A bibliometric analysis of fruit disease prediction using machine learning

Title

A bibliometric analysis of fruit disease prediction using machine learning

Creator

Kujur, Lawrence; Gupta, Varuna; Singhal, Abhinav; Srivastava, Shilpa

Description

In recent years, there has been a growing interest in leveraging machine learning techniques for the early detection and prediction of diseases affecting fruit crops. This study presents a comprehensive bibliometric analysis of research literature focused on fruit disease prediction using machine learning algorithms. Through systematic review and analysis of a large corpus of scholarly articles, conference papers, and patents, this paper aims to provide insights into the current trends, key research themes, influential authors, and popular machine learning methods in this domain. This paper conducts a literature review and bibliometric analysis to explore a significant increase in research activity in fruit disease prediction using machine learning, indicating the increasing importance of this area in agriculture and plant pathology. Various machine learning and deep learning algorithms, including convolutional neural network (CNN), decision trees, random forests and LSTM have been widely employed for disease prediction tasks. Moreover, the study identifies common datasets, evaluation metrics, and challenges encountered in this field. Overall, this bibliometric analysis provides valuable insights for researchers, practitioners, and policymakers interested in fruit disease prediction, highlighting opportunities for collaboration, innovation, and advancement in agricultural technology and plant health management. 2025 Author(s).

Source

AIP Conference Proceedings;Volume;3297;Issue;1;Article No.;286503;

Date

01-01-2025

Publisher

American Institute of Physics

Subject

deep leaning; Fruit disease; Prediction

Coverage

Kujur L., Christ University, Karnataka, Bangalore, India; Gupta V., Christ University, Karnataka, Bangalore, India; Singhal A., Christ University, Karnataka, Bangalore, India; Srivastava S., Christ University, Karnataka, Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 0094243X;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1063/5.0286503

https://www.scopus.com/pages/publications/105022823185?origin=resultslist