Evidence map›Paper›PMID 33240302›Full record

ArticleFrontiers in plant science2020

Digital Image Analysis Using

Martina Zorić, Sandra Cvejić, Emina Mladenović, Siniša Jocić, Zdenka Babić, Ana Marjanović Jeromela, Dragana Miladinović

Abstract read
PubMed Full text at PMC Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Martina ZorićInstitute of Lowland Forestry and Environment, University of Novi Sad, Novi Sad, Serbia.
Sandra CvejićSunflower Department, Institute of Field and Vegetable Crops, Novi Sad, Serbia.
Emina MladenovićFaculty of Agriculture, University of Novi Sad, Novi Sad, Serbia.
Siniša JocićSunflower Department, Institute of Field and Vegetable Crops, Novi Sad, Serbia.
Zdenka BabićFaculty of Electrical Engineering, University of Banja Luka, Banja Luka, Bosnia and Herzegovina.
Ana Marjanović JeromelaSunflower Department, Institute of Field and Vegetable Crops, Novi Sad, Serbia.
Dragana MiladinovićSunflower Department, Institute of Field and Vegetable Crops, Novi Sad, Serbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As an esthetic trait, ray floret color has a high importance in the development of new sunflower genotypes and their market value. Standard methodology for the evaluation of sunflower ray florets is based on International Union for the Protection of New Varieties of Plants (UPOV) guidelines for sunflower. The major deficiency of this methodology is the necessity of high expertise from evaluators and its high subjectivity. To test the hypothesis that humans cannot distinguish colors equally, six commercial sunflower genotypes were evaluated by 100 agriculture experts, using UPOV guidelines. Moreover, the paper proposes a new methodology for sunflower ray floret color classification - digital UPOV (dUPOV), that relies on software image analysis but still leaves the final decision to the evaluator. For this purpose, we created a new

Indexed as

breedingclassificationdigital UPOVornamental valuesoftwaresunflower

Identifiers

PMID33240302
PMCPMC7680878

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.