Núria Mach
Impact in
- Equine top 0.5%
- Animal Science and Zoology top 0.5%
- Animal Nutrition and Physiology
- Meat and Animal Product Quality
Papers in
- Equine 10
- Veterinary Equine Medical Research 10
- Co-authors
- Allison ClarkÀ. BachM. DevantJordi EstelléClaire Rogel GaillardGaëtan LemonnierYuliaxis Ramayo‐CaldasJoël Doré
- Journals
- Scientific Reports (8 papers)BMC Genomics (6 papers)Meat Science (4 papers)Frontiers in Physiology (4 papers)Journal of Animal Breeding and Genetics (3 papers)
- Partner nations
- FranceSpainNetherlands
In The Last Decade
Núria Mach
102 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Equine 225
- Animal Science and Zoology 698
- Agronomy and Crop Science 516
- Small Animals 318
- Rehabilitation 274
Countries citing papers authored by Núria Mach
This map shows the geographic impact of Núria Mach'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 Núria Mach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Núria Mach more than expected).
Fields of papers citing papers by Núria Mach
This network shows the impact of papers produced by Núria Mach. 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 Núria Mach. The network helps show where Núria Mach may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Núria Mach, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 13 | |
| 8 | 2022 | 10 | |
| 9 | 2020 | 42 | |
| 10 | 2019 | 29 | |
| 11 | 2019 | 66 | |
| 12 | 2018 | 41 | |
| 13 | 2017 | 25 | |
| 14 | 2015 | 23 | |
| 15 | Influencia de la gestación, el parto y el tipo de lactancia sobre la microbiota intestinal del neonato | 2014 | 3 |
| 16 | 2012 | 7 | |
| 17 | 2012 | 4 | |
| 18 | 2012 | 114 | |
| 19 | 2011 | 3 | |
| 20 | 2008 | 8 |
About Núria Mach
Núria Mach is a scholar working on Equine, Small Animals, Agronomy and Crop Science, Animal Science and Zoology and Nutrition and Dietetics, having authored 104 papers that have together received 3.6k indexed citations. Recurring topics across this work include Gut microbiota and health (24 papers), Multi-Agent Systems and Negotiation (11 papers), Artificial Intelligence in Law (11 papers), Diet and metabolism studies (10 papers), Veterinary Equine Medical Research (10 papers), Fatty Acid Research and Health (10 papers), Semantic Web and Ontologies (10 papers) and Genetic and phenotypic traits in livestock (9 papers). The work is most often cited by research in Equine (225 citations), Animal Science and Zoology (698 citations), Agronomy and Crop Science (516 citations), Small Animals (318 citations) and Rehabilitation (274 citations). Núria Mach has collaborated with scholars based in France, Spain and Netherlands. Frequent co-authors include Allison Clark, À. Bach, M. Devant, Jordi Estellé, Claire Rogel Gaillard, Gaëtan Lemonnier, Yuliaxis Ramayo‐Caldas, Joël Doré, Antonio Velarde and Mustapha Berri. Their work appears in journals such as Scientific Reports, BMC Genomics, Meat Science, Frontiers in Physiology and Journal of Animal Breeding and Genetics.
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.