Spotibot: Strawberry Fruit Images for Botrytis cinerea Screening

Spotibot (Strawberry) is a dataset supporting research on automated fruit-level screening of Botrytis cinerea in strawberries using a multi-model deep learning pipeline. The dataset is 898.4 MB in size and consists of JPG image files. It was authored by Dan Jeric Arcega Rustia and last updated on 2026-05-27.

Use Cases

• Training image classification models to detect Botrytis cinerea infection on strawberries.
• Developing object detection pipelines for automated fruit-level disease screening.
• Benchmarking multi-model deep learning approaches for plant phenomics tasks.
• Studying the visual symptoms of gray mold (Botrytis cinerea) on strawberry fruit.

Strengths

• Dataset size is 898.4 MB, indicating a medium-scale collection of image data.
• Data is openly shared under a CC-BY-4.0 license, facilitating reuse and modification.
• The dataset is specifically designed to support a described multi-model deep learning pipeline for a concrete research problem.

Limitations

• Row count and specific number of images are unknown, which may limit suitability assessment.
• Column-level documentation and sample data are unavailable; data structure must be inferred after download.
• Description metadata is limited; actual data quality and annotation details require manual inspection.

Provenance

Source

figshare

Collection Method

Likely collected as supporting data for a research submission to Plant Phenomics journal.

Freshness

Last updated 2026-05-27 06:58:44; freshness should be verified.