Jorge Cadima

9.9k total citations · 1 hit paper
22 papers, 6.5k citations indexed

About

Jorge Cadima is a scholar working on Food Science, Plant Science and Agronomy and Crop Science. According to data from OpenAlex, Jorge Cadima has authored 22 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Food Science, 8 papers in Plant Science and 6 papers in Agronomy and Crop Science. Recurrent topics in Jorge Cadima's work include Sensory Analysis and Statistical Methods (6 papers), Spectroscopy and Chemometric Analyses (6 papers) and Seed Germination and Physiology (4 papers). Jorge Cadima is often cited by papers focused on Sensory Analysis and Statistical Methods (6 papers), Spectroscopy and Chemometric Analyses (6 papers) and Seed Germination and Physiology (4 papers). Jorge Cadima collaborates with scholars based in Portugal, United Kingdom and United States. Jorge Cadima's co-authors include Ian T. Jolliffe, Jorge Orestes Cerdeira, L. S. Pereira, Carlos Pires, Diogo Martins, Paula Paredes, João M. N. Silva, Jean‐Marie Grégoire, José M. C. Pereira and Tayeb Raziei and has published in prestigious journals such as Biometrics, International Journal of Remote Sensing and Theoretical and Applied Genetics.

In The Last Decade

Jorge Cadima

21 papers receiving 6.4k citations

Hit Papers

Principal component analysis: a review and recent develop... 2016 2026 2019 2022 2016 1000 2.0k 3.0k 4.0k 5.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jorge Cadima Portugal 11 780 757 580 500 476 22 6.5k
Lynne J. Williams Canada 14 892 1.1× 1.2k 1.5× 668 1.2× 421 0.8× 571 1.2× 24 9.3k
Andrea Johnson United States 4 593 0.8× 1.1k 1.5× 337 0.6× 448 0.9× 394 0.8× 6 8.8k
David C. Hoaglin United States 47 655 0.8× 1.3k 1.7× 388 0.7× 517 1.0× 213 0.4× 165 15.5k
Roy E. Welsch United States 30 379 0.5× 1.2k 1.6× 331 0.6× 441 0.9× 419 0.9× 115 11.9k
Werner A. Stahel Switzerland 32 352 0.5× 897 1.2× 549 0.9× 486 1.0× 306 0.6× 86 9.2k
Mark Kramer United States 46 664 0.9× 1.2k 1.6× 406 0.7× 240 0.5× 389 0.8× 250 10.7k
Kjell Johnson United States 16 567 0.7× 948 1.3× 322 0.6× 419 0.8× 192 0.4× 39 5.8k
Leonard Kaufman Belgium 22 1.1k 1.4× 2.1k 2.8× 297 0.5× 498 1.0× 327 0.7× 60 9.3k
Paul D. Sampson United States 63 743 1.0× 622 0.8× 335 0.6× 828 1.7× 204 0.4× 155 15.6k
Zigang Lu China 6 522 0.7× 2.1k 2.8× 423 0.7× 442 0.9× 266 0.6× 17 8.8k

Countries citing papers authored by Jorge Cadima

Since Specialization
Citations

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

Fields of papers citing papers by Jorge Cadima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jorge Cadima. 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 Jorge Cadima. The network helps show where Jorge Cadima may publish in the future.

Co-authorship network of co-authors of Jorge Cadima

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge Cadima. A scholar is included among the top collaborators of Jorge Cadima 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 Jorge Cadima. Jorge Cadima 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.
Cadima, Jorge, et al.. (2025). Integer programming as a powerful tool for polyclonal selection in ancient grapevine varieties. Theoretical and Applied Genetics. 138(6). 122–122. 1 indexed citations
3.
Ribeiro, Henrique, et al.. (2021). Mechanical Pruning and Soil Organic Amending in Two Terroirs. Effects on Wine Chemical Composition and Sensory Profile. American Journal of Enology and Viticulture. 73(1). 26–38. 2 indexed citations
4.
Cerdeira, Jorge Orestes, et al.. (2020). Selecting Variable Subsets [R package subselect version 0.15.2]. 1 indexed citations
5.
Cadima, Jorge, et al.. (2020). Seed loss of bean and maize varieties as a function of temperature and irrigation levels. IOP Conference Series Earth and Environmental Science. 594(1). 12033–12033. 1 indexed citations
6.
Cadima, Jorge, et al.. (2019). Optimizing germination of seven Mediterranean crops. Journal of Crop Improvement. 34(2). 164–189.
7.
Cadima, Jorge, et al.. (2019). Modeling the spread of germination of four Mediterranean crops at different temperatures. Journal of Crop Improvement. 33(6). 730–754. 1 indexed citations
8.
Paredes, Paula, Diogo Martins, L. S. Pereira, Jorge Cadima, & Carlos Pires. (2018). Accuracy of daily estimation of grass reference evapotranspiration using ERA-Interim reanalysis products with assessment of alternative bias correction schemes. Agricultural Water Management. 210. 340–353. 54 indexed citations
9.
Cadima, Jorge, et al.. (2018). Modeling germination rate and cardinal temperatures of seven mediterranean crops. Journal of Crop Improvement. 32(6). 878–902. 9 indexed citations
10.
Jolliffe, Ian T. & Jorge Cadima. (2016). Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 374(2065). 20150202–20150202. 5828 indexed citations breakdown →
11.
Martins, Isabel P., et al.. (2012). Modeling target volume flows in forest harvest scheduling subject to maximum area restrictions. Top. 22(1). 343–362. 17 indexed citations
12.
Cadima, Jorge, et al.. (2011). Nutritive value of Cistus salvifolius shrubs for small ruminants. Animal Feed Science and Technology. 165(3-4). 167–175. 7 indexed citations
13.
Cadima, Jorge, et al.. (2010). Predicting degradability parameters of diets for ruminants using regressions on chemical components. Journal of the Science of Food and Agriculture. 90(6). 949–955. 3 indexed citations
14.
Cadima, Jorge, et al.. (2010). The eigenstructure of block-structured correlation matrices and its implications for principal component analysis. Journal of Applied Statistics. 37(4). 577–589. 6 indexed citations
15.
Cadima, Jorge & Ian T. Jolliffe. (2009). ON RELATIONSHIPS BETWEEN UNCENTRED AND COLUMN-CENTRED PRINCIPAL COMPONENT ANALYSIS. 40 indexed citations
16.
Silva, A. Pedro Duarte, et al.. (2006). Subselect 0.9-99: Selecting variable subsets in multivariate linear models. 14 indexed citations
17.
Cadima, Jorge, et al.. (2003). Computational aspects of algorithms for variable selection in the context of principal components. Computational Statistics & Data Analysis. 47(2). 225–236. 130 indexed citations
18.
Cadima, Jorge & Ian T. Jolliffe. (2001). Variable selection and the interpretation of principal subspaces. Journal of Agricultural Biological and Environmental Statistics. 6(1). 62–79. 67 indexed citations
19.
Cadima, Jorge & Ian T. Jolliffe. (1996). Size- and Shape-Related Principal Component Analysis. Biometrics. 52(2). 710–710. 37 indexed citations
20.
Cadima, Jorge & Ian T. Jolliffe. (1995). Loading and correlations in the interpretation of principle compenents. Journal of Applied Statistics. 22(2). 203–214. 229 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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