Skip to content
Open access

Detect Plant Disease and Recommend Fertilizer and Supplement Using CNN & Mobile Net Algorithm

Jul 2026 · International Journal for Research in Applied Science and Engineering Technology · Vol 14, pp. 1665-1671 · 0 citations

TL;DR

A method that which is detecting the disease of a tomato plant from their leaf images is proposed with the deep learning algorithms Convolutional Neural Network (CNN), and MobileNet which is a one of the transfer learning method of CNN.

Abstract

Agriculture plays a crucial role in the Indian economy. Early detection of plant diseases is very much essential to prevent crop loss and further spread of diseases. Most plants such as apple, tomato, cherry, grapes show visible symptoms of the disease on the leaf. These visible patterns can be identified to correctly predict the disease and take early actions to prevent it. This can be overcome by the use of machine learning and deep learning algorithms. Hence, we are proposing a method that which is detecting the disease of a tomato plant from their leaf images. Here the process is performed with the deep learning algorithms Convolutional Neural Network (CNN), and MobileNet which is a one of the transfer learning method of CNN. Once after training the dataset with the algorithms, the accuracy of algorithms is compared and the images are classified. And the precautions are also provided for the classified plant.

Read PDF

Similar papers

Plant Disease Detecting System Using CNN

The Plant Disease Detecting System leverages advances in artificial intelligence and deep learning to provide an automated, efficient, and reliable solution for identifying plant diseases at an early stage and contributes to increased crop productivity, reduced chemical usage, and sustainable farming practices.

K. Maithili · 0 citations
Open access Jul 2026

Automated Detection and Classification of Vegetable Leaf Disease using Machine Learning Techniques

The proposed automated leaf disease detection system using image processing and deep learning techniques can detect leaf diseases effectively and efficiently, making it a useful and cost-effective solution for supporting farmers and agricultural experts in early disease diagnosis.

Shilpa T. S., K. U, Anusha Jajur J · 0 citations
Open access Sep 2026

Deep Learning-based Classification of Tomato Leaf Diseases

Background: In the Indian economy agriculture plays important role. Many of the crops are damaged due to diseases, therefore plant leaf disease detection at early stage is important. Tomatoes are the second most consumed vegetable in Indian households, with a rank second largest producer and consumption in world. Tomat...

V. Nemade, V. Fegade, Deepti Barhate et al. · 0 citations
Conference Jul 2026

A Hybrid Deep Learning Approach for Plant leaf Disease Detection and Classification using YOLO and Transformer-based CNN

Plant leaf diseases are known to affect agricultural productivity and food security on a global level. "Therefore, the detection and diagnosis of diseases are important aspects of maintaining the health of crops on a sustainable level. Traditionally, the detection of diseases in plants is performed manually by experts....

Adilikitha Ravinuthala, Kandula Kavya Sree, Chinna Gopi Simhadri · 0 citations
Open access Jul 2026

Advanced Deep Learning Approaches for Image-based Diagnosis of Banana Leaf Diseases

The state-of-the-art deep learning methods for detection and classification are applied on banana leaf dataset and healthy and two common diseases of banana leaves are classified in this work.

N. Vidhya, R. Priya · 0 citations
Aug 2026

Integration of CNN and Random Forest Classifier for Detecting Tomato Diseases

Plant diseases, particularly in tomato crops pose a significant threat to agricultural productivity which results in yield losses, accounting for an estimated 10-30% of global tomato production annually. In this era characterized by technological advancement farmers continue to follow traditional practices regarding di...

Isaac Phiri, Regi Anbumozhi Y., Esther J. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.