Maria Font‐i‐Furnols

3.7k total citations · 1 hit paper
107 papers, 2.8k citations indexed

About

Maria Font‐i‐Furnols is a scholar working on Animal Science and Zoology, Small Animals and Food Science. According to data from OpenAlex, Maria Font‐i‐Furnols has authored 107 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Animal Science and Zoology, 34 papers in Small Animals and 25 papers in Food Science. Recurrent topics in Maria Font‐i‐Furnols's work include Meat and Animal Product Quality (85 papers), Animal Nutrition and Physiology (39 papers) and Animal Behavior and Welfare Studies (34 papers). Maria Font‐i‐Furnols is often cited by papers focused on Meat and Animal Product Quality (85 papers), Animal Nutrition and Physiology (39 papers) and Animal Behavior and Welfare Studies (34 papers). Maria Font‐i‐Furnols collaborates with scholars based in Spain, Slovenia and Germany. Maria Font‐i‐Furnols's co-authors include Luís Guerrero, M. Gispert, Núria Tous, E. Esteve‐García, Igor Tomašević, M.A. Oliver, Ilija Đjekić, José M. Lorenzo, Nino Terjung and Antonio Velarde and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Maria Font‐i‐Furnols

102 papers receiving 2.7k citations

Hit Papers

Consumer preference, behavior and perception about meat a... 2014 2026 2018 2022 2014 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Maria Font‐i‐Furnols Spain 26 2.0k 712 497 347 345 107 2.8k
Claudio Cavani Italy 32 3.6k 1.8× 534 0.8× 485 1.0× 242 0.7× 473 1.4× 85 4.0k
Rod Polkinghorne Australia 26 1.8k 0.9× 717 1.0× 290 0.6× 210 0.6× 196 0.6× 71 2.2k
G.E. Gardner Australia 33 2.5k 1.2× 454 0.6× 449 0.9× 357 1.0× 356 1.0× 177 3.4k
J.L. Olleta Spain 29 2.2k 1.1× 469 0.7× 252 0.5× 191 0.6× 212 0.6× 78 2.6k
Bénédicte Lebret France 32 2.8k 1.4× 412 0.6× 643 1.3× 283 0.8× 908 2.6× 89 3.8k
Margit Dall Aaslyng Denmark 34 2.5k 1.3× 1.3k 1.8× 360 0.7× 185 0.5× 593 1.7× 86 3.5k
Katja Rosenvold New Zealand 25 2.4k 1.2× 529 0.7× 216 0.4× 119 0.3× 522 1.5× 42 2.8k
G. Ripoll Spain 29 2.0k 1.0× 424 0.6× 143 0.3× 185 0.5× 217 0.6× 135 2.7k
M.F. Miller United States 35 3.5k 1.8× 1.5k 2.1× 541 1.1× 186 0.5× 454 1.3× 187 4.5k
Massimiliano Petracci Italy 43 5.8k 2.9× 904 1.3× 669 1.3× 346 1.0× 935 2.7× 164 6.6k

Countries citing papers authored by Maria Font‐i‐Furnols

Since Specialization
Citations

This map shows the geographic impact of Maria Font‐i‐Furnols'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 Maria Font‐i‐Furnols with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Font‐i‐Furnols more than expected).

Fields of papers citing papers by Maria Font‐i‐Furnols

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maria Font‐i‐Furnols. 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 Maria Font‐i‐Furnols. The network helps show where Maria Font‐i‐Furnols may publish in the future.

Co-authorship network of co-authors of Maria Font‐i‐Furnols

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Font‐i‐Furnols. A scholar is included among the top collaborators of Maria Font‐i‐Furnols 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 Maria Font‐i‐Furnols. Maria Font‐i‐Furnols is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Afseth, Nils Kristian, et al.. (2025). Discrimination of normal and wooden breast chicken fillets using NIR, fluorescence and Raman spectroscopy. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 343. 126463–126463.
2.
Zomeño, Cristina, et al.. (2024). The role of carcass processing (hot vs. cold boning) on pork belly morphological and mechanical characteristics. Meat Science. 218. 109632–109632. 2 indexed citations
3.
Font‐i‐Furnols, Maria & Luís Guerrero. (2024). An overview of drivers and emotions of meat consumption. Meat Science. 219. 109619–109619. 8 indexed citations
4.
Mishra, Puneet & Maria Font‐i‐Furnols. (2024). X‐Ray Computed Tomography Meets Robust Chemometric Latent Space Modeling for Lean Meat Percentage Prediction in Pig Carcasses. Journal of Chemometrics. 38(10). 1 indexed citations
6.
Font‐i‐Furnols, Maria, et al.. (2023). The effect of immunocastration of male and female Duroc pigs on the morphological, mechanical and compositional characteristics of pork belly. Meat Science. 204. 109263–109263. 10 indexed citations
7.
Font‐i‐Furnols, Maria, Anna Claret, Luís Guerrero, & Antoni Dalmau. (2022). Consumers’ Expectations about Meat from Surgical Castrated or Immunocastrated Male and Female Iberian Pigs. Animals. 12(4). 468–468. 4 indexed citations
8.
Zomeño, Cristina, M. Gispert, Marjeta Čandek‐Potokar, Daniel Mörlein, & Maria Font‐i‐Furnols. (2022). A matter of body weight and sex type: Pig carcass chemical composition and pork quality. Meat Science. 197. 109077–109077. 15 indexed citations
9.
10.
Blanco–Penedo, Isabel, et al.. (2021). Exploring Sustainable Food Choices Factors and Purchasing Behavior in the Sustainable Development Goals Era in Spain. Sustainability. 13(13). 7397–7397. 17 indexed citations
11.
Škrlep, Martin, Igor Tomašević, Daniel Mörlein, et al.. (2020). The Use of Pork from Entire Male and Immunocastrated Pigs for Meat Products—An Overview with Recommendations. Animals. 10(10). 1754–1754. 41 indexed citations
12.
Tomašević, Igor, Jaroslav Čítek, Marjeta Čandek‐Potokar, et al.. (2020). Attitudes and Beliefs of Eastern European Consumers Towards Animal Welfare. Animals. 10(7). 1220–1220. 25 indexed citations
13.
Čandek‐Potokar, Marjeta, et al.. (2019). Acceptability of Dry-Cured Belly (Pancetta) from Entire Males, Immunocastrates or Surgical Castrates: Study with Slovenian Consumers. Foods. 8(4). 122–122. 7 indexed citations
14.
Font‐i‐Furnols, Maria, Margit Dall Aaslyng, G.B.C. Backus, et al.. (2016). Russian and Chinese consumers' acceptability of boar meat patties depending on their sensitivity to androstenone and skatole. Meat Science. 121. 96–103. 11 indexed citations
15.
Kallas, Zein, José María Gil Roig, Marta Blanch, et al.. (2013). Effect of tasting and information on consumer opinion about pig castration. Meat Science. 95(2). 242–249. 20 indexed citations
16.
Font‐i‐Furnols, Maria, et al.. (2011). Determinación del porcentaje de grasa intramuscular en lomo de cerdo mediante métodos químicos y métodos no invasivos.. 70–77. 2 indexed citations
17.
Font‐i‐Furnols, Maria. (2009). Efecto de la inmunocastración de cerdos en las características de calidad de canal y carne, los niveles de androstenona y escatol y la composición en ácidos grasos. 60–68. 2 indexed citations
18.
Font‐i‐Furnols, Maria. (2008). La tomografía computerizada como herramienta para la determinación de la composición de la canal. 114–122. 1 indexed citations
19.
Font‐i‐Furnols, Maria, et al.. (2007). Evolución y situación de la cabaña porcina española. 51–62. 4 indexed citations
20.
Spindler, Michael, C. Sañudo, R. San Julián, et al.. (2006). Verbraucherakzeptanz von uruguayischem und deutschem Rind- und Lammfleisch. ˜Die œFleischwirtschaft. 86(8). 101–106.

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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