Evidence map›Paper›PMID 32429327›Full record

ArticlePlants (Basel, Switzerland)2020

Creating Predictive Weed Emergence Models Using Repeat Photography and Image Analysis.

Theresa Reinhardt Piskackova, Chris Reberg-Horton, Robert J Richardson, Robert Austin, Katie M Jennings, Ramon G Leon

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plants (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Theresa Reinhardt PiskackovaDepartment of Crop and Soil Science, North Carolina State University, Raleigh, NC 276957620, USA.
Chris Reberg-HortonDepartment of Crop and Soil Science, North Carolina State University, Raleigh, NC 276957620, USA.
Robert J RichardsonDepartment of Crop and Soil Science, North Carolina State University, Raleigh, NC 276957620, USA.
Robert AustinDepartment of Crop and Soil Science, North Carolina State University, Raleigh, NC 276957620, USA.
Katie M JenningsDepartment of Horticulture, North Carolina State University, Raleigh, NC 276957609, USA.
Ramon G LeonDepartment of Crop and Soil Science, North Carolina State University, Raleigh, NC 276957620, USA.

Funding

U.S. Department of Agriculture 2017-6505-26807, 2018-70006-28933, 2019-68012-29818
6 · The paper itself

Abstract

Weed emergence models have the potential to be important tools for automating weed control actions; however, producing the necessary data (e.g., seedling counts) is time consuming and tedious. If similar weed emergence models could be created by deriving emergence data from images rather than physical counts, the amount of generated data could be increased to create more robust models. In this research, repeat RGB images taken throughout the emergence period of

Indexed as

emergence modelsmaximum likelihood analysisRGBsigmoidal modelssupervised classification

Identifiers

PMID32429327
PMCPMC7285028

What OpenQuestion holds

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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.