Evidence map›Paper›PMID 41362345›Full record

ArticleData in brief2025

CS-D: A dataset for disease in tea leaf (Camellia sinensis) from Assam.

Megha Gupta, Sunaina Garg, Nabamita Deb, Piyush Pandey

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Megha GuptaDepartment of Computer Application, RIMT University, Mandi Gobindgarh, Punjab, India.
Sunaina GargDepartment of Computer Application, RIMT University, Mandi Gobindgarh, Punjab, India.
Nabamita DebDepartment of Information Technology, Gauhati University, Guwahati, Assam, India.
Piyush PandeyDepartment of Microbiology, Assam University, Silchar, Assam, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tea has a refreshing taste, smooth aroma, flavour, texture, and appearance, and provides various health benefits. Tea is made from tea leaves. Diseases infest tea leaves, ultimately impacting tea quality. The proposed tea leaf dataset comprises healthy leaves and diseased leaves attacked by insect pests, mite pests, fungi, and algae. The following five affected classes are included in the dataset: Tea Mosquito Bug, Red Spider Mite, Leaf Red Rust, Blister Blight, and Brown Blight. The data were collected from seven tea fields in different districts of Assam over a period of seven months, using three smartphone devices with varying pixel dimensions. Raw images are resized, augmented, and cleaned. Our aim is to provide a proposed dataset to researchers, enabling them to develop models.

Indexed as

Blister blightBrown blightDatasetDiseaseImage classificationRed spider miteTea leaf

Identifiers

PMID41362345
PMCPMC12681924

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.