Orange Leaves Images Dataset for the Detection of Huanglongbing

Juan Carlos Torres-Galván, Paul Hernández Herrera, Juan Antonio Obispo, Xocoyotzin Guadalupe Ávila Cruz, Liliana Montserrat Camacho Ibarra, Paula Magaldi Morales Orosco, Alfonso Alba, Edgar R. Arce-Santana, Valdemar Arce-Guevara, J. S. Murguía, Edgar Guevara and Miguel G. Ramírez-Elías ()
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Juan Carlos Torres-Galván: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Paul Hernández Herrera: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Juan Antonio Obispo: Comité Estatal de Sanidad Vegetal de San Luis Potosí, Rioverde 796133, Mexico
Xocoyotzin Guadalupe Ávila Cruz: Comité Estatal de Sanidad Vegetal de San Luis Potosí, Rioverde 796133, Mexico
Liliana Montserrat Camacho Ibarra: Comité Estatal de Sanidad Vegetal de San Luis Potosí, Rioverde 796133, Mexico
Paula Magaldi Morales Orosco: Comité Estatal de Sanidad Vegetal de San Luis Potosí, Rioverde 796133, Mexico
Alfonso Alba: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Edgar R. Arce-Santana: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Valdemar Arce-Guevara: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
J. S. Murguía: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Edgar Guevara: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico
Miguel G. Ramírez-Elías: Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Av. Chapultepec 1570, Privadas del Pedregal, San Luis Potosí 78295, Mexico

Data, 2025, vol. 10, issue 5, 1-8

Abstract: In agriculture, machine learning (ML) and deep learning (DL) have increased significantly in the last few years. The use of ML and DL for image classification in plant disease has generated significant interest due to their cost, automatization, scalability, and early detection. However, high-quality image datasets are required to train robust classifier models for plant disease detection. In this work, we have created an image dataset of 649 orange leaves divided into two groups: control ( n = 379) and huanglongbing (HLB) disease ( n = 270). The images were acquired with several smartphone cameras of high resolution and processed to remove the background. The dataset enriches the information on characteristics and symptoms of citrus leaves with HLB and healthy leaves. This enhancement makes the dataset potentially valuable for disease identification through leaf segmentation and abnormality detection, particularly when applying ML and DL models.

Keywords: Huanglongbing; orange trees; orange leaves; plant disease detection; image classification (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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