Multi-objective Breeding Optimization
Multi-Objective Breeding Optimization is a computational framework in plant and animal breeding programs that simultaneously optimizes multiple conflicting genetic and phenotypic objectives—such as yield, resilience, and environmental adaptability—by integrating advanced selection indices, genomic prediction models, and multi-criteria decision-making algorithms to identify optimal breeding strategies under trade-offs.
12
Publications
598
Citations
32
Authors
26
Institutions
Publications per year
2017–2026
7
12
Multi-trait Genomic Selection Methods for Crop Improvement
Saba Moeinizade, Aaron Kusmec, Guiping Hu et al. · Genetics · 2020 · 81 citations · Full text
Agriculture, Agronomy, Crop Sciences +15
1–5 of 12
32
2
h-index
2
h-index
2
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2
h-index
Commonwealth Scientific and Industrial Research Organisation, Australia
1 publications · 20 citations
1
h-index
1–5 of 32
26
Iowa State University
Ames, United States
3 h-index
12 publications
810 citations
Universidade Estadual Paulista (Unesp)
São Paulo, Brazil
1 h-index
1 publications
18 citations
Hendrix Genetics (Netherlands)
Boxmeer, Netherlands
1 h-index
1 publications
16 citations
Statistical Research (United States)
Redlands, United States
1 h-index
1 publications
124 citations

Utah State University
Logan, United States
1 h-index
2 publications
24 citations
Génétique Physiologie et Systèmes d'Elevage
Toulouse, France
1 h-index
1 publications
40 citations
Roslin Institute
Dalkeith, United Kingdom
1 h-index
2 publications
184 citations

Shahid Bahonar University of Kerman
Kerman, Iran
1 h-index
2 publications
24 citations
1–8 of 26
2 publications · 104 citations
2
h-index
1 publications · 92 citations
1
h-index
JDS · 1 publications · 16 citations
1
h-index
1 publications · 40 citations
1
h-index
1 publications · 50 citations
1
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1–5