Evidence map›Paper›PMID 41461821›Full record

ArticleScientific reports2025

Performance of multi-trait and single-trait genomic selection for grain Fe and Zn concentrations in sorghum under different breeding constraints.

Ephrem Habyarimana, Sonal Chavan, Chaitra Hugar, Suvarna, Niranjan Ravindra Thakur, Marco Lopez-Cruz, Jieqin Li, Pradeep Ruperao

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Ephrem HabyarimanaInternational Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502324, India. Ephrem.Habyarimana@icrisat.org.
Sonal ChavanInternational Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502324, India.
Chaitra HugarUniversity of Agricultural Sciences, Raichur, 584 104, Karnataka, India.
SuvarnaUniversity of Agricultural Sciences, Raichur, 584 104, Karnataka, India.
Niranjan Ravindra ThakurInternational Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502324, India.
Marco Lopez-CruzDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, 48824, USA.
Jieqin LiCollege of Agriculture, Anhui Science and Technology University, Fengyang, 233100, China.
Pradeep RuperaoInternational Crops Research Institute for the Semi-Arid Tropics, Patancheru, 502324, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sorghum biofortification is a cost-effective approach to solving the issue of micronutrient deficiencies in human diets. Research programs face challenges, e.g., phenotyping time, cost, and accuracy in evaluating breeding populations across years and environments, which can be addressed through genomic selection (GS). The present GS work on sorghum grain Fe and Zn contents revealed that the multi-trait genomic best linear unbiased prediction (GBLUP) model (MT-GBLUP) consistently outperformed single-trait GBLUP (ST-GBLUP) in terms of prediction accuracy (PA) under different breeding resource-constrained scenarios. The PA gain by MT-GBLUP for Fe (0.274) and Zn (0.183) was greater when information was borrowed from auxiliary agronomic traits evaluated in a few locations than when only highly correlated target traits (Fe and Zn) were evaluated in more years and locations (PA gain ≤ 0.005). These results suggest that easily scorable non-target traits can inform and improve MT-GBLUP prediction accuracy for the genomic estimated breeding values of the target traits, thereby significantly saving multi-environment testing resources and potentially boosting genetic gain per unit time and cost.

Indexed as

Edible GrainIronPlant BreedingQuantitative Trait LociSelection, GeneticSorghumZincBiofortificationGenome, PlantGenomicsPhenotypeIronZincGenomic selectionMicronutrients biofortificationMulti-trait GBLUPPrediction accuracySorghum bicolor

Identifiers

PMID41461821
PMCPMC12749847

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.