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Plant Science and Agronomy
Mexico
2026

D-Index & Metrics

Plant Science and Agronomy

D-Index
118
Citations
45508
World Ranking
75
National Ranking
1

José Crossa publication distribution in Plant Science and Agronomy in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Plant Science and Agronomy in 2026. The highlighted bar marks where José Crossa sits on this spectrum.

36–40 publications: 2 scientists 41–45 publications: 7 scientists 46–50 publications: 40 scientists 51–55 publications: 58 scientists 56–60 publications: 60 scientists 61–65 publications: 107 scientists 66–70 publications: 130 scientists 71–75 publications: 153 scientists 76–80 publications: 191 scientists 81–85 publications: 199 scientists 86–90 publications: 206 scientists 91–95 publications: 218 scientists 96–100 publications: 226 scientists 101–105 publications: 227 scientists 106–110 publications: 247 scientists 111–115 publications: 255 scientists 116–120 publications: 253 scientists 121–125 publications: 233 scientists 126–130 publications: 219 scientists 131–135 publications: 201 scientists 136–140 publications: 194 scientists 141–145 publications: 176 scientists 146–150 publications: 157 scientists 151–155 publications: 147 scientists 156–160 publications: 151 scientists 161–165 publications: 159 scientists 166–170 publications: 137 scientists 171–175 publications: 128 scientists 176–180 publications: 126 scientists 181–185 publications: 98 scientists 186–190 publications: 114 scientists 191–195 publications: 100 scientists 196–200 publications: 90 scientists 201–205 publications: 71 scientists 206–210 publications: 98 scientists 211–215 publications: 70 scientists 216–220 publications: 86 scientists 221–225 publications: 61 scientists 226–230 publications: 58 scientists 231–235 publications: 53 scientists 236–240 publications: 64 scientists 241–245 publications: 39 scientists 246–250 publications: 46 scientists 251–255 publications: 51 scientists 256–260 publications: 36 scientists 261–265 publications: 44 scientists 266–270 publications: 35 scientists 271–275 publications: 30 scientists 276–280 publications: 33 scientists 281–285 publications: 35 scientists 286–290 publications: 36 scientists 291–295 publications: 26 scientists 296–300 publications: 26 scientists 301–305 publications: 31 scientists 306–310 publications: 30 scientists 311–315 publications: 21 scientists 316–320 publications: 29 scientists 321–325 publications: 14 scientists 326–330 publications: 15 scientists 331–335 publications: 15 scientists 336–340 publications: 17 scientists 341–345 publications: 15 scientists 346–350 publications: 12 scientists 351–355 publications: 17 scientists 356–360 publications: 18 scientists 361–365 publications: 12 scientists 366–370 publications: 11 scientists 371–375 publications: 6 scientists 376–380 publications: 6 scientists 381–385 publications: 11 scientists 386–390 publications: 9 scientists 391–395 publications: 10 scientists 396–400 publications: 8 scientists 401–405 publications: 4 scientists 406–410 publications: 9 scientists 411–415 publications: 11 scientists 416–420 publications: 4 scientists 421–425 publications: 7 scientists 426–430 publications: 4 scientists 431–435 publications: 3 scientists 436–440 publications: 5 scientists 441–445 publications: 8 scientists 446–450 publications: 6 scientists 451–455 publications: 7 scientists 456–460 publications: 5 scientists 461–465 publications: 6 scientists 466 publications: 2 scientists 467+ publications: 99 scientists
36 publications 467+

This scientist: 682 publications — 100th percentile

100% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 467 publications or more.

José Crossa D-index placement in Plant Science and Agronomy in 2026

The chart shows the D-index (discipline H-index) distribution of Plant Science and Agronomy scientists ranked by Research.com in 2026. The highlighted bar marks where José Crossa sits on this spectrum.

30 D-Index: 200 scientists 31 D-Index: 236 scientists 32 D-Index: 253 scientists 33 D-Index: 283 scientists 34 D-Index: 288 scientists 35 D-Index: 240 scientists 36 D-Index: 246 scientists 37 D-Index: 243 scientists 38 D-Index: 247 scientists 39 D-Index: 229 scientists 40 D-Index: 232 scientists 41 D-Index: 230 scientists 42 D-Index: 228 scientists 43 D-Index: 219 scientists 44 D-Index: 193 scientists 45 D-Index: 164 scientists 46 D-Index: 158 scientists 47 D-Index: 143 scientists 48 D-Index: 131 scientists 49 D-Index: 127 scientists 50 D-Index: 122 scientists 51 D-Index: 122 scientists 52 D-Index: 110 scientists 53 D-Index: 102 scientists 54 D-Index: 98 scientists 55 D-Index: 79 scientists 56 D-Index: 85 scientists 57 D-Index: 88 scientists 58 D-Index: 91 scientists 59 D-Index: 62 scientists 60 D-Index: 61 scientists 61 D-Index: 59 scientists 62 D-Index: 54 scientists 63 D-Index: 61 scientists 64 D-Index: 59 scientists 65 D-Index: 58 scientists 66 D-Index: 41 scientists 67 D-Index: 49 scientists 68 D-Index: 39 scientists 69 D-Index: 32 scientists 70 D-Index: 40 scientists 71 D-Index: 47 scientists 72 D-Index: 38 scientists 73 D-Index: 28 scientists 74 D-Index: 29 scientists 75 D-Index: 28 scientists 76 D-Index: 22 scientists 77 D-Index: 21 scientists 78 D-Index: 25 scientists 79 D-Index: 26 scientists 80 D-Index: 19 scientists 81 D-Index: 16 scientists 82 D-Index: 12 scientists 83 D-Index: 16 scientists 84 D-Index: 14 scientists 85 D-Index: 11 scientists 86 D-Index: 17 scientists 87 D-Index: 13 scientists 88 D-Index: 10 scientists 89 D-Index: 12 scientists 90 D-Index: 18 scientists 91 D-Index: 16 scientists 92 D-Index: 16 scientists 93 D-Index: 17 scientists 94 D-Index: 12 scientists 95 D-Index: 8 scientists 96 D-Index: 9 scientists 97 D-Index: 9 scientists 98 D-Index: 11 scientists 99 D-Index: 12 scientists 100 D-Index: 5 scientists 101 D-Index: 8 scientists 102 D-Index: 4 scientists 103 D-Index: 11 scientists 104 D-Index: 5 scientists 105 D-Index: 9 scientists 106 D-Index: 7 scientists 107 D-Index: 4 scientists 108 D-Index: 8 scientists 109+ D-Index: 99 scientists
30 D-Index 109+

This scientist: 118 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 109 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Plant Science and Agronomy in Mexico Leader Award
  • 2025 - Research.com Plant Science and Agronomy in Mexico Leader Award
  • 2022 - Research.com Plant Science and Agronomy in Mexico Leader Award
  • 2002 - Fellow of the American Society of Agronomy (ASA)
  • 2002 - Fellow of the Crop Science Society of America (CSSA)

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Genetics
  • Gene

José Crossa mostly deals with Biotechnology, Gene–environment interaction, Agronomy, Plant breeding and Genetics. His Biotechnology research includes themes of Genetic diversity, Crop, Linkage disequilibrium, Selection and Data set. His Selection study integrates concerns from other disciplines, such as Genetic gain and Genomic selection.

His Gene–environment interaction study combines topics in areas such as Covariance, Mixed model, Statistics, Quantitative trait locus and Biplot. As part of the same scientific family, José Crossa usually focuses on Agronomy, concentrating on Crop residue and intersecting with Crop rotation and Soil water. He works mostly in the field of Genetics, limiting it down to topics relating to Computational biology and, in certain cases, Phenotype.

His most cited work include:

  • Prediction of Genetic Values of Quantitative Traits in Plant Breeding Using Pedigree and Molecular Markers (497 citations)
  • Statistical analyses of multilocation trials (433 citations)
  • Genomic Selection in Wheat Breeding using Genotyping-by-Sequencing (415 citations)

What are the main themes of his work throughout his whole career to date?

José Crossa focuses on Agronomy, Statistics, Selection, Germplasm and Gene–environment interaction. His study looks at the relationship between Statistics and topics such as Trait, which overlap with Heritability. His research integrates issues of Genetic gain and Genomic selection in his study of Selection.

His Germplasm research is multidisciplinary, incorporating perspectives in Zea mays, Heterosis and Genetic diversity. His Gene–environment interaction study improves the overall literature in Genotype. His Plant breeding study incorporates themes from Quantitative trait locus, Biotechnology, Crop yield and Breeding program.

He most often published in these fields:

  • Agronomy (27.98%)
  • Statistics (27.44%)
  • Selection (18.05%)

What were the highlights of his more recent work (between 2018-2021)?

  • Statistics (27.44%)
  • Selection (18.05%)
  • Artificial intelligence (7.76%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Statistics, Selection, Artificial intelligence, Bayesian probability and Plant breeding. His Statistics study which covers Trait that intersects with Genetic gain. His study looks at the relationship between Selection and fields such as Doubled haploidy, as well as how they intersect with chemical problems.

Within one scientific family, José Crossa focuses on topics pertaining to Machine learning under Artificial intelligence, and may sometimes address concerns connected to Grain yield. His Bayesian probability research is multidisciplinary, incorporating elements of Kernel regression, Regression, Predictive modelling and Maximum a posteriori estimation. His research in Plant breeding intersects with topics in Breeding program, Computational biology, Marker-assisted selection and Genomic selection.

Between 2018 and 2021, his most popular works were:

  • Resequencing of 429 chickpea accessions from 45 countries provides insights into genome diversity, domestication and agronomic traits. (64 citations)
  • Improving grain yield, stress resilience and quality of bread wheat using large-scale genomics. (54 citations)
  • Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat (32 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Gene
  • Genetics

His scientific interests lie mostly in Statistics, Plant breeding, Artificial intelligence, Selection and Hybrid. His Statistics research incorporates elements of Heritability, Trait, Set and Gene–environment interaction. His work carried out in the field of Gene–environment interaction brings together such families of science as Remote sensing and Grain yield, Agronomy.

The concepts of his Plant breeding study are interwoven with issues in Toxicology, Quantitative trait locus, Carotenoid, Breeding program and Computational biology. His research investigates the connection between Artificial intelligence and topics such as Machine learning that intersect with problems in Bayesian probability. José Crossa has researched Hybrid in several fields, including Biotechnology, Inbred strain and Participatory assessment.

Best Publications

  • Genomic Selection in Plant Breeding: Methods, Models, and Perspectives

    José Crossa;Paulino Pérez-Rodríguez;Jaime Cuevas;Osval Montesinos-López

  • Statistical analyses of multilocation trials

    Jose Crossa

  • Prediction of genetic values of quantitative traits in plant breeding using pedigree and molecular markers.

    José Crossa;Gustavo De Los Campos;Gustavo De Los Campos;Paulino Pérez;Daniel Gianola

  • Additive main effects and multiplicative interaction analysis of two international Maize cultivar trials

    J. Crossa;H. G. Gauch;R. W. Zobel

  • Genomic Selection in Wheat Breeding using Genotyping-by-Sequencing

    Jesse A. Poland;Jeffrey Endelman;Julie Dawson;Jessica Rutkoski

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

    Gustavo de los Campos;Hugo Naya;Daniel Gianola;José Crossa

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

    Diego Jarquín;Diego Jarquín;José Crossa;Xavier Lacaze;Philippe Du Cheyron

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

    Juan Burgueño;Gustavo de los Campos;Kent Weigel;José Crossa

  • Association analysis of historical bread wheat germplasm using additive genetic covariance of relatives and population structure

    José Crossa;Juan Burgueño;Susanne Dreisigacker;Mateo Vargas

  • Two Types of GGE Biplots for Analyzing Multi-Environment Trial Data

    Weikai Yan;Paul L. Cornelius;Jose Crossa;L.A. Hunt

  • Genomic prediction in CIMMYT maize and wheat breeding programs

    Jose Crossa;Paulino Perez;John M Hickey;John M Hickey;Juan Burgueno

  • Canopy temperature and vegetation indices from high-throughput phenotyping improve accuracy of pedigree and genomic selection for grain yield in wheat

    Jessica Rutkoski;Jessica Rutkoski;Jesse Poland;Suchismita Mondal;Enrique Autrique

  • Semi-parametric genomic-enabled prediction of genetic values using reproducing kernel Hilbert spaces methods

    Gustavo De Los Campos;Daniel Gianola;Guilherme J. M. Rosa;Kent A. Weigel

  • Biplot Analysis of Genotype × Environment Interaction: Proceed with Caution

    Rong-Cai Yang;Jose Crossa;Paul L. Cornelius;Juan Burgueño

  • AMMI adjustment for statistical analysis of an international wheat yield trial.

    J. Crossa;P.N. Fox;W.H. Pfeiffer;S. Rajaram

  • High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

    Llorenç Cabrera-Bosquet;José Crossa;Jarislav von Zitzewitz;María Dolors Serret

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

    Filippo M Bassi;Alison R Bentley;Gilles Charmet;Rodomiro Ortiz

  • Identification of Drought, Heat, and Combined Drought and Heat Tolerant Donors in Maize

    Jill E. Cairns;Jose Crossa;P. H. Zaidi;Pichet Grudloyma

  • Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

    Marco Lopez-Cruz;Jose Crossa;David Bonnett;Susanne Dreisigacker

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

    Gregorio Alvarado;Francisco M. Rodríguez;Francisco M. Rodríguez;Angela Pacheco;Juan Burgueño

  • Race non-specific resistance to rust diseases in CIMMYT spring wheats

    R. P. Singh;J. Huerta-Espino;S. Bhavani;S. A. Herrera-Foessel

  • Genetic Characterization of CIMMYT Inbred Maize Lines and Open Pollinated Populations Using Large Scale Fingerprinting Methods

    Marilyn L. Warburton;Xia Xianchun;Jose Crossa;Jorge Franco

Frequent Co-Authors

Juan Burgueño
Juan Burgueño International Maize and Wheat Improvement Center
Ravi P. Singh
Ravi P. Singh International Maize and Wheat Improvement Center
Paulino Pérez-Rodríguez
Paulino Pérez-Rodríguez Colegio de Postgraduados
Mateo Vargas
Mateo Vargas Chapingo Autonomous University
Susanne Dreisigacker
Susanne Dreisigacker International Maize and Wheat Improvement Center
Jesse Poland
Jesse Poland King Abdullah University of Science and Technology
Richard Trethowan
Richard Trethowan University of Sydney
Suchismita Mondal
Suchismita Mondal Montana State University
Gustavo de los Campos
Gustavo de los Campos Michigan State University
Daniel Gianola
Daniel Gianola University of Wisconsin–Madison

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