RaspberryJalisco: A field-collected multi-class dataset of Raspberry (Rubus idaeus) phenological stages from Mexican
Jaime Adan Cuevas-Ramirez1, Carlos Alberto Villaseñor-Padilla1, Javier Gomez-Avila1
1Division of Technologies for Cyber-Human Integration (DTIC), Centro Universitario de Ciencias Exactas e Ingenierias (CUCEI), Universidad de Guadalajara, Blvd. Marcelino Garcia Barragan 1421, Guadalajara, Jalisco, 44430, Mexico.
Abstract:
We present RaspberryJalisco, a field-collected annotated image dataset of raspberry (Rubus idaeus) fruits at distinct phenological stages, captured in a commercial orchard in Jocotepec, Jalisco, Mexico, during November-December 2025. The dataset comprises 11,884 tiled images and 174,763 bounding-box annotations distributed across two complementary labeling schemes: a fine-grained 5-class configuration (Bud, BrightRed C4, DarkRed C5, Green, Orange (red dot)) and a coarser 3-class configuration (Immature, BrightRed C4, Orange (red dot)) designed for yield-prediction and harvest-planning tasks. Images were acquired using a DSLR camera under natural midday illumination and manually annotated by three domain-expert annotators with LabelImg. In response to the risk of parent-image leakage after tiling, the revised release includes persistent parent-image identifiers, random and parent-image grouped split manifests, a leakage audit, corrected random-split baselines, and leakage-resistant grouped YOLOv8 benchmarks. All annotations are provided in YOLO normalized format, with dataset descriptors, scripts, source tables, figures, and YOLOv8 benchmark weights. The data can be reused for in-domain fruit detection, fruit counting, phenological analysis, model benchmarking, and method development, while cross-site or cross-season deployment should be validated externally.
More Related Videos
Related Concept Videos
Light Acquisition
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Aggregates Classification
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Plant Breeding and Biotechnology
Data Collection I
Fruit Development, Structure, and Function


