Evidence map›Paper›PMID 34420247›Full record

ArticleGlobal change biology2021

Diminishing weed control exacerbates maize yield loss to adverse weather.

Christopher A Landau, Aaron G Hager, Martin M Williams

Abstract read
In one paragraph

Article in Global change biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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

3 authors.

Christopher A LandauDepartment of Crop Sciences, University of Illinois, Urbana, Illinois, USA.ORCID https://orcid.org/0000-0002-7153-0231
Aaron G HagerDepartment of Crop Sciences, University of Illinois, Urbana, Illinois, USA.ORCID https://orcid.org/0000-0002-3823-7068
Martin M WilliamsGlobal Change and Photosynthesis Research Unit, USDA-ARS, Urbana, Illinois, USA.ORCID https://orcid.org/0000-0002-6302-7724

Funding

Agricultural Research Service
6 · The paper itself

Abstract

Both weed interference and adverse weather can cause significant maize yield losses. However, most climate change projections on maize yields ignore the fact that weeds are widespread in maize production. Herein, we examine the effects of weed control and weather variability on maize yield loss due to weeds by using machine learning techniques on an expansive database of herbicide efficacy trials spanning 205 weather environments and 27 years. Late-season control of all weed species was the most important driver of maize yield loss due to weeds according to multiple analyses. Average yield losses of 50% were observed with little to no weed control. Furthermore, when the highest levels of weed control were not achieved, drier, hotter conditions just before and during silking exacerbated maize yield losses due to weeds. Current climate predictions suggest much of the US maize-growing regions will experience warmer, drier summers. This, coupled with the growing prevalence of herbicide resistance, increases the risk of maize yield loss due to weeds in the future without transformational change in weed management systems.

Indexed as

Weed ControlZea maysHerbicide ResistancePlant WeedsWeatherclimate changeherbicide efficacymachine learningmaize (Zea mays)weather variabilityweed interference

Identifiers

PMID34420247
PMCPMC9291076

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.