A bibliometric and visual analysis of fruit quality detection research
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Food Science and Technology (Campinas) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101304 |
Resumo: | Abstract To understand the research status and current dynamics of fruit quality detection and objectively reflect the influence of different countries, research institutions and authors in this field, the software CiteSpace was used to bibliometrically and visually analyze the relevant literature on fruit quality detection in Web of Science (WoS) database from 1982 to 2021. The results showed that the number of publications on fruit quality detection showed a trend of slow in the early stage, rapid in the middle stage and intensified in the late stage. China has the largest number of international publications, accounting for 21.80% of the WoS database, but its intermediary centrality is inferior to that of the United States, Germany, Italy and Spain; the United States is at the core of international cooperation, establishing cooperative relations with most countries; through keywords co-occurrence network and keyword clustering, it is concluded that the research mainly focuses on fruit quality detection based on spectral technology or electronic nose technology, fruit composition detection based on high-performance liquid chromatography (HPLC), fruit edible safety detection, and genetic analysis of fruit quality-related traits. Bibliometrics and visual analysis of this fruit quality detection research can provide a certain reference for relevant researchers. |
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Food Science and Technology (Campinas) |
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A bibliometric and visual analysis of fruit quality detection researchfruit quality detectionCiteSpaceresearch trendbibliometric analysisAbstract To understand the research status and current dynamics of fruit quality detection and objectively reflect the influence of different countries, research institutions and authors in this field, the software CiteSpace was used to bibliometrically and visually analyze the relevant literature on fruit quality detection in Web of Science (WoS) database from 1982 to 2021. The results showed that the number of publications on fruit quality detection showed a trend of slow in the early stage, rapid in the middle stage and intensified in the late stage. China has the largest number of international publications, accounting for 21.80% of the WoS database, but its intermediary centrality is inferior to that of the United States, Germany, Italy and Spain; the United States is at the core of international cooperation, establishing cooperative relations with most countries; through keywords co-occurrence network and keyword clustering, it is concluded that the research mainly focuses on fruit quality detection based on spectral technology or electronic nose technology, fruit composition detection based on high-performance liquid chromatography (HPLC), fruit edible safety detection, and genetic analysis of fruit quality-related traits. Bibliometrics and visual analysis of this fruit quality detection research can provide a certain reference for relevant researchers.Sociedade Brasileira de Ciência e Tecnologia de Alimentos2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101304Food Science and Technology v.42 2022reponame:Food Science and Technology (Campinas)instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)instacron:SBCTA10.1590/fst.72322info:eu-repo/semantics/openAccessMA,XuetingLUO,HuapingZHANG,FeiGAO,Fengeng2022-08-30T00:00:00Zoai:scielo:S0101-20612022000101304Revistahttp://www.scielo.br/ctaONGhttps://old.scielo.br/oai/scielo-oai.php||revista@sbcta.org.br1678-457X0101-2061opendoar:2022-08-30T00:00Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA)false |
dc.title.none.fl_str_mv |
A bibliometric and visual analysis of fruit quality detection research |
title |
A bibliometric and visual analysis of fruit quality detection research |
spellingShingle |
A bibliometric and visual analysis of fruit quality detection research MA,Xueting fruit quality detection CiteSpace research trend bibliometric analysis |
title_short |
A bibliometric and visual analysis of fruit quality detection research |
title_full |
A bibliometric and visual analysis of fruit quality detection research |
title_fullStr |
A bibliometric and visual analysis of fruit quality detection research |
title_full_unstemmed |
A bibliometric and visual analysis of fruit quality detection research |
title_sort |
A bibliometric and visual analysis of fruit quality detection research |
author |
MA,Xueting |
author_facet |
MA,Xueting LUO,Huaping ZHANG,Fei GAO,Feng |
author_role |
author |
author2 |
LUO,Huaping ZHANG,Fei GAO,Feng |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
MA,Xueting LUO,Huaping ZHANG,Fei GAO,Feng |
dc.subject.por.fl_str_mv |
fruit quality detection CiteSpace research trend bibliometric analysis |
topic |
fruit quality detection CiteSpace research trend bibliometric analysis |
description |
Abstract To understand the research status and current dynamics of fruit quality detection and objectively reflect the influence of different countries, research institutions and authors in this field, the software CiteSpace was used to bibliometrically and visually analyze the relevant literature on fruit quality detection in Web of Science (WoS) database from 1982 to 2021. The results showed that the number of publications on fruit quality detection showed a trend of slow in the early stage, rapid in the middle stage and intensified in the late stage. China has the largest number of international publications, accounting for 21.80% of the WoS database, but its intermediary centrality is inferior to that of the United States, Germany, Italy and Spain; the United States is at the core of international cooperation, establishing cooperative relations with most countries; through keywords co-occurrence network and keyword clustering, it is concluded that the research mainly focuses on fruit quality detection based on spectral technology or electronic nose technology, fruit composition detection based on high-performance liquid chromatography (HPLC), fruit edible safety detection, and genetic analysis of fruit quality-related traits. Bibliometrics and visual analysis of this fruit quality detection research can provide a certain reference for relevant researchers. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101304 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-20612022000101304 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/fst.72322 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Ciência e Tecnologia de Alimentos |
publisher.none.fl_str_mv |
Sociedade Brasileira de Ciência e Tecnologia de Alimentos |
dc.source.none.fl_str_mv |
Food Science and Technology v.42 2022 reponame:Food Science and Technology (Campinas) instname:Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA) instacron:SBCTA |
instname_str |
Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA) |
instacron_str |
SBCTA |
institution |
SBCTA |
reponame_str |
Food Science and Technology (Campinas) |
collection |
Food Science and Technology (Campinas) |
repository.name.fl_str_mv |
Food Science and Technology (Campinas) - Sociedade Brasileira de Ciência e Tecnologia de Alimentos (SBCTA) |
repository.mail.fl_str_mv |
||revista@sbcta.org.br |
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1752126335114805248 |