Evidence map›Paper›PMID 39811518›Full record

ArticleData in brief2025

Money plant disease atlas: A comprehensive dataset for disease classification in ornamental horticulture.

Md Seyam Ali Biswas, Md Hasan Ahmad, Sajib Bormon, Rimon, Sohanur Rahman Sohag, Amatul Bushra Akhi

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Md Seyam Ali BiswasDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
Md Hasan AhmadDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
Sajib BormonDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
RimonDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
Sohanur Rahman SohagDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
Amatul Bushra AkhiDepartment of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epipremnum aureum, sometimes known as the Money Plant, is a popular houseplant known for its hearts-shaped leaves and durability. Commonly referred to as Golden Pothos or Devil's Ivy, it is also appreciated for its ornamental value and air cleaning ability. They say that these plants are attractive to many people owing to their tolerance to several conditions and easy care, therefore, it is no surprise that they are found in many households and workplaces. Money Plants are hardy, but like any other plant they can also be infected by various diseases, which may render them less attractive, or even unattractive. This work encompasses bacterial wilt, manganese poisoning aspects and together with a healthy leaves aspect presents all prevalent masses and offer a comprehensive image of diseases. A dataset of 224 × 224 pixel images is utilized to accomplish this work with the intention to further enhance support in Ornamental Horticulture practices and diagnose more accurately. This work not only contributes ideas and approaches in understanding the field of plants pathology but also stresses on the fact how image processing can be beneficial in looking after plants. The dataset serves as a solid foundation for deep learning approaches into Ornamental Agriculture and provides useful insights for researchers studying the cultivation of money plants.

Indexed as

Deep learningImage identificationImage pre-processingMoney leaf datasetOrnamental agricultureTransformer

Identifiers

PMID39811518
PMCPMC11729688

What OpenQuestion holds

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LicenceCC BY
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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.