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José Crossa

Active 1990–2025

Also published as
Jose Crossa
227
Papers
30,290
Citations
102
h-index
212
i10-index

Citations

Citations per year for José Crossa1966: 1 citations1984: 1 citations1989: 2 citations1990: 1 citations1991: 1 citations1992: 2 citations1993: 5 citations1994: 8 citations1995: 1 citations1996: 4 citations1997: 6 citations1998: 8 citations1999: 7 citations2000: 7 citations2001: 5 citations2002: 18 citations2003: 20 citations2004: 22 citations2005: 29 citations2006: 28 citations2007: 46 citations2008: 37 citations2009: 47 citations2010: 48 citations2011: 84 citations2012: 161 citations2013: 152 citations2014: 219 citations2015: 195 citations2016: 311 citations2017: 272 citations2018: 250 citations2019: 840 citations2020: 1,162 citations2021: 1,300 citations2022: 1,005 citations2023: 644 citations2024: 1,177 citations2025: 710 citations2026: 37 citations1967–1983: no citations, so these years are not shown1985–1988: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 1,201 citing papers, 17.9% of this breakdownChina: 754 citing papers, 11.2% of this breakdownMexico: 484 citing papers, 7.2% of this breakdownIndia: 412 citing papers, 6.1% of this breakdownAustralia: 357 citing papers, 5.3% of this breakdownGermany: 297 citing papers, 4.4% of this breakdownFrance: 230 citing papers, 3.4% of this breakdownUnited Kingdom: 222 citing papers, 3.3% of this breakdownBrazil: 161 citing papers, 2.4% of this breakdownCanada: 158 citing papers, 2.4% of this breakdownItaly: 150 citing papers, 2.2% of this breakdownKenya: 143 citing papers, 2.1% of this breakdown
0%17.9%Other 32.1%

Institutions

Fields

  • Biochemistry, Genetics and Molecular Biology45.1%
  • Agricultural and Biological Sciences41.3%
  • Computer Science3.4%
  • Environmental Science3.1%
  • Medicine2.1%
  • Engineering1.4%
  • Other3.6%

Topics

  • Genetic Mapping and Diversity in Plants and Animals20%
  • Genetics and Plant Breeding15.7%
  • Genetic and phenotypic traits in livestock11.8%
  • Wheat and Barley Genetics and Pathology7.4%
  • Genetic diversity and population structure1.8%
  • Crop Yield and Soil Fertility1.3%
  • Other42%

Coauthors

All papers

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  1. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives

    Authors: José Crossa, Paulino Pérez‐Rodríguez, Jaime Cuevas, Osval A. Montesinos‐López, Diego Jarquín, Gustavo de los Campos, Juan Burgueño, Juan Manuel González‐Camacho, Sergio Pérez‐Elizalde, Yoseph Beyene, Susanne Dreisigacker, Ravi P. Singh, Xuecai Zhang, Manje Gowda, Manish Roorkiwal, Jessica Rutkoski, Rajeev K. Varshney - Trends in Plant Science 2017 cited by 1,793

  2. Multivariate Statistical Machine Learning Methods for Genomic Prediction

    Authors: Osval A. Montesinos‐López, Abelardo Montesinos‐López, José Crossa - 2022 cited by 488

  3. DNNGP, a deep neural network-based method for genomic prediction using multi-omics data in plants

    Authors: K. Wang, Muhammad Abid, Awais Rasheed, José Crossa, Sarah Hearne, Huihui Li - Molecular Plant 2022 cited by 249

  4. A review of deep learning applications for genomic selection

    Authors: Osval A. Montesinos‐López, Abelardo Montesinos‐López, Paulino Pérez‐Rodríguez, José Alberto Barrón‐López, Johannes W. R. Martini, Silvia B. Fajardo-Flores, Laura S. Gaytán‐Lugo, Pedro C. Santana‐Mancilla, José Crossa - BMC Genomics 2021 cited by 333

  5. Overfitting, Model Tuning, and Evaluation of Prediction Performance

    Authors: Osval A. Montesinos‐López, Abelardo Montesinos‐López, José Crossa - Multivariate Statistical Machine Learning Methods for Genomic Prediction 2022 cited by 298

  6. A reaction norm model for genomic selection using high-dimensional genomic and environmental data

    Authors: Diego Jarquín, José Crossa, Xavier Lacaze, Philippe du Cheyron, Joëlle Daucourt, Josiane Lorgeou, François Piraux, Laurent Guerreiro, Paulino Pérez‐Rodríguez, M.P.L. Calus, Juan Burgueño, Gustavo de los Campos - Theoretical and Applied Genetics 2013 cited by 706

  7. Fundamentals of Artificial Neural Networks and Deep Learning

    Authors: Osval A. Montesinos‐López, Abelardo Montesinos‐López, José Crossa - Multivariate Statistical Machine Learning Methods for Genomic Prediction 2022 cited by 263

  8. Genomic selection in plant breeding: Key factors shaping two decades of progress

    Authors: Admas Alemu, Johanna Åstrand, Osval A. Montesinos‐López, Julio Isidro y Sánchez, Javier Fernández-Gónzalez, Wuletaw Tadesse, Ramesh R. Vetukuri, Anders S. Carlsson, Alf Ceplitis, José Crossa, Rodomiro Ortíz, Aakash Chawade - Molecular Plant 2024 cited by 269

  9. Genomic Prediction of Breeding Values when Modeling Genotype × Environment Interaction using Pedigree and Dense Molecular Markers

    Authors: Juan Burgueño, Gustavo de los Campos, K.A. Weigel, José Crossa - Crop Science 2012 cited by 617

  10. META-R: A software to analyze data from multi-environment plant breeding trials

    Authors: Gregorio Alvarado, Francisco Mario Barcala Rodríguez, Ángela Pacheco, Juan Burgueño, José Crossa, Mateo Vargas, Paulino Pérez‐Rodríguez, Marco Lopez‐Cruz - The Crop Journal 2020 cited by 361

  11. The Modern Plant Breeding Triangle: Optimizing the Use of Genomics, Phenomics, and Enviromics Data

    Authors: José Crossa, Roberto Fritsche‐Neto, Osval A. Montesinos‐López, Germano Costa‐Neto, Susanne Dreisigacker, Abelardo Montesinos‐López, Alison R. Bentley - Frontiers in Plant Science 2021 cited by 259

  12. Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers

    Authors: José Crossa, Gustavo de los Campos, Paulino Pérez‐Rodríguez, Daniel Gianola, Juan Burgueño, J. L. Araus, Dan Makumbi, Ravi P. Singh, Susanne Dreisigacker, Jianbing Yan, Vivi N. Arief, Marianne Bänziger, Hans‐Joachim Braun - Genetics 2010 cited by 809

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

    Authors: Jessica Rutkoski, Jesse Poland, Suchismita Mondal, Enrique Autrique, Lorena González-Pérez, José Crossa, Matthew Reynolds, Ravi P. Singh - G3 Genes Genomes Genetics 2016 cited by 424

  14. Fast-forward breeding for a food-secure world

    Authors: Rajeev K. Varshney, Abhishek Bohra, Manish Roorkiwal, Rutwik Barmukh, Wallace A. Cowling, Annapurna Chitikineni, Hon‐Ming Lam, Lee T. Hickey, Janine Croser, Philipp E. Bayer, David Edwards, José Crossa, Wolfram Weckwerth, A. Harvey Millar, Arvind Kumar, Michael Bevan, Kadambot H. M. Siddique - Trends in Genetics 2021 cited by 174

  15. Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture

    Authors: Abelardo Montesinos‐López, Osval A. Montesinos‐López, Daniel Gianola, José Crossa, Carlos Hernández-Suárez - G3 Genes Genomes Genetics 2018 cited by 188

  16. Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat

    Authors: Diego Jarquín, Cristiano Lemes da Silva, R. Chris Gaynor, Jesse Poland, Allan K. Fritz, Réka Howard, Sarah Battenfield, José Crossa - The Plant Genome 2017 cited by 177

  17. A Benchmarking Between Deep Learning, Support Vector Machine and Bayesian Threshold Best Linear Unbiased Prediction for Predicting Ordinal Traits in Plant Breeding

    Authors: Osval A. Montesinos‐López, Javier Martín‐Vallejo, José Crossa, Daniel Gianola, Carlos Hernández-Suárez, Abelardo Montesinos‐López, Philomin Juliana, Ravi P. Singh - G3 Genes Genomes Genetics 2018 cited by 148

  18. A chickpea genetic variation map based on the sequencing of 3,366 genomes

    Authors: Rajeev K. Varshney, Manish Roorkiwal, Shuai Sun, Prasad Bajaj, Annapurna Chitikineni, Mahendar Thudi, Narendra Pratap Singh, Xiao Du, Hari D. Upadhyaya, Aamir W. Khan, Yue Wang, Vanika Garg, Guangyi Fan, Wallace A. Cowling, José Crossa, Laurent Gentzbittel, Kai P. Voss‐Fels, Vinod Kumar Valluri, Pallavi Sinha, Vikas Kumar Singh, Cécile Ben, Abhishek Rathore, Punna Ramu, Muneendra Kumar Singh, Bunyamin Tar’an, C. Bharadwaj, Mohammad Yasin, Motisagar S. Pithia, Servejeet Singh, Khela Ram Soren, Himabindu Kudapa, Diego Jarquín, Philippe Cubry, Lee T. Hickey, G. P. Dixit, Anne‐Céline Thuillet, Aladdin Hamwieh, Shiv Kumar, Amit Deokar, S. K. Chaturvedi, Aleena Francis, Réka Howard, Debasis Chattopadhyay, David Edwards, Eric Lyons, Yves Vigouroux, Ben J. Hayes, Eric von Wettberg, Swapan K. Datta, Huanming Yang, Henry T. Nguyen, Jian Wang, Kadambot H. M. Siddique, Trilochan Mohapatra, Jeffrey L. Bennetzen, Xun Xu, Xin Liu - Nature 2021 cited by 248

  19. Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

    Authors: Gustavo de los Campos, Hugo Naya, Daniel Gianola, José Crossa, Andrés Legarra, Eduardo Manfredi, K.A. Weigel, José Miguel Cotes Torres - Genetics 2009 cited by 622

  20. Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits

    Authors: Osval A. Montesinos‐López, Abelardo Montesinos‐López, José Crossa, Daniel Gianola, Carlos Hernández-Suárez, Javier Martín‐Vallejo - G3 Genes Genomes Genetics 2018 cited by 185

  21. Breeding schemes for the implementation of genomic selection in wheat ( Triticum spp . )

    Authors: Filippo M. Bassi, Alison R. Bentley, Gilles Charmet, Rodomiro Ortíz, José Crossa - Plant Science 2015 cited by 369

  22. Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

    Authors: Margaret Krause, Lorena González-Pérez, José Crossa, Paulino Pérez‐Rodríguez, Osval A. Montesinos‐López, Ravi P. Singh, Susanne Dreisigacker, Jesse Poland, Jessica Rutkoski, Mark E. Sorrells, Michael A. Gore, Suchismita Mondal - G3 Genes Genomes Genetics 2019 cited by 165

  23. Genomic prediction in CIMMYT maize and wheat breeding programs

    Authors: José Crossa, P Pérez, John M. Hickey, Juan Burgueño, Leonardo Ornella, J. Jesús Cerón‐Rojas, Xuecai Zhang, Susanne Dreisigacker, Raman Babu, Yongle Li, David Bonnett, Ky L. Mathews - Heredity 2013 cited by 468

  24. Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics

    Authors: Philomin Juliana, Jesse Poland, Julio Huerta‐Espino, Sandesh Shrestha, José Crossa, Leonardo Crespo‐Herrera, Fernando Toledo, Velu Govindan, Suchismita Mondal, Uttam Kumar, Sridhar Bhavani, P. K. Singh, M. S. Randhawa, Xinyao He, Carlos Guzmán, Susanne Dreisigacker, Matthew N. Rouse, Yue Jin, Paulino Pérez‐Rodríguez, Osval A. Montesinos‐López, Daljit Singh, Mohammad Mokhlesur Rahman, Félix Marza, Ravi P. Singh - Nature Genetics 2019 cited by 279