Luís G. Dias

4.2k total citations
94 papers, 3.2k citations indexed

About

Luís G. Dias is a scholar working on Biomedical Engineering, Food Science and Nutrition and Dietetics. According to data from OpenAlex, Luís G. Dias has authored 94 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Biomedical Engineering, 29 papers in Food Science and 28 papers in Nutrition and Dietetics. Recurrent topics in Luís G. Dias's work include Advanced Chemical Sensor Technologies (45 papers), Biochemical Analysis and Sensing Techniques (26 papers) and Bee Products Chemical Analysis (24 papers). Luís G. Dias is often cited by papers focused on Advanced Chemical Sensor Technologies (45 papers), Biochemical Analysis and Sensing Techniques (26 papers) and Bee Products Chemical Analysis (24 papers). Luís G. Dias collaborates with scholars based in Portugal, Spain and Brazil. Luís G. Dias's co-authors include Letı́cia M. Estevinho, António M. Peres, Leandro Moreira, José Alberto Pereira, Ana C. A. Veloso, Ana Paula Pereira, Ermelinda Pereira, Nuno Rodrigues, Susana I.L. Gomes and Paula Rodrigues and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Agricultural and Food Chemistry.

In The Last Decade

Luís G. Dias

93 papers receiving 3.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luís G. Dias Portugal 30 1.3k 1.1k 1.0k 504 499 94 3.2k
Ioannis K. Karabagias Greece 31 1.3k 1.1× 1.4k 1.2× 341 0.3× 591 1.2× 374 0.7× 122 3.1k
Abdalbasit Adam Mariod Sudan 34 410 0.3× 1.1k 1.0× 491 0.5× 717 1.4× 596 1.2× 155 3.7k
Peter Sporns Canada 29 404 0.3× 984 0.9× 320 0.3× 482 1.0× 651 1.3× 88 2.9k
Yang Shan China 31 308 0.2× 1.1k 1.0× 434 0.4× 368 0.7× 538 1.1× 124 2.9k
Ana I. Ruiz‐Matute Spain 25 448 0.4× 589 0.5× 323 0.3× 216 0.4× 538 1.1× 64 2.1k
Vibeke Orlien Denmark 35 386 0.3× 1.9k 1.6× 384 0.4× 836 1.7× 706 1.4× 82 4.1k
Mecit Halil Öztop Türkiye 35 219 0.2× 2.0k 1.7× 342 0.3× 271 0.5× 389 0.8× 173 3.6k
Gary A. Reineccius United States 39 369 0.3× 3.5k 3.1× 807 0.8× 394 0.8× 808 1.6× 175 5.1k
Renato Amadò Switzerland 37 379 0.3× 2.3k 2.0× 385 0.4× 408 0.8× 684 1.4× 93 4.5k
Giampiero Sacchetti Italy 39 285 0.2× 2.1k 1.9× 190 0.2× 712 1.4× 476 1.0× 109 4.1k

Countries citing papers authored by Luís G. Dias

Since Specialization
Citations

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

Fields of papers citing papers by Luís G. Dias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luís G. Dias. 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 Luís G. Dias. The network helps show where Luís G. Dias may publish in the future.

Co-authorship network of co-authors of Luís G. Dias

This figure shows the co-authorship network connecting the top 25 collaborators of Luís G. Dias. A scholar is included among the top collaborators of Luís G. Dias 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 Luís G. Dias. Luís G. Dias 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.
García-Hernández, Celia, et al.. (2024). Looking for the optimal harvest time of red grapes with an enzymatic electrochemical multisensory system. Journal of Agriculture and Food Research. 19. 101554–101554. 1 indexed citations
2.
Rodrigues, Sandra, Luís G. Dias, & A. Teixeira. (2024). Emerging Methods for the Evaluation of Sensory Quality of Food: Technology at Service. 2(1). 77–90. 25 indexed citations
3.
Paula, Vanessa, Luís G. Dias, & Letı́cia M. Estevinho. (2024). Microbiological and Physicochemical Evaluation of Hydroxypropyl Methylcellulose (HPMC) and Propolis Film Coatings for Cheese Preservation. Molecules. 29(9). 1941–1941. 3 indexed citations
4.
5.
Paula, Vanessa, et al.. (2024). Phenolic Class Analysis in Honey: Comparison of Classical and Single UV Spectrum Methodologies. Processes. 12(10). 2297–2297. 2 indexed citations
6.
Paula, Vanessa, Letı́cia M. Estevinho, Susana M. Cardoso, & Luís G. Dias. (2023). Comparative Methods to Evaluate the Antioxidant Capacity of Propolis: An Attempt to Explain the Differences. Molecules. 28(12). 4847–4847. 4 indexed citations
7.
Dias, Luís G., Ana Leite, Etelvina Pereira, et al.. (2023). SVM Regression to Assess Meat Characteristics of Bísaro Pig Loins Using NIRS Methodology. Foods. 12(3). 470–470. 12 indexed citations
8.
Dias, Luís G., Ana Leite, Etelvina Pereira, et al.. (2023). Can Near-Infrared Spectroscopy Replace a Panel of Tasters in Sensory Analysis of Dry-Cured Bísaro Loin?. Foods. 12(23). 4335–4335. 2 indexed citations
9.
Peres, António M., Letı́cia M. Estevinho, C. Garcı́a, et al.. (2022). Enose Lab Made with Vacuum Sampling: Quantitative Applications. Chemosensors. 10(7). 261–261. 8 indexed citations
10.
Dias, Luís G., Nuno Rodrigues, Ítala M.G. Marx, et al.. (2021). Application of a lab-made electronic nose for extra virgin olive oils commercial classification according to the perceived fruitiness intensity. Talanta. 226. 122122–122122. 40 indexed citations
11.
Rodrigues, Nuno, Ítala M.G. Marx, Luís G. Dias, et al.. (2020). Sweet peppers discrimination according to agronomic production mode and maturation stage using a chemical-sensory approach and an electronic tongue. Microchemical Journal. 157. 105034–105034. 17 indexed citations
12.
Garcı́a, C., Luís G. Dias, Coral Salvo‐Comino, et al.. (2020). Analysis of Phenolic Content in Grape Seeds and Skins by Means of a Bio-Electronic Tongue. Sensors. 20(15). 4176–4176. 12 indexed citations
13.
Marx, Ítala M.G., et al.. (2019). An electronic tongue as a classifier tool for assessing perfume olfactory family and storage time-period. Talanta. 208. 120364–120364. 4 indexed citations
14.
15.
Combarros‐Fuertes, Patricia, Rosa María Valencia‐Barrera, Letı́cia M. Estevinho, et al.. (2018). Spanish honeys with quality brand: a multivariate approach to physicochemical parameters, microbiological quality, and floral origin. Journal of Apicultural Research. 58(1). 92–103. 21 indexed citations
16.
Dias, Luís G., et al.. (2017). Electrochemical aptasensor for human osteopontin detection using a DNA aptamer selected by SELEX. Analytica Chimica Acta. 987. 25–37. 59 indexed citations
17.
Marx, Ítala M.G., Nuno Rodrigues, Luís G. Dias, et al.. (2016). Sensory classification of table olives using an electronic tongue: Analysis of aqueous pastes and brines. Talanta. 162. 98–106. 32 indexed citations
18.
Dias, Luís G., et al.. (2015). Development of an electrochemical RNA-aptasensor to detect human osteopontin. Biosensors and Bioelectronics. 71. 332–341. 31 indexed citations
19.
Sodré, Geni da Silva, et al.. (2015). Microbiological Assessment, Nutritional Characterization and Phenolic Compounds of Bee Pollen from Mellipona mandacaia Smith, 1983. Molecules. 20(7). 12525–12544. 41 indexed citations
20.
Iglesias, Antonio, Xesús Feás, Sandra Rodrigues, et al.. (2012). Comprehensive Study of Honey with Protected Denomination of Origin and Contribution to the Enhancement of Legal Specifications. Molecules. 17(7). 8561–8577. 45 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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