Evidence map›Paper›PMID 32409788›Full record

ArticleScientific reports2020

Improving root characterisation for genomic prediction in cassava.

Bilan Omar Yonis, Dunia Pino Del Carpio, Marnin Wolfe, Jean-Luc Jannink, Peter Kulakow, Ismail Rabbi

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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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

13 citing papers in PubMed.

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  9. Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  10. Article
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  13. Review
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

6 authors.

Bilan Omar Yonis *Montpellier SupAgro, 34060, Montpellier, Cedex, 02, France.
Dunia Pino Del Carpio *Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14850, USA.
Marnin WolfeDepartment of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14850, USA.
Jean-Luc JanninkDepartment of Plant Breeding and Genetics, Cornell University, Ithaca, NY, 14850, USA.
Peter KulakowInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
Ismail RabbiInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. I.Rabbi@cgiar.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cassava is cultivated due to its drought tolerance and high carbohydrate-containing storage roots. The lack of uniformity and irregular shape of storage roots poses constraints on harvesting and post-harvest processing. Here, we phenotyped the Genetic gain and offspring (C1) populations from the International Institute of Tropical Agriculture (IITA) breeding program using image analysis of storage root photographs taken in the field. In the genome-wide association analysis (GWAS), we detected for most shape and size-related traits, QTL on chromosomes 1 and 12. In a previous study, we found the QTL on chromosome 12 to be associated with cassava mosaic disease (CMD) resistance. Because the root uniformity is important for breeding, we calculated the standard deviation (SD) of individual root measurements per clone. With SD measurements we identified new significant QTL for Perimeter, Feret and Aspect Ratio on chromosomes 6, 9 and 16. Predictive accuracies of root size and shape image-extracted traits were mostly higher than yield trait prediction accuracies. This study aimed to evaluate the feasibility of the image phenotyping protocol and assess GWAS and genomic prediction for size and shape image-extracted traits. The methodology described and the results are promising and open up the opportunity to apply high-throughput methods in cassava.

Indexed as

Genome, PlantGenomicsGenome-Wide Association StudyManihotModels, BiologicalPhenotypePlant BreedingPlant RootsQuantitative Trait, HeritableSeeds

Identifiers

PMID32409788
PMCPMC7224197

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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.