CoLeaf-DB: Peruvian coffee leaf images dataset for coffee leaf nutritional deficiencies detection and classification

Victor A. Tuesta-Monteza, Heber I. Mejia-Cabrera, Juan Arcila-Diaz

Research output: Contribution to journalArticlepeer-review

Abstract

This article introduces Peruvian coffee leaf datasets known as CATIMOR, CATURRA and BORBON of coffee plantations located at San Miguel de las Naranjas and La Palma Central, Jaén province, Cajamarca, Perú. The leaves with nutritional deficiencies were identified by agronomists, using a physical structure the controlled environment was designed and the images were captured with a digital camera. The dataset contains 1006 leaf images grouped according to their nutritional deficiencies (Boron, Iron, Potasium, Calcium, Magnesium, Manganese, Nitrogen and others). CoLeaf dataset contain images that facilitate training and validation during the utilization of deep learning algorithms for coffee plant leaf nutritional deficiencies recognition and classification. The dataset is publicly and freely available at http://dx.doi.org/10.17632/brfgw46wzb.1.

Original languageEnglish
Article number109226
JournalData in Brief
Volume48
DOIs
StatePublished - Jun 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023

Keywords

  • Deep learning
  • Deficiencies detection
  • Image datasets
  • Machine learning
  • Peruvian coffee

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