José Crossa

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.