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

Scientific data · 6 May 2026 · 10.1038/s41597-026-07180-9

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.

Plant phenotyping relevance

オリーブ核の画像から形態形質を抽出する専用コードと、検証用ベンチマークデータセットを開発・提示しており、植物形質取得法が中心である。

abstractSuch 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.
abstractA dedicated MATLAB® code was developed to extract the silhouettes of each pit and to calculate 16 morphometric traits of each view of the pit.
abstractThese were used to test the accuracy of the dataset and the new approach in representing the different cultivars.

Code and data availability

The paper's olive pit images (1008 photos of 504 pits) and morphometric trait data (16 parameters per view) are openly deposited on Zenodo, along with the authors' MATLAB 'PitAnalyzer' software used for silhouette extraction and trait calculation. Both are paper-specific, public, and directly actionable via the Zenodo.

Datasetpublic

All the images are available on a dedicated Zenodo repository17. The file name of each image comprises an abbreviation of the cultivar name (Table 1), tree number (a, b or c), pit number (1–30) and the pit position (VD VL for dorsal and lateral, respectively).

Open resource ↗Zenodo · html-lines:220-292
Codepublic

The code that was used in this work is compiled as a stand-alone software based on MATLAB “PitAnalyzer”. The software is available to download at the following repository, where any use of it should be attributed appropriately to this publication (https://zenodo.org/records/18789307).

Open resource ↗Zenodo · html-lines:381-404

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