Micotoxinas en el análisis de los alimentos: Un estudio con indicadores bibliométricos y mapas de visualización

Ricardo A.J. Leon-Vasquez, Cesar H. Limaymanta

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

Resumen

The purpose of the study was to identify the development of scientific production by year and journal, determine the thematic structure and identify the co-authorship network of the literature about mycotoxins in food analysis. A descriptive study was conducted of documents published in the database Scopus from 2011 to 2020, using bibliometric indicators and visualization maps. A total 453 articles were included which met the inclusion criteria. Of these, 382 were research articles and 71 were reviews. The average annual number of citations per article ranged from 6 in 2019 to 40.5 in 2012. The most productive journal was Mycotoxin Research from Springer Nature publishers. The co-occurrence map displayed five descriptor clusters, whereas the co-authorship map displayed 21 clusters, 14 of which corresponded to authors researching in co-authorship. Scientific development had a non-uniform, slowly growing annual output. The thematic structure according to the co-occurrence network shows that the most frequent term is "mycotoxins", corresponding to mycotoxins influencing public health from the first cluster. The co-authorship network shows that 98.2% of the articles were co-authored, and the most productive author was Krska Rudolf, from Queen's University, Belfast, with 24 articles.

Título traducido de la contribuciónMycotoxins in food analysis: A study with bibliometric indicators and visualization maps
Idioma originalEspañol
Número de artículoe1792
PublicaciónRevista Cubana de Informacion en Ciencias de la Salud
Volumen32
N.º4
EstadoPublicada - 1 oct. 2021
Publicado de forma externa

Nota bibliográfica

Publisher Copyright:
© 2021, Centro Nacional de Informacion de Ciencias Medicas. All rights reserved.

Palabras clave

  • Mycotoxins
  • bibliometrics
  • food analysis
  • visualization maps

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