Evidence map›Paper›PMID 42860556›Full record

ArticleThe plant genome2026

Genomic prediction of single cross families of perennial ryegrass under two nitrogen managements.

Divino Rosa Dos Santos Junior, Dario Fè, Ingo Lenk, Christian S Jensen, Torben Asp, Luc Janss, Elesandro Bornhofen

Abstract read
In one paragraph

Article in The plant genome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Divino Rosa Dos Santos JuniorCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-8104-558X
Dario FèCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0009-0004-8281-3992
Ingo LenkResearch Division, DLF Seeds A/S, Store Heddinge, Denmark.ORCID https://orcid.org/0000-0002-9375-2783
Christian S JensenResearch Division, DLF Seeds A/S, Store Heddinge, Denmark.
Torben AspCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-6470-2410
Luc JanssCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0001-9804-1529
Elesandro BornhofenCenter for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark.ORCID https://orcid.org/0000-0002-7447-6226

Funding

Danish Ministry of Food, Agriculture and FisheriesGUDP 34009-15-0952Ministeriet for Fødevarer, Landbrug og Fiskeri - Green Development and Demonstration Programme
6 · The paper itself

Abstract

The performance of a single cross is determined by the additive effects of the parents and their interactions, which can be estimated through general combining ability (GCA) and specific combining ability (SCA). With genome-wide marker information, it is possible to predict GCA for new parents and the genetic value of unrealized crosses. Several studies in crops such as maize (Zea mays L.) and rice (Oryza sativa L.) have demonstrated the potential of genomic prediction for single-cross performance. However, no study to date has explored its relevance in perennial ryegrass (Lolium perenne L.), an obligate allogamous species bred in genetically heterogeneous families. In this study, we estimated genetic parameters and evaluated genomic prediction models for dry matter yield and nutritive quality traits in F

Indexed as

Genome, PlantLoliumNitrogenCrosses, GeneticGenomicsGenotypeModels, GeneticPhenotypeQuantitative Trait LociNitrogen

Identifiers

PMID42860556
PMCPMC13655223

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.