Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Responses to Drought and Flooding

Responses to Drought and Flooding

Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Global knowledge, attitudes, and practices toward pit-and-fissure sealants: A systematic review, meta-analysis, and meta-regression.

Journal of the American Dental Association (1939)·2026

Same author

Clinical performance of resin infiltration and different sealant modalities in noncavitated pits and fissures: a split-mouth randomized controlled trial.

Quintessence international (Berlin, Germany : 1985)·2026

Same author

Effect of sleep quality on physical performance in the elderly.

Journal of bodywork and movement therapies·2026

Same author

Evaluating the effects of sacubitril/valsartan with ST-elevated myocardial infarction: a systematic review and meta-analysis.

Annals of medicine and surgery (2012)·2026

Same author

Therapeutic Potential of Indazole as a Promising Scaffold for Anticancer Drug Development: A Comprehensive Review.

Archiv der Pharmazie·2026

Same author

Design, synthesis, and in-vitro evaluation of 2-(heteroarylthio)acetamido-1<i>H</i>-benzo[<i>d</i>]imidazole derivatives as PTP1B inhibitors for the treatment of type 2 diabetes.

3 Biotech·2026

Search research articles

Related Experiment Video

Updated: Jan 14, 2026

Author Spotlight: Harnessing DNA Barcode Technology to Enhance the Efficiency of Medicinal Plant Identification

Author Spotlight: Harnessing DNA Barcode Technology to Enhance the Efficiency of Medicinal Plant Identification

Published on: November 1, 2024

Central India Medicinal Plant Dataset (CIMPD).

Rajeev Kumar Singh¹, Akhilesh Tiwari², Rajendra Kumar Gupta³

¹Department of IT, Madhav Institute of Technology and Science DU, Gwalior, MP 474005, India.

|October 27, 2025

Summary

A new dataset of medicinal plant leaf images from Central India aids health research. This resource supports advancements in machine learning for plant identification and disease detection.

Keywords:

Feature visualization Image processing Leaf images Medicinal plant Plant classification ResNet18

More Related Videos

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Published on: December 16, 2022

Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry

Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry

Published on: February 2, 2024

Related Experiment Videos

Last Updated: Jan 14, 2026

Author Spotlight: Harnessing DNA Barcode Technology to Enhance the Efficiency of Medicinal Plant Identification

Author Spotlight: Harnessing DNA Barcode Technology to Enhance the Efficiency of Medicinal Plant Identification

Published on: November 1, 2024

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Visualization of Metabolites Identified in the Spatial Metabolome of Traditional Chinese Medicine Using DESI-MSI

Published on: December 16, 2022

Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry

Preparation of Gynura bicolor DC samples for High-Resolution Tandem Mass Spectrometry

Published on: February 2, 2024

Area of Science:

Ethnobotany
Computer Vision
Machine Learning

Background:

Medicinal plants are vital for health and income, especially in rural areas.
Existing research often lacks comprehensive datasets for computational analysis.
Developing robust computational tools requires diverse, well-annotated plant image data.

Purpose of the Study:

To introduce the Central India Medicinal Plant Dataset (CIMPD).
To provide a valuable resource for machine learning and computer vision research in human health.
To facilitate the development of automated plant identification and disease detection systems.

Main Methods:

Collected 9130 leaf images (healthy and unhealthy) from 23 medicinal plant species.
Images were sourced from various locations across Central India.
Data organization included botanical names, common names, geographical origins, and medicinal uses.

Main Results:

The Central India Medicinal Plant Dataset (CIMPD) comprises 9130 images.
The dataset covers 23 distinct medicinal plant species.
Includes detailed metadata for each plant and its images.

Conclusions:

The CIMPD is a significant resource for advancing research in medicinal plant analysis.
Enables the development and evaluation of AI-driven tools for plant health monitoring.
Supports interdisciplinary research bridging botany, computer science, and healthcare.