Daniel P. Martin

2.2k total citations
26 papers, 393 citations indexed

About

Daniel P. Martin is a scholar working on Plant Science, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Daniel P. Martin has authored 26 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Plant Science, 4 papers in Control and Systems Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Daniel P. Martin's work include Plant Physiology and Cultivation Studies (10 papers), Postharvest Quality and Shelf Life Management (6 papers) and Fault Detection and Control Systems (4 papers). Daniel P. Martin is often cited by papers focused on Plant Physiology and Cultivation Studies (10 papers), Postharvest Quality and Shelf Life Management (6 papers) and Fault Detection and Control Systems (4 papers). Daniel P. Martin collaborates with scholars based in United States, Australia and Germany. Daniel P. Martin's co-authors include Sara E. Rimm‐Kaufman, J. Černý, David A. Ratkowsky, Timo von Oertzen, Mark A. LaPack, Randy J. Pell, Jerome Workman, Kenneth R. Beebe, Elisabeth Oswald and Martijn Stam and has published in prestigious journals such as Analytical Chemistry, Structural Equation Modeling A Multidisciplinary Journal and Journal of School Psychology.

In The Last Decade

Daniel P. Martin

23 papers receiving 355 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel P. Martin United States 10 98 91 60 47 37 26 393
Youssef Es-Saady Morocco 12 232 2.4× 22 0.2× 93 1.6× 20 0.4× 10 0.3× 32 558
Jayoung Lee South Korea 10 48 0.5× 25 0.3× 36 0.6× 51 1.1× 10 0.3× 26 286
Lele Wang China 7 73 0.7× 173 1.9× 23 0.4× 25 0.5× 68 1.8× 20 533
Eeke van der Burg Netherlands 8 9 0.1× 100 1.1× 45 0.8× 24 0.5× 50 1.4× 13 340
Enio Galinkin Jelihovschi Brazil 10 47 0.5× 93 1.0× 5 0.1× 17 0.4× 48 1.3× 17 354
Xinyu He China 8 68 0.7× 32 0.4× 14 0.2× 6 0.1× 6 0.2× 41 230
Karin Binder Germany 11 25 0.3× 100 1.1× 5 0.1× 16 0.3× 33 0.9× 26 318
Tomohiro Masuda Japan 12 67 0.7× 3 0.0× 15 0.3× 102 2.2× 108 2.9× 29 389
Fernando Flores-Camacho Mexico 10 29 0.3× 218 2.4× 2 0.0× 70 1.5× 26 0.7× 42 405
J. Lingoes United States 3 15 0.2× 10 0.1× 4 0.1× 70 1.5× 23 0.6× 4 365

Countries citing papers authored by Daniel P. Martin

Since Specialization
Citations

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

Fields of papers citing papers by Daniel P. Martin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel P. Martin. 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 Daniel P. Martin. The network helps show where Daniel P. Martin may publish in the future.

Co-authorship network of co-authors of Daniel P. Martin

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel P. Martin. A scholar is included among the top collaborators of Daniel P. Martin 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 Daniel P. Martin. Daniel P. Martin 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.
Wilcock, William S. D., et al.. (2024). The Self‐Calibrating Tilt Accelerometer: A Method for Observing Tilt and Correcting Drift With a Triaxial Accelerometer. Earth and Space Science. 11(11). 1 indexed citations
2.
Estabrook, Ryne, et al.. (2021). Correcting the bias of the Root Mean Squared Error of Approximation under missing data. Methodology. 17(3). 189–204. 7 indexed citations
3.
4.
Wilcock, William S. D., et al.. (2018). Self-Calibrating Resonant Quartz Crystal Technology Sensors for Seafloor Geodesy and Oceanographic Applications. AGU Fall Meeting Abstracts. 2018. 1 indexed citations
5.
Estabrook, Ryne, et al.. (2018). Correcting the Bias of the Root Mean Squared Error of Approximation under Missing Data. Open Science Framework. 1 indexed citations
6.
Wilcock, William S. D., et al.. (2017). A Seafloor Test of the A-0-A Approach to Calibrating Pressure Sensors for Vertical Geodesy. AGU Fall Meeting Abstracts. 2017. 3 indexed citations
7.
Wang, Yan Ming, G. L. Mader, Daniel P. Martin, et al.. (2017). The Geoid Slope Validation Survey 2014 and GRAV-D airborne gravity enhanced geoid comparison results in Iowa. Journal of Geodesy. 91(10). 1261–1276. 21 indexed citations
8.
Martin, Daniel P. & Sara E. Rimm‐Kaufman. (2015). Do student self-efficacy and teacher-student interaction quality contribute to emotional and social engagement in fifth grade math?. Journal of School Psychology. 53(5). 359–373. 137 indexed citations
9.
Martin, Daniel P. & Timo von Oertzen. (2014). Growth Mixture Models Outperform Simpler Clustering Algorithms When Detecting Longitudinal Heterogeneity, Even With Small Sample Sizes. Structural Equation Modeling A Multidisciplinary Journal. 22(2). 264–275. 22 indexed citations
10.
Buehler, M., et al.. (2002). Test structures applied to the rapid prototyping of sensors. 212–217.
11.
Stewart, Mary E., et al.. (1998). TRACEABILITY AND THE CALIBRATION OF SATELLITE POSITIONING SYSTEMS. Survey Review. 34(269). 437–446.
12.
Beebe, Kenneth R., et al.. (1993). Process analytical chemistry. Analytical Chemistry. 65(12). 199–216. 41 indexed citations
13.
Martin, Daniel P.. (1990). Canonical variate analysis of large scale systems on a transputer array. 623–628 vol.2. 3 indexed citations
14.
Larimore, Wallace E., Daniel P. Martin, & Franklin T. Luk. (1989). A Transputer Implementation Of System Identification And Control Using SVD's. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1152. 108–108. 1 indexed citations
15.
16.
Martin, Daniel P., et al.. (1975). The Predominant Role of Calcium as an Indicator in Storage Disorders in Cleopatra Apples. Journal of Horticultural Science. 50(4). 447–455. 9 indexed citations
17.
Martin, Daniel P., et al.. (1973). Longitudinal distribution of applied calcium, and of naturally occurring calcium, magnesium, and potassium, in Merton apple fruits. Australian Journal of Agricultural Research. 24(3). 363–371. 28 indexed citations
18.
Martin, Daniel P., et al.. (1965). The interrelation of susceptibility to breakdown, cell size, and nitrogen and phosphorus levels in Jonathan apple fruits. Australian Journal of Agricultural Research. 16(4). 617–625. 9 indexed citations
19.
Martin, Daniel P., et al.. (1960). Bitter pit in the apple variety Cleopatra in Tasmania in relation to calcium and magnesium.. Australian Journal of Agricultural and Resource Economics. 2(5). 2 indexed citations
20.
Martin, Daniel P., et al.. (1960). Bitter pit in the apple variety Cleopatra in Tasmania in relation to calcium and magnesium. Australian Journal of Agricultural Research. 11(5). 742–749. 13 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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