Evidence map›Paper›PMID 34724078›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2022

Genome-based prediction of agronomic traits in spring wheat under conventional and organic management systems.

Kassa Semagn, Muhammad Iqbal, José Crossa, Diego Jarquin, Reka Howard, Hua Chen, Darcy H Bemister, Brian L Beres, Harpinder Randhawa, Amidou N'Diaye and 2 more

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Comparison of single-trait and multi-trait genomic predictions on agronomic and disease resistance traits in spring wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  4. Article
  5. Article
  6. 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

12 authors.

Kassa SemagnDepartment of Agricultural, Food, and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada.ORCID http://orcid.org/0000-0001-6486-5685
Muhammad IqbalDepartment of Agricultural, Food, and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
José CrossaInternational Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico, DF, Mexico.
Diego JarquinUniversity of Nebraska - Lincoln, Lincoln, NE, 68583, USA.
Reka HowardUniversity of Nebraska - Lincoln, Lincoln, NE, 68583, USA.
Hua ChenDepartment of Agricultural, Food, and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
Darcy H BemisterDepartment of Agricultural, Food, and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada.
Brian L BeresAgriculture and Agri-Food Canada, 5403-1st Avenue South, Lethbridge, AB, T1J 4B1, Canada.
Harpinder RandhawaAgriculture and Agri-Food Canada, 5403-1st Avenue South, Lethbridge, AB, T1J 4B1, Canada.
Amidou N'DiayeCrop Development Centre and Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada.
Curtis PozniakCrop Development Centre and Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK, S7N 5A8, Canada.
Dean SpanerDepartment of Agricultural, Food, and Nutritional Science, 4-10 Agriculture-Forestry Centre, University of Alberta, Edmonton, AB, T6G 2P5, Canada. dean.spaner@ualberta.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageUsing phenotype data of three spring wheat populations evaluated at 6-15 environments under two management systems, we found moderate to very high prediction accuracies across seven traits. The phenotype data collected under an organic management system effectively predicted the performance of lines in the conventional management and vice versa. There is growing interest in developing wheat cultivars specifically for organic agriculture, but we are not aware of the effect of organic management on the predictive ability of genomic selection (GS). Here, we evaluated within populations prediction accuracies of four GS models, four combinations of training and testing sets, three reaction norm models, and three random cross-validations (CV) schemes in three populations phenotyped under organic and conventional management systems. Our study was based on a total of 578 recombinant inbred lines and varieties from three spring wheat populations, which were evaluated for seven traits at 3-9 conventionally and 3-6 organically managed field environments and genotyped either with the wheat 90 K SNP array or DArTseq. We predicted the management systems (CV0

Indexed as

GenomicsTriticumGenome, PlantGenotypePhenotype

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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.