Citation

C., Pabitha and B., Vanathi and K., Revathi and S., Benila (2025) Enhancing Citrus Plant Health through the Application of Image Processing Techniques for Disease Detection. Journal of Informatics and Web Engineering, 4 (2). pp. 53-63. ISSN 2821-370X

Text View of Enhancing Citrus Plant Health through the Application of Image Processing Techniques for Disease Detection.pdf - Published Version Restricted to Repository staff only Download (3MB)

Abstract

The foremost task in agriculture is the decisive identification of citrus plants and the timely identification of diseases inthe plants with the aim of improving the quality of crops and the yield. In this work, a machine learning algorithmfocuses on image processing of citrus to solveissues that are significant and cause concern in agriculture. This workfocus on the machine learning models like VGG 19 and VGG 16. In addition, dataset curation, data augmentation and various other methods were employed. The dataset used in thisresearch is acomposed one which isrecorded in a comprehensive manner includingthe data of both the affected and healthy pieces of citrus fruits. The ensemble model utilised here to ensure theimprovement of trained datasets. Reviewing the research on machine learning models indicates a possibility for accurate classification of the fruits and disease detection models of the fruit. The three contenders performed admirably, with VGG 19 dominating with 95.5% accuracy. In second place was CNN with 93.4% and VGG 16 trailing at 91.2%. Such models are recognisable, because they perform well in agricultural environments, thanks to their precision, recall, and F1 scores, which are all balanced properly.The models’ capacity to lessen the number of false alarms and misses is further assessed with the use of confusion matrices, which are of utmost importance in disease control. New developments in early disease diagnosis and detection of citrus fruits in agriculture may greatly enhance the health and productivity of crops. This research can be critical in increasing agricultural productivity while ensuring the environmental sustainability and health of growers and citrus crops in the long run

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	25 Jun 2025 07:37
Last Modified:	25 Jun 2025 07:37
URII:	http://shdl.mmu.edu.my/id/eprint/14009

Downloads

Edit (login required)