Evidence map›Paper›PMID 42091604›Full record

ArticleScientific data2026

Morphometric Properties of Olive (Olea europaea) Pits: A Dataset for Cultivar Identification and Analysis.

Elad Ben-Dor, Oz Barazani, Guy Bar-Oz, Giora Ben-Ari, Arnon Dag, Yoav Ben Dor

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. 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. 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

6 authors.

Elad Ben-DorThe School of Plant Sciences and Food Security, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel. eladben@volcani.agri.gov.il.ORCID http://orcid.org/0009-0006-6414-9519
Oz BarazaniDepartment of Vegetable and Field Crops, Institute of Plant Sciences, Agricultural Research Organization, Rishon LeZion, Israel.ORCID http://orcid.org/0000-0002-1557-7799
Guy Bar-OzSchool of Archaeology and Maritime Cultures, University of Haifa, Haifa, Mount Carmel, Israel.ORCID http://orcid.org/0000-0002-1009-5619
Giora Ben-AriDepartment of Fruit Tree Sciences, Institute of Plant Sciences, Agricultural Research Organization, Rishon LeZion, Israel.
Arnon DagDepartment of Fruit Tree Sciences, Gilat Research Center, Agricultural Research Organization, Volcani Institute, Gilat, Israel.
Yoav Ben DorGeochemistry and Environmental Geology Division, Geological Survey of Israel, Jerusalem, Israel. Yoavbd@gsi.gov.il.ORCID http://orcid.org/0000-0002-5345-0297

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101096539Israel Science Foundation (ISF) 332/21
6 · The paper itself

Abstract

Image analysis of pits and grains provide alternative routes for overcoming the invasive approach of genomic tools in the investigation of archaeological or modern plant material, which is only seldom a viable option due to the complex and laborious methodologies required. Nevertheless, any investigation of pit morphology and cultivar interpretation requires a high quality, comprehensive dataset for comparison. Such a benchmark dataset for the morphology of olive (Olea europaea) pits is presented in this paper, designed to facilitate similar research and establish a base for future investigations. The dataset was established by image analysis of pits of 18 olive cultivars that were photographed in both lateral and dorsal positions. A dedicated MATLAB® code was developed to extract the silhouettes of each pit and to calculate 16 morphometric traits of each view of the pit. Altogether, a total of 1008 photos of 504 pits of the 18 cultivars, together with their detailed morphometric description and statistical analysis are available here. These were used to test the accuracy of the dataset and the new approach in representing the different cultivars.

Indexed as

OleaImage Processing, Computer-Assisted

Identifiers

PMID42091604
PMCPMC13358147

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Registered trials

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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.