LastName>
<ForeName>Meng</ForeName>
<Initials>M</Initials>
</Author>
<Author ValidYN="Y"><LastName>Wang</LastName>
<ForeName>Zhi-fang</ForeName>
<Initials>ZF</Initials>
</Author>
</AuthorList>
<Language>ENG</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
</PublicationTypeList>
</Article>
<MedlineJournalInfo><Country>China</Country>
<MedlineTA>Guang Pu Xue Yu Guang Pu Fen Xi</MedlineTA>
<NlmUniqueID>9424805</NlmUniqueID>
<ISSNLinking>1000-0593</ISSNLinking>
</MedlineJournalInfo>
<ChemicalList><Chemical><RegistryNumber>X045WJ989B</RegistryNumber>
<NameOfSubstance UI="D013011">Sorbic Acid</NameOfSubstance>
</Chemical>
</ChemicalList>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="N">Algorithms</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D032084" MajorTopicYN="N">Citrus sinensis</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000067030" MajorTopicYN="N">Fruit and Vegetable Juices</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D016571" MajorTopicYN="Y">Neural Networks (Computer)</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013011" MajorTopicYN="N">Sorbic Acid</DescriptorName>
<QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D013050" MajorTopicYN="Y">Spectrometry, Fluorescence</DescriptorName>
</MeshHeading>
</MeshHeadingList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2016</Year>
<Month>3</Month>
<Day>12</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2016</Year>
<Month>3</Month>
<Day>12</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2016</Year>
<Month>4</Month>
<Day>27</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>ppublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">26964248</ArticleId>
</ArticleIdList>
</PubmedData>
</pubmed>
<affiliations><list></list>
<tree><noCountry><name sortKey="Chen, Dong Ying" sort="Chen, Dong Ying" uniqKey="Chen D" first="Dong-Ying" last="Chen">Dong-Ying Chen</name>
<name sortKey="Wang, Shu Tao" sort="Wang, Shu Tao" uniqKey="Wang S" first="Shu-Tao" last="Wang">Shu-Tao Wang</name>
<name sortKey="Wang, Xing Long" sort="Wang, Xing Long" uniqKey="Wang X" first="Xing-Long" last="Wang">Xing-Long Wang</name>
<name sortKey="Wang, Zhi Fang" sort="Wang, Zhi Fang" uniqKey="Wang Z" first="Zhi-Fang" last="Wang">Zhi-Fang Wang</name>
<name sortKey="Wei, Meng" sort="Wei, Meng" uniqKey="Wei M" first="Meng" last="Wei">Meng Wei</name>
</noCountry>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Bois/explor/OrangerV1/Data/PubMed/Checkpoint
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000253 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd -nk 000253 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Bois |area= OrangerV1 |flux= PubMed |étape= Checkpoint |type= RBID |clé= pubmed:26964248 |texte= A New Method for the Determination of Potassium Sorbate Combining Fluorescence Spectra Method with PSO-BP Neural Network. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/PubMed/Checkpoint/RBID.i -Sk "pubmed:26964248" \ | HfdSelect -Kh $EXPLOR_AREA/Data/PubMed/Checkpoint/biblio.hfd \ | NlmPubMed2Wicri -a OrangerV1
![]() | This area was generated with Dilib version V0.6.25. | ![]() |