International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 06 | Jun 2025
p-ISSN: 2395-0072
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Plant Disease Detection Using Machine Learning Suyash Mane1, Shreyash Chavare2, Sarvesh Redekar3 1 B.E. Student, Dept. of Computer Science and Engineering (Artificial Intelligence and Machine Learning), S.S.P.M’s
College of Engineering, Kankavli, Maharashtra, India
2 B.E. Student, Dept. of Computer Science and Engineering (Artificial Intelligence and Machine Learning), S.S.P.M’s
College of Engineering, Kankavli, Maharashtra, India
3 B.E. Student, Dept. of Computer Science and Engineering (Artificial Intelligence and Machine Learning), S.S.P.M’s
College of Engineering, Kankavli, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------model learns from these images and can correctly tell what Abstract - This project uses deep learning to detect plant
disease a plant has. This system can also be added to mobile or web apps, so farmers can use it anytime to check their crops.
diseases from leaf images using a method called Convolutional Neural Networks (CNN). The goal is to build a smart and reliable system that can find and recognize different plant leaf diseases easily and accurately. Finding plant diseases early is very important for farmers because it helps protect crops and avoid big losses. The model is trained on a public dataset that contains many pictures of healthy and sick plant leaves. Before training, the images are processed by resizing and enhancing them to make the model work better. CNN automatically learns useful features from the images, so we don’t need to manually choose them. The model's performance is tested using measures like accuracy and precision. It gives very good results in detecting various diseases. This system can be helpful for farmers by giving quick and correct information about plant health. It can also be added to mobile or web apps, so it can be used anytime and anywhere. This project supports smart farming by giving a fast, low-cost, and easy solution to check crops and improve farming methods.
This project gives farmers and agriculture workers a smart and easy tool to check plant health. It also helps modern farming by using technology to grow better and healthier crops.
2. .LITERATURE REVIEW Many people have done research on finding plant diseases by using pictures of leaves. In the past, experts had to look at the leaves with their own eyes to find out what disease the plant had. This method takes a lot of time and is not always possible, especially in villages where experts may not be available. Later, computer methods like Support Vector Machines (SVM) and k-Nearest Neighbours (k-NN) were used. These needed people to choose important parts of the leaf image by hand before training the model. This was not always easy or accurate.
Key Words: Plant Disease Detection, Deep Learning, CNN, Leaf Image, Smart Farming, Image Processing, Crop Health, Agriculture
1.INTRODUCTION
Now, deep learning methods like Convolutional Neural Networks (CNN) are used. CNN can learn directly from images and find patterns without any manual work. Many researchers have used CNN to detect plant diseases and got good results. Most of them used the Plant Village dataset, which has images of plants like tomato, potato, and grape.
Farming is very important for India and the whole world. One big problem farmers face is plant diseases. These diseases can damage crops and reduce the amount and quality of food. If these diseases are found early, farmers can save their plants and avoid losing money. But checking for diseases by hand takes time and needs experts, which is not always possible for farmers, especially in villages.
But most of these projects focus only on a few common plants. Our project is different because we also added leaf images of mango, coconut, and cashew plants. These are important crops in India, but not many research papers have used them. Finding diseases early in these plants can help farmers a lot.
Now, with the help of technology like Artificial Intelligence (AI) and Deep Learning, we can create smart systems that find plant diseases by just looking at pictures of leaves. A special method called Convolutional Neural Networks (CNN) is very good at learning from images without any manual effort.
By using more types of plants and leaf images, our project becomes more useful and can help more farmers in real life.
In this project, we made a CNN model that can detect different plant diseases from leaf images. We used a free dataset with images of healthy and diseased leaves. The
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