Exploration of Foods and Foodomics

From: Unified CNN-based recognition of multi-crop leaf diseases with web deployment

Table 1. Summary of the collected dataset.

Class name	Number of images
Class name	Training image usage	Validation image usage	Test image usage	Total image
Corn Cercospora leaf spot (gray leaf spot)	1,080	270	150	1,500
Corn common rust	1,080	270	150	1,500
Corn northern leaf blight	1,080	270	150	1,500
Corn healthy	1,080	270	150	1,500
Potato early blight	1,080	270	150	1,500
Potato late blight	1,080	270	150	1,500
Potato healthy	1,080	270	150	1,500
Rice bacterial blight	1,080	270	150	1,500
Rice brown spot	1,080	270	150	1,500
Rice leaf smut	1,080	270	150	1,500
Rice healthy	1,080	270	150	1,500
Tomato bacterial spot	1,080	270	150	1,500
Tomato spider mites (two-spotted)	1,080	270	150	1,500
Tomato healthy	1,080	270	150	1,500
Total images	15,120	3,780	2,100	21,000

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Declarations

Author contributions

ZWB: Conceptualization, Methodology, Software, Investigation, Data curation, Formal analysis, Visualization, Resources, Writing—original draft, Writing—review & editing. ZBMA: Writing—original draft. MH: Supervision, Conceptualization, Resources, Writing—review & editing. MTH: Conceptualization, Methodology, Supervision, Resources, Project administration, Writing—review & editing. All authors read and approved the submitted version.

Conflicts of interest

The authors declare that there are no conflicts of interest.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

All images used in this study were obtained from publicly available repositories, primarily the rice leaf diseases dataset (Antony and Prasanth [1]), the seasonal corn leaf disease dataset (Ahmad [2]), and the potatof leaf disease dataset in uncontrolled environments (Shabrina et al. [3]), all hosted on Mendeley Data. These images were re-curated into a balanced 14-class dataset of 21,000 images covering corn, potato, rice, and tomato, with fixed training, validation, and test splits, as described in the Materials and methods section. No new raw data were generated in this study, and all source data can be accessed directly from the repositories cited above.

Funding

Not applicable.

Copyright

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Open Exploration maintains a neutral stance on jurisdictional claims in published institutional affiliations and maps. All opinions expressed in this article are the personal views of the author(s) and do not represent the stance of the editorial team or the publisher.

References

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Ahmad H. Seasonal Corn Leaf Disease Dataset: A Multi-Year Collection for Robust Analysis [Internet]. [cited 2025 Jul 21]. Available from: https://doi.org/10.17632/vy629dngm8.1

Shabrina HN, Indarti S, Maharani R, Kristiyanti DA, Irmawati I, Prastomo K. Potato leaf disease dataset in uncontrolled environment [Internet]. [cited 2025 Jul 21]. Available from: https://doi.org/10.17632/ptz377bwb8.1

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