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Updated: Jul 25, 2025

Deep Neural Networks for Image-Based Dietary Assessment
Published on: March 13, 2021
CoLeaf-DB: Peruvian coffee leaf images dataset for coffee leaf nutritional deficiencies detection and classification
Victor A Tuesta-Monteza1, Heber I Mejia-Cabrera1, Juan Arcila-Diaz1
1Facultad de Ingeniería Arquitectura y Urbanismo, Universidad Señor de Sipán, Perú.
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.
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