Margit Dall Aaslyng

4.7k total citations
86 papers, 3.5k citations indexed

About

Margit Dall Aaslyng is a scholar working on Animal Science and Zoology, Food Science and Small Animals. According to data from OpenAlex, Margit Dall Aaslyng has authored 86 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Animal Science and Zoology, 36 papers in Food Science and 17 papers in Small Animals. Recurrent topics in Margit Dall Aaslyng's work include Meat and Animal Product Quality (65 papers), Animal Nutrition and Physiology (26 papers) and Sensory Analysis and Statistical Methods (19 papers). Margit Dall Aaslyng is often cited by papers focused on Meat and Animal Product Quality (65 papers), Animal Nutrition and Physiology (26 papers) and Sensory Analysis and Statistical Methods (19 papers). Margit Dall Aaslyng collaborates with scholars based in Denmark, United Kingdom and Belgium. Margit Dall Aaslyng's co-authors include Lene Meinert, Hanne Christine Bertram, C. Bejerholm, Henrik J. Andersen, Per Ertbjerg, Wender L.P. Bredie, Anette Granly Koch, Mette Christensen, Kaja Tikk and Line Bach Christensen and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Food Chemistry and Journal of Nutrition.

In The Last Decade

Margit Dall Aaslyng

83 papers receiving 3.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Margit Dall Aaslyng Denmark 34 2.5k 1.3k 593 561 556 86 3.5k
Chris R. Calkins United States 32 3.5k 1.4× 1.2k 0.9× 668 1.1× 546 1.0× 437 0.8× 189 4.5k
R. K. Miller United States 44 4.5k 1.8× 2.0k 1.5× 636 1.1× 522 0.9× 670 1.2× 179 5.7k
José Antonio Beltrán Spain 40 3.6k 1.4× 1.6k 1.2× 703 1.2× 696 1.2× 422 0.8× 108 4.8k
P.J. Shand Canada 33 2.2k 0.9× 1.5k 1.2× 828 1.4× 195 0.3× 625 1.1× 101 3.7k
D.J. Troy Ireland 37 3.5k 1.4× 1.5k 1.2× 826 1.4× 348 0.6× 665 1.2× 94 4.6k
Awis Qurni Sazili Malaysia 37 2.6k 1.0× 980 0.8× 1.2k 2.0× 419 0.7× 516 0.9× 192 4.6k
J.L. Aalhus Canada 39 4.2k 1.7× 792 0.6× 917 1.5× 552 1.0× 1.3k 2.4× 216 5.9k
C. Sañudo Spain 48 5.2k 2.0× 1.4k 1.1× 480 0.8× 406 0.7× 480 0.9× 152 6.2k
C.E. Realini Spain 31 2.0k 0.8× 736 0.6× 335 0.6× 392 0.7× 365 0.7× 88 3.2k
Pedro Roncalés Spain 39 3.3k 1.3× 1.8k 1.4× 658 1.1× 665 1.2× 411 0.7× 89 4.6k

Countries citing papers authored by Margit Dall Aaslyng

Since Specialization
Citations

This map shows the geographic impact of Margit Dall Aaslyng'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 Margit Dall Aaslyng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Margit Dall Aaslyng more than expected).

Fields of papers citing papers by Margit Dall Aaslyng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margit Dall Aaslyng. 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 Margit Dall Aaslyng. The network helps show where Margit Dall Aaslyng may publish in the future.

Co-authorship network of co-authors of Margit Dall Aaslyng

This figure shows the co-authorship network connecting the top 25 collaborators of Margit Dall Aaslyng. A scholar is included among the top collaborators of Margit Dall Aaslyng 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 Margit Dall Aaslyng. Margit Dall Aaslyng 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.
2.
Aaslyng, Margit Dall, et al.. (2023). Protein content and amino acid composition in the diet of Danish vegans: a cross-sectional study. BMC Nutrition. 9(1). 131–131. 9 indexed citations
3.
Christensen, Lars Bager, et al.. (2019). Physico‐chemical, orosensory and microstructural properties of meat products containing rye bran, pea fibre or a combination of the two. International Journal of Food Science & Technology. 55(3). 1010–1017. 6 indexed citations
4.
5.
Aaslyng, Margit Dall & Lene Meinert. (2017). Meat flavour in pork and beef – From animal to meal. Meat Science. 132. 112–117. 180 indexed citations
6.
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
7.
Aaslyng, Margit Dall, et al.. (2016). Meatballs with 3% and 6% dietary fibre from rye bran or pea fibre ‐ Effects on sensory quality and subjective appetite sensations. Meat Science. 125. 66–75. 46 indexed citations
8.
Aaslyng, Margit Dall, et al.. (2015). The effect of skatole and androstenone on consumer response towards streaky bacon and pork belly roll. Meat Science. 110. 52–61. 26 indexed citations
9.
Straadt, Ida Krestine, Margit Dall Aaslyng, & Hanne Christine Bertram. (2013). An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception. Meat Science. 96(2). 719–728. 54 indexed citations
10.
Meinert, Lene, et al.. (2012). Consuming pork proteins at breakfast reduces the feeling of hunger before lunch. Appetite. 59(2). 201–203. 9 indexed citations
11.
Aaslyng, Margit Dall, Lene Duedahl‐Olesen, Kirsten Jensen, & Lene Meinert. (2012). Content of heterocyclic amines and polycyclic aromatic hydrocarbons in pork, beef and chicken barbecued at home by Danish consumers. Meat Science. 93(1). 85–91. 88 indexed citations
12.
Christensen, Line Bach, Per Ertbjerg, Margit Dall Aaslyng, & Mette Christensen. (2011). Effect of prolonged heat treatment from 48°C to 63°C on toughness, cooking loss and color of pork. Meat Science. 88(2). 280–285. 120 indexed citations
13.
Straadt, Ida Krestine, Margit Dall Aaslyng, & Hanne Christine Bertram. (2011). Assessment of meat quality by NMR—an investigation of pork products originating from different breeds. Magnetic Resonance in Chemistry. 49(S1). S71–8. 28 indexed citations
14.
Aaslyng, Margit Dall & Michael Bom Frøst. (2010). THE EFFECT OF THE COMBINATION OF SALTY, BITTER AND SOUR ACCOMPANIMENT ON THE FLAVOR AND JUICINESS OF PORK PATTIES. Journal of Sensory Studies. 25(4). 536–548. 17 indexed citations
15.
Aaslyng, Margit Dall, et al.. (2010). Scandinavian consumer preference for beef steaks packed with or without oxygen. Meat Science. 85(3). 519–524. 27 indexed citations
16.
Tikk, Kaja, John‐Erik Haugen, Henrik J. Andersen, & Margit Dall Aaslyng. (2008). Monitoring of warmed-over flavour in pork using the electronic nose – correlation to sensory attributes and secondary lipid oxidation products. Meat Science. 80(4). 1254–1263. 74 indexed citations
17.
Reinbach, Helene Christine, Lene Meinert, Davide Ballabio, et al.. (2007). Interactions between oral burn, meat flavor and texture in chili spiced pork patties evaluated by time-intensity. Food Quality and Preference. 18(6). 909–919. 36 indexed citations
18.
Bertram, Hanne Christine, et al.. (2007). Relationship between water mobility and distribution and sensory attributes in pork slaughtered at an age between 90 and 180 days. Meat Science. 77(2). 190–195. 36 indexed citations
19.
Bertram, Hanne Christine, Margit Dall Aaslyng, & Henrik J. Andersen. (2005). Elucidation of the relationship between cooking temperature, water distribution and sensory attributes of pork – a combined NMR and sensory study. Meat Science. 70(1). 75–81. 71 indexed citations
20.
Aaslyng, Margit Dall, et al.. (2004). Sensory and instrumental analysis of longitudinal and transverse textural variation in pork longissimus dorsi. Meat Science. 68(4). 611–629. 19 indexed citations

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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