Christina M. Bava

1.0k citations
13 papers · 755 indexed · h-index 10
Topics
Biochemical Analysis and Sensing Techniques (4 papers)Sensory Analysis and Statistical Methods (4 papers)Olfactory and Sensory Function Studies (3 papers)

In The Last Decade

Christina M. Bava

13 papers receiving 738 citations

Peers

Christina M. Bava
Comparison fields: 5 of 93
  • Food Science 333
  • Nutrition and Dietetics 251
  • Plant Science 215
  • Sensory Systems 200
  • Public Health, Environmental and Occupational Health 103
Replace Marina Peparaio with:
Marina Peparaio Italy
Nancy Holthuysen Netherlands
Line Ahm Mielby Denmark
Helene Christine Reinbach Denmark
Kwang-Ok Kim South Korea
Denize Oliveira Brazil
Mara V. Galmarini Argentina
Joanna Gamble New Zealand
Cristina Proserpio Italy
Christina M. Bava relative to Marina Peparaio Italy Marina Peparaio's profile →
Citations per field
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Citations per year

Countries citing papers authored by Christina M. Bava

Since Specialization
Citations

This map shows the geographic impact of Christina M. Bava's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Christina M. Bava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christina M. Bava more than expected).

Fields of papers citing papers by Christina M. Bava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christina M. Bava. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Christina M. Bava. The network helps show where Christina M. Bava may publish in the future.

Co-authorship network of co-authors of Christina M. Bava

This figure shows the co-authorship network connecting the top 25 collaborators of Christina M. Bava. A scholar is included among the top collaborators of Christina M. Bava based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christina M. Bava. Christina M. Bava is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 122
2 62
3 84
4 103
5 83
6 6
7 50
8 18
9 4
10 101
11 1
12 21
13 100

About Christina M. Bava

Christina M. Bava is a scholar working on Tourism, Leisure and Hospitality Management, Sensory Systems and Food Science, having authored 13 papers that have together received 755 indexed citations. Recurring topics across this work include Biochemical Analysis and Sensing Techniques (4 papers), Sensory Analysis and Statistical Methods (4 papers) and Olfactory and Sensory Function Studies (3 papers). The work is most often cited by research in Sensory Systems (200 citations), Food Science (333 citations) and Tourism, Leisure and Hospitality Management (27 citations). Christina M. Bava has collaborated with scholars based in New Zealand, Uruguay and United Kingdom. Frequent co-authors include Sara R. Jaeger, Sok L. Chheang, Julie Park, Letícia Vidal, Ana Giménez, Gastón Ares, Michelle K. Beresford, Joanna Gamble, David Jin and John A. Dawson. Their work appears in journals such as Current Biology, Appetite and Postharvest Biology and Technology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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