Evidence map›Paper›PMID 33505418›Full record

ArticleFrontiers in plant science2020

Advances in Breeding for Mixed Cropping - Incomplete Factorials and the Producer/Associate Concept.

Benedikt Haug, Monika M Messmer, Jérôme Enjalbert, Isabelle Goldringer, Emma Forst, Timothée Flutre, Tristan Mary-Huard, Pierre Hohmann

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
8.7field-weighted citation impact, top 2% of its field
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

20 citing papers in PubMed, 41 citations in OpenAlex.

  1. Article
  2. Review
  3. Fungal Disease Tolerance with a Focus on Wheat: A Review.Journal of fungi (Basel, Switzerland) · 2024
    Review
  4. Coadaptation of coexisting plants enhances productivity in an agricultural system.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Article
  7. Toward plant breeding for multicrop systems.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
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  17. Article
  18. Review
  19. Article
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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

8 authors at 3 institutions in 3 countries.

Benedikt HaugDepartment of Crop Sciences, Research Institute of Organic Agriculture FiBL, Frick, Switzerland.
Monika M MessmerDepartment of Crop Sciences, Research Institute of Organic Agriculture FiBL, Frick, Switzerland.
Jérôme EnjalbertUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, Gif-sur-Yvette, France.
Isabelle GoldringerUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, Gif-sur-Yvette, France.
Emma ForstDipartimento di Scienze Agrarie, Alimentari ed Ambientali (D3A), Università Politecnica delle Marche, Ancona, Italy.
Timothée FlutreUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, Gif-sur-Yvette, France.
Tristan Mary-HuardUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE - Le Moulon, Gif-sur-Yvette, France.
Pierre HohmannDepartment of Crop Sciences, Research Institute of Organic Agriculture FiBL, Frick, Switzerland.
Centre National de la Recherche Scientifique · FRForschungsinstitut für Biologischen Landbau · CHMarche Polytechnic University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mixed cropping has been suggested as a resource-efficient approach to meet high produce demands while maintaining biodiversity and minimizing environmental impact. Current breeding programs do not select for enhanced general mixing ability (GMA) and neglect biological interactions within species mixtures. Clear concepts and efficient experimental designs, adapted to breeding for mixed cropping and encoded into appropriate statistical models, are lacking. Thus, a model framework for GMA and SMA (specific mixing ability) was established. Results of a simulation study showed that an incomplete factorial design combines advantages of two commonly used full factorials, and enables to estimate GMA, SMA, and their variances in a resource-efficient way. This model was extended to the Producer (Pr) and Associate (As) concept to exploit additional information based on fraction yields. It was shown that the Pr/As concept allows to characterize genotypes for their contribution to total mixture yield, and, when relating to plant traits, allows to describe biological interaction functions (BIF) in a mixed crop. Incomplete factorial designs show the potential to drastically improve genetic gain by testing an increased number of genotypes using the same amount of resources. The Pr/As concept can further be employed to maximize GMA in an informed and efficient way. The BIF of a trait can be used to optimize species ratios at harvest as well as to extend our understanding of competitive and facilitative interactions in a mixed plant community. This study provides an integrative methodological framework to promote breeding for mixed cropping.

Indexed as

biological interactionbreedinggeneral mixing abilityincomplete factorial designintercroppingmixed croppingproducer/associate conceptsimulations

Identifiers

PMID33505418
PMCPMC7829252
OpenAlexW3119459041

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.