B. Sams

606 total citations
13 papers, 376 citations indexed

About

B. Sams is a scholar working on Plant Science, Ecology and Environmental Engineering. According to data from OpenAlex, B. Sams has authored 13 papers receiving a total of 376 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Plant Science, 6 papers in Ecology and 4 papers in Environmental Engineering. Recurrent topics in B. Sams's work include Horticultural and Viticultural Research (7 papers), Smart Agriculture and AI (6 papers) and Remote Sensing in Agriculture (6 papers). B. Sams is often cited by papers focused on Horticultural and Viticultural Research (7 papers), Smart Agriculture and AI (6 papers) and Remote Sensing in Agriculture (6 papers). B. Sams collaborates with scholars based in United States, Australia and United Kingdom. B. Sams's co-authors include Luis Sánchez, Nick Dokoozlian, María Mar Alsina, David Walker, Carolyn A. Copenheaver, William P. Kustas, Martha C. Anderson, W. Dulaney, Forrest Melton and Feng Gao and has published in prestigious journals such as Remote Sensing, IEEE Internet of Things Journal and Computers and Electronics in Agriculture.

In The Last Decade

B. Sams

12 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
B. Sams United States 8 216 144 91 73 52 13 376
Justin Sexton Australia 10 316 1.5× 94 0.7× 72 0.8× 49 0.7× 5 0.1× 25 463
Aikaterini Kasimati Greece 12 222 1.0× 114 0.8× 23 0.3× 50 0.7× 2 0.0× 23 407
Peter Dahlhaus Australia 12 61 0.3× 38 0.3× 36 0.4× 97 1.3× 3 0.1× 36 353
Evangelos Anastasiou Greece 13 262 1.2× 178 1.2× 43 0.5× 80 1.1× 25 452
Tulsi P. Kharel United States 13 190 0.9× 166 1.2× 48 0.5× 115 1.6× 36 402
Yannick Curnel Belgium 11 139 0.6× 187 1.3× 124 1.4× 82 1.1× 17 354
Francelino A. Rodrigues Mexico 12 263 1.2× 204 1.4× 52 0.6× 144 2.0× 28 447
V. Liakos Greece 11 286 1.3× 106 0.7× 65 0.7× 101 1.4× 22 472
Vivekananda M. Byrareddy Australia 9 169 0.8× 69 0.5× 75 0.8× 25 0.3× 17 535
Hildo Loayza Peru 10 184 0.9× 105 0.7× 54 0.6× 31 0.4× 19 271

Countries citing papers authored by B. Sams

Since Specialization
Citations

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

Fields of papers citing papers by B. Sams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of B. Sams

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

All Works

13 of 13 papers shown
1.
Kamangir, Hamid, et al.. (2025). Predicting crop yield lows through the highs via binned deep imbalanced regression: A case study on vineyards. International Journal of Applied Earth Observation and Geoinformation. 139. 104536–104536.
2.
Kamangir, Hamid, et al.. (2023). Large-scale spatio-temporal yield estimation via deep learning using satellite and management data fusion in vineyards. Computers and Electronics in Agriculture. 216. 108439–108439. 13 indexed citations
3.
4.
Sams, B., et al.. (2022). End-to-end deep learning for directly estimating grape yield from ground-based imagery. Computers and Electronics in Agriculture. 198. 107081–107081. 27 indexed citations
5.
Sams, B., R. G. V. Bramley, Luis Sánchez, et al.. (2022). Characterising spatio‐temporal variation in fruit composition for improved winegrowing management in California Cabernet Sauvignon. Australian Journal of Grape and Wine Research. 28(3). 407–423. 3 indexed citations
6.
Sams, B., R. G. V. Bramley, Luis Sánchez, et al.. (2022). Remote Sensing, Yield, Physical Characteristics, and Fruit Composition Variability in Cabernet Sauvignon Vineyards. American Journal of Enology and Viticulture. 73(2). 93–105. 16 indexed citations
7.
Sams, B., R. G. V. Bramley, Vinay Pagay, et al.. (2019). Can mapping of within-vineyard variability be facilitated using data from multiple vineyards?. 743–749. 1 indexed citations
8.
Klein, Levente J., Hendrik F. Hamann, Supratik Guha, et al.. (2018). Closed Loop Controlled Precision Irrigation Sensor Network. IEEE Internet of Things Journal. 5(6). 4580–4588. 34 indexed citations
9.
Sams, B., et al.. (2017). Two methods for processing yield maps from multiple sensors in large vineyards in California. Advances in Animal Biosciences. 8(2). 530–533. 5 indexed citations
10.
Sun, Liang, Feng Gao, Martha C. Anderson, et al.. (2017). Daily Mapping of 30 m LAI and NDVI for Grape Yield Prediction in California Vineyards. Remote Sensing. 9(4). 317–317. 142 indexed citations
11.
Sams, B., et al.. (2017). Improving vineyard water use efficiency and yield with variable rate irrigation in California. Advances in Animal Biosciences. 8(2). 574–577. 31 indexed citations
12.
Taylor, James A., et al.. (2016). Evaluation of a commercial grape yield monitor for use mid-season and at-harvest. OENO One. 50(2). 18 indexed citations
13.
Sams, B., et al.. (2011). Citation pattern and lifespan: a comparison of discipline, institution, and individual. Scientometrics. 89(3). 955–966. 84 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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2026