Luis Díaz‐García

945 total citations
40 papers, 540 citations indexed

About

Luis Díaz‐García is a scholar working on Plant Science, Cell Biology and Genetics. According to data from OpenAlex, Luis Díaz‐García has authored 40 papers receiving a total of 540 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Plant Science, 14 papers in Cell Biology and 12 papers in Genetics. Recurrent topics in Luis Díaz‐García's work include Plant Pathogens and Fungal Diseases (14 papers), Berry genetics and cultivation research (13 papers) and Horticultural and Viticultural Research (12 papers). Luis Díaz‐García is often cited by papers focused on Plant Pathogens and Fungal Diseases (14 papers), Berry genetics and cultivation research (13 papers) and Horticultural and Viticultural Research (12 papers). Luis Díaz‐García collaborates with scholars based in United States, Mexico and Canada. Luis Díaz‐García's co-authors include Juan Zalapa, Brandon Schlautman, Giovanny Covarrubias‐Pazaran, Nicholi Vorsa, Massimo Iorizzo, Pablo González‐Barrios, Lucı́a Gutiérrez, Shawn A. Steffan, James Polashock and Jennifer Johnson‐Cicalese and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Frontiers in Plant Science.

In The Last Decade

Luis Díaz‐García

39 papers receiving 535 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Luis Díaz‐García United States 16 373 179 124 107 76 40 540
L.J. Grauke United States 13 440 1.2× 85 0.5× 85 0.7× 118 1.1× 96 1.3× 75 672
Emily Telfer New Zealand 13 182 0.5× 233 1.3× 59 0.5× 138 1.3× 52 0.7× 25 506
Annika Djurle Sweden 17 791 2.1× 112 0.6× 163 1.3× 170 1.6× 105 1.4× 30 887
Brandon Schlautman United States 19 485 1.3× 136 0.8× 161 1.3× 156 1.5× 54 0.7× 40 677
Ivan Pejić Croatia 14 440 1.2× 73 0.4× 69 0.6× 110 1.0× 60 0.8× 66 550
Patrick Vallée France 13 479 1.3× 113 0.6× 53 0.4× 232 2.2× 57 0.8× 17 597
Sara Pinosio Italy 12 420 1.1× 267 1.5× 50 0.4× 298 2.8× 42 0.6× 20 669
Jerzy H. Czembor Poland 14 785 2.1× 126 0.7× 87 0.7× 117 1.1× 56 0.7× 74 837
Richard D. Cuthbert Canada 20 959 2.6× 295 1.6× 106 0.9× 102 1.0× 49 0.6× 81 1.0k
Márcio Vinícius de Carvalho Barros Côrtes Brazil 12 384 1.0× 64 0.4× 117 0.9× 120 1.1× 83 1.1× 33 528

Countries citing papers authored by Luis Díaz‐García

Since Specialization
Citations

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

Fields of papers citing papers by Luis Díaz‐García

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luis Díaz‐García. 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 Luis Díaz‐García. The network helps show where Luis Díaz‐García may publish in the future.

Co-authorship network of co-authors of Luis Díaz‐García

This figure shows the co-authorship network connecting the top 25 collaborators of Luis Díaz‐García. A scholar is included among the top collaborators of Luis Díaz‐García 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 Luis Díaz‐García. Luis Díaz‐García 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.
Cochetel, Noé, José Muñóz, Ana Gaspar, et al.. (2025). The genetic basis of chloride exclusion in grapevines. G3 Genes Genomes Genetics. 15(9).
2.
Wiesner‐Hanks, Tyr, Andrew Maule, Luis Díaz‐García, et al.. (2024). BerryPortraits: Phenotyping Of Ripening Traits in cranberry (Vaccinium macrocarpon Ait.) with YOLOv8. Plant Methods. 20(1). 172–172. 2 indexed citations
3.
Díaz‐García, Luis, Diego Jarquín, Shinya Ikeda, et al.. (2024). Multiparametric Cranberry (Vaccinium macrocarpon Ait.) Fruit Textural Trait Development for Harvest and Postharvest Evaluation in Representative Cultivars. Journal of Texture Studies. 55(5). e12866–e12866. 2 indexed citations
4.
Maule, Andrew, Luis Díaz‐García, Jennifer Johnson‐Cicalese, et al.. (2024). Of buds and bits: a meta-QTL study identifies stable QTL for berry quality and yield traits in cranberry mapping populations (Vaccinium macrocarpon Ait.). Frontiers in Plant Science. 15. 1294570–1294570. 3 indexed citations
5.
Bhattarai, Krishna, et al.. (2024). Hyperspectral sensing for high‐throughput chloride detection in grapevines. SHILAP Revista de lepidopterología. 7(1). 2 indexed citations
6.
Lozoya-Saldaña, Héctor, et al.. (2024). Morphometric analysis of wild potato leaves. Genetic Resources and Crop Evolution. 71(8). 4533–4548. 2 indexed citations
7.
Díaz‐García, Luis, Mura Jyostna Devi, Shinya Ikeda, et al.. (2023). A Survey of Key Methods, Traits, Parameters, and Conditions for Measuring Texture in Cranberry (Vaccinium macrocarpon Ait.). Horticulturae. 9(4). 479–479. 5 indexed citations
8.
Li, Meng, Denise E. Costich, Jorge Nieto‐Sotelo, et al.. (2022). A B73×Palomero Toluqueño mapping population reveals local adaptation in Mexican highland maize. G3 Genes Genomes Genetics. 12(3). 7 indexed citations
9.
Schlautman, Brandon, et al.. (2021). Perennial groundcovers: an emerging technology for soil conservation and the sustainable intensification of agriculture. Emerging Topics in Life Sciences. 5(2). 337–347. 18 indexed citations
10.
Tassel, David L. Van, Lee R. DeHaan, Luis Díaz‐García, et al.. (2021). Re-imagining crop domestication in the era of high throughput phenomics. Current Opinion in Plant Biology. 65. 102150–102150. 16 indexed citations
11.
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13.
Díaz‐García, Luis, Brandon Schlautman, Giovanny Covarrubias‐Pazaran, et al.. (2018). Massive phenotyping of multiple cranberry populations reveals novel QTLs for fruit anthocyanin content and other important chemical traits. Molecular Genetics and Genomics. 293(6). 1379–1392. 25 indexed citations
14.
Singh, Vijay P., Juan Enciso, C. L. Munster, et al.. (2018). Spatio-temporal trends in monthly pan evaporation in Aguascalientes, Mexico. Theoretical and Applied Climatology. 136(1-2). 775–789. 11 indexed citations
15.
Schlautman, Brandon, Giovanny Covarrubias‐Pazaran, Luis Díaz‐García, et al.. (2017). Construction of a High-Density American Cranberry ( Vaccinium macrocarpon Ait.) Composite Map Using Genotyping-by-Sequencing for Multi-pedigree Linkage Mapping. G3 Genes Genomes Genetics. 7(4). 1177–1189. 22 indexed citations
16.
Schlautman, Brandon, Luis Díaz‐García, Giovanny Covarrubias‐Pazaran, et al.. (2017). Comparative genetic mapping reveals synteny and collinearity between the American cranberry and diploid blueberry genomes. Molecular Breeding. 38(1). 14 indexed citations
17.
Steffan, Shawn A., Prarthana S. Dharampal, Luis Díaz‐García, et al.. (2017). Empirical, Metagenomic, and Computational Techniques Illuminate the Mechanisms by which Fungicides Compromise Bee Health. Journal of Visualized Experiments. 19 indexed citations
18.
Díaz‐García, Luis, Giovanny Covarrubias‐Pazaran, Brandon Schlautman, & Juan Zalapa. (2016). GiNA, an Efficient and High-Throughput Software for Horticultural Phenotyping. PLoS ONE. 11(8). e0160439–e0160439. 18 indexed citations
19.
Covarrubias‐Pazaran, Giovanny, Luis Díaz‐García, Brandon Schlautman, et al.. (2016). Exploiting genotyping by sequencing to characterize the genomic structure of the American cranberry through high-density linkage mapping. BMC Genomics. 17(1). 451–451. 26 indexed citations
20.
Covarrubias‐Pazaran, Giovanny, Luis Díaz‐García, Brandon Schlautman, Walter Salazar, & Juan Zalapa. (2016). Fragman: an R package for fragment analysis. BMC Genetics. 17(1). 62–62. 42 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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