ACHENY: A Standard Chenopodiaceae Image Dataset

ACHENY (Autumn Chenopod of Yazd) is a standardized image dataset of Chenopodiaceae plants, curated to advance deep learning research in botanical identification and biodiversity monitoring.

📌 Overview

Identifying species within the Chenopodiaceae family is historically challenging due to high morphological similarities. This dataset provides 27,030 high-resolution images across 30 species, captured in real-world desert and semi-desert conditions in the Yazd province of Iran.

Key Features:

• Diverse Conditions: Captured under varying sunlight, wind, viewpoints, and distances.
• Standardized Format: RGB images resized to 224 x 224 pixels (with 64 x 64 versions also available).
• Expert Labeling: Collected from multiple bushes per species to ensure high intra-species variety.

🌿 Species List & Taxonomy

The dataset contains 30 species collected from various habitats.

Row	Class ID	Scientific Name	Natural Habitat Area Studied
1	AnaHau	Anabasis haussknechtii Bge. ex Boiss.	Around Nodooshan
2	AnaSet	Anabasis setifera Moq.	Desert areas around Yazd
3	AtrCan	Atriplex canescens (Pursh) Nutt.	Cultivated between Ardakan and Yazd
4	AtrLen	Atriplex lentiformis (Torr.) S. Watds.	Cultivated in Chah-Afzal of Ardakan
5	AtrLeu	Atriplex leucoclada (Boiss.) Aellen	Desert areas around Yazd, Ardakan, and Meybod
6	CerAre	Ceratocarpus arenarius L.	Around Taft (Shirkooh)
7	CheAlb	Chenopodium album L.	Yazd province among farms and gardens
8	CorMon	Cornulaca monacantha Delile	Between Yazd and Ardakan
9	GirOpp	Girgensonia oppositiflora (Pall.) Fenzl.	Around Mehriz
10	HalAmm	Haloxylon ammodendron (C. A. Mey.) Bge.	Wide area of Yazd Deserts
11	HalBel	Halostachys belangeriana (Moq.) Botsch.	Abarkuh deserts
12	HalPer	Haloxylon persicum Bge. ex Boiss.	From Mehriz to Marvast
13	HalStr	Halocnemum strobilaceum (Pall.) M. B.	Salt marshes around Behabad and Aghda
14	HalSub	Halothamnus subaphyllus (C. A. Mey.) Botsch.	Around Chadormaloo
15	HamSal	Hammada salicornica (Moq.) Iljin	Yazd-Bafgh road
16	KocSco	Kochia scoparia (L.) Schrad.	Often as weed in parks
17	KocSte	Kochia stellaris Moq.	Yazd to Ardakan
18	SalAba	Salsola abarghuensis Assadi	North of Abarkuh desert (Endemic to Iran)
19	SalDen	Salsola dendroides Pall.	Between Marvast and Harat
20	SalInc	Salsola incanescens C. A. Mey.	Around the road of Yazd-Ardakan
21	SalKal	Salsola kali L.	Often as weed in different areas of Yazd
22	SalKer	Salsola kerneri (Wol.) Osczak. Botsch.	Desert areas around Nodooshan
23	SalPra	Salsola praecox Litw.	Sand dunes around Ardakan
24	SalTom	Salsola tomentosa (Moq.) Spach.	Across the Yazd desert areas
25	SalTur	Salsola turcomanica (Litv.) Freitag.	Ardakan Around
26	SalYaz	Salsola yazdiana Assadi	Around Kharanagh (Endemic to Iran)
27	SeiCin	Seidlitzia cinerea (Moq.) Bge & Botsch.	Eastern areas of Yazd
28	SeiRos	Seidlitzia rosmarinus (Ehrenb.) Bge. ex Boiss.	Beside Yazd-Ardakan Road
29	SuaAcu	Suaeda acuminata (C. A. Mey.) Moq.	Around Ardakan
30	SuaAeg	Suaeda aegyptiaca (Hasselq.) Zohary	Around Ardakan

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🚀 Data Access

The full dataset is hosted on Mendeley Data:
Download ACHENY Dataset

🖼️ Looking for High-Resolution images? Original uncompressed files are available for research purposes. See DATA_REQUEST.md for details.

📄 License

The dataset is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

📚 Research & Publications

The following publications detail the creation of the ACHENY dataset and the development of deep learning models optimized for its classification.

1. Primary Dataset Paper

ACHENY: A Standard Chenopodiaceae Image dataset for Deep Learning Models > A. Heidary-Sharifabad, M. Sardari Zarchi, S. Emadi, & G. Zarei (2021) > Journal: Data in Brief, 39, 107478. [DOI: 10.1016/j.dib.2021.107478]

2. Deep Learning Benchmarks

Efficient Deep Learning Models for Categorizing Chenopodiaceae in the Wild > A. Heidary-Sharifabad, M. Sardari Zarchi, S. Emadi, & G. Zarei (2021) > Journal: Int. J. of Pattern Recognition and Artificial Intelligence, 35(10). [DOI: 10.1142/S0218001421520157]

3. Padeep: Patched Deep Learning

Padeep: A Patched Deep Learning Based Model for Plants Recognition on Small Size Dataset: Chenopodiaceae Case Study > A. Heidary-Sharifabad, M. Sardari Zarchi, & G. Zarei (2022) > Journal: Int. J. of Computational Intelligence and Applications, 21(01). [DOI: 10.1142/S1469026822500055]

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📖 BibTeX

If you use the ACHENY dataset or the related models in your research, please cite:

@article{acheny2021,
  title={ACHENY: A Standard Chenopodiaceae Image dataset for Deep Learning Models},
  author={Heidary-Sharifabad, Ahmad and Sardari Zarchi, Mohsen and Emadi, Sima and Zarei, Gholamreza},
  journal={Data in Brief},
  volume={39},
  pages={107478},
  year={2021},
  publisher={Elsevier}
}

@article{efficient_acheny2021,
  title={Efficient Deep Learning Models for Categorizing Chenopodiaceae in the Wild},
  author={Heidary-Sharifabad, Ahmad and Sardari Zarchi, Mohsen and Emadi, Sima and Zarei, Gholamreza},
  journal={International Journal of Pattern Recognition and Artificial Intelligence},
  volume={35},
  number={10},
  pages={2152015},
  year={2021}
}

@article{padeep2022,
  title={Padeep: A Patched Deep Learning Based Model for Plants Recognition on Small Size Dataset: Chenopodiaceae Case Study},
  author={Heidary-Sharifabad, Ahmad and Sardari Zarchi, Mohsen and Zarei, Gholamreza},
  journal={International Journal of Computational Intelligence and Applications},
  volume={21},
  number={01},
  year={2022}
}

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