Lorena González-Pérez

1.4k total citations · 1 hit paper
12 papers, 1.0k citations indexed

About

Lorena González-Pérez is a scholar working on Plant Science, Ecology and Genetics. According to data from OpenAlex, Lorena González-Pérez has authored 12 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Plant Science, 6 papers in Ecology and 6 papers in Genetics. Recurrent topics in Lorena González-Pérez's work include Genetics and Plant Breeding (6 papers), Remote Sensing in Agriculture (6 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). Lorena González-Pérez is often cited by papers focused on Genetics and Plant Breeding (6 papers), Remote Sensing in Agriculture (6 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). Lorena González-Pérez collaborates with scholars based in Mexico, United States and Argentina. Lorena González-Pérez's co-authors include Suchismita Mondal, Jessica Rutkoski, José Crossa, Ravi P. Singh, Jesse Poland, Matthew Reynolds, Enrique Autrique, Osval A. Montesinos‐López, Juan Burgueño and Abelardo Montesinos‐López and has published in prestigious journals such as PLoS ONE, Frontiers in Plant Science and Theoretical and Applied Genetics.

In The Last Decade

Lorena González-Pérez

12 papers receiving 983 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

2016 281 citations Jessica Rutkoski, Jesse Poland et al. G3 Genes Genomes Genetics profile →

Peers

Lorena González-Pérez

GENET

ECOLO

John T. Heun United States

Duke Pauli United States

Barbara George‐Jaeggli Australia

Katy Martin Rainey United States

José A. Fernandez-Gallego Colombia

Adrian Gracia‐Romero Spain

Shaokun Li China

Vincent Stoerger United States

Yongdun Xie China

John T. Heun United States

Lorena González-Pérez

716 ×0.9

203 ×0.4

GENET

380 ×0.9

ECOLO

137 ×1.0

61 ×0.5

Citations per year, relative to Lorena González-Pérez Lorena González-Pérez (= 1×) peers John T. Heun

Countries citing papers authored by Lorena González-Pérez

Since Specialization

Citations

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

Fields of papers citing papers by Lorena González-Pérez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lorena González-Pérez. 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 Lorena González-Pérez. The network helps show where Lorena González-Pérez may publish in the future.

Co-authorship network of co-authors of Lorena González-Pérez

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

All Works

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12 of 12 papers shown

González-Pérez, Lorena, et al.. (2022). QTL and genomic prediction accuracy for grain yield and secondary traits in a maize population under heat and heat-drought stresses. Journal of Crop Improvement. 37(5). 709–734. 3 indexed citations

Pinto, Francisco, Lorena González-Pérez, Aluízio Borém, et al.. (2021). High Throughput Field Phenotyping for Plant Height Using UAV-Based RGB Imagery in Wheat Breeding Lines: Feasibility and Validation. Frontiers in Plant Science. 12. 591587–591587. 77 indexed citations

Ortiz‐Monasterio, Iván, et al.. (2021). High-Resolution Airborne Hyperspectral Imagery for Assessing Yield, Biomass, Grain N Concentration, and N Output in Spring Wheat. Remote Sensing. 13(7). 1373–1373. 16 indexed citations

González-Pérez, Lorena, José Crossa, Paulino Pérez‐Rodríguez, et al.. (2019). Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat. G3 Genes Genomes Genetics. 9(4). 1231–1247. 107 indexed citations

Trachsel, Samuel, et al.. (2019). Estimation of physiological genomic estimated breeding values (PGEBV) combining full hyperspectral and marker data across environments for grain yield under combined heat and drought stress in tropical maize (Zea mays L.). PLoS ONE. 14(3). e0212200–e0212200. 18 indexed citations

Juliana, Philomin, Osval A. Montesinos‐López, José Crossa, et al.. (2018). Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat. Theoretical and Applied Genetics. 132(1). 177–194. 65 indexed citations

Montesinos‐López, Abelardo, Osval A. Montesinos‐López, Jaime Cuevas, et al.. (2017). Genomic Bayesian functional regression models with interactions for predicting wheat grain yield using hyper-spectral image data. Plant Methods. 13(1). 62–62. 67 indexed citations

Montesinos‐López, Osval A., Abelardo Montesinos‐López, José Crossa, et al.. (2017). Predicting grain yield using canopy hyperspectral reflectance in wheat breeding data. Plant Methods. 13(1). 4–4. 121 indexed citations

Trachsel, Samuel, Lorena González-Pérez, Juan Burgueño, et al.. (2017). Use of Hyperspectral Image Data Outperforms Vegetation Indices in Prediction of Maize Yield. Crop Science. 57(5). 2517–2524. 62 indexed citations

10.

Cerrudo, Diego, et al.. (2017). Stay-Green and Associated Vegetative Indices to Breed Maize Adapted to Heat and Combined Heat-Drought Stresses. Remote Sensing. 9(3). 235–235. 13 indexed citations

11.

Haghighattalab, Atena, Lorena González-Pérez, Suchismita Mondal, et al.. (2016). Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries. Plant Methods. 12(1). 35–35. 174 indexed citations

12.

Rutkoski, Jessica, Jesse Poland, Suchismita Mondal, et al.. (2016). Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat. G3 Genes Genomes Genetics. 6(9). 2799–2808. 281 indexed citations breakdown →

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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