Corn Leaf Diseases

## Overview

Corn Leaf Diseases is a dataset for classification tasks - it contains Corn Leaf annotations for 4,186 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

A dataset for classification of corn or maize plant leaf diseases

Dataset Description:

• 0: Common Rust - 1306 images
• 1: Gray Leaf Spot - 574 images
• 2: Blight -1146 images
• 3: Healthy - 1162 images

Note:

This dataset has been made using the popular PlantVillage and PlantDoc datasets. During the formation of the dataset certain images have been removed which were not found to be useful. The original authors reserve right to the respective datasets. If you use this dataset in your academic research, please credit the authors.

Citations:

1. Singh D, Jain N, Jain P, Kayal P, Kumawat S, Batra N. PlantDoc: a dataset for visual plant disease detection. InProceedings of the 7th ACM IKDD CoDS and 25th COMAD 2020 Jan 5 (pp. 249-253).

2. J, ARUN PANDIAN; GOPAL, GEETHARAMANI (2019), “Data for: Identification of Plant Leaf Diseases Using a 9-layer Deep Convolutional Neural Network”, Mendeley Data, V1, doi: 10.17632/tywbtsjrjv.1

Corn Leaf Disease

## Overview

Corn Leaf Disease is a dataset for object detection tasks - it contains Objects annotations for 1,830 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Maize leaf spot, also known as stripe spot, coal sheath, blight, leaf spot. The main symptoms of maize leaf blight are maize leaves. Water-stained grey-blue spots appeared on the lower leaves first, then spread along the veins to both ends. The lesions were long shuttle-shaped, light brown in the center and dark brown in the outer edge. When the wetness was high in the field, grey-black moulds appeared on the surface of the lesions. In severe cases, the lesions fuse, causing the whole leaf to die. [Control methods] Maize hybrids with resistance to both large and small spot diseases were selected as Jingzao 7 and Guidan 16. Implementing rotation cropping system to avoid continuous cropping of maize, deep ploughing of soil in autumn, deep burying of diseased stubble and eliminating bacterial sources; maize straw used as fuel is treated as early as possible after spring, and corn borer can be treated simultaneously; diseased stubble should be fully matured as compost, and straw fertilizer should not be applied in Maize fields. Improving cultivation techniques and enhancing disease resistance of summer maize early sowing can significantly reduce the incidence of disease. Appropriate application of phosphorus fertilizer, proper combination of nitrogen, phosphorus and potassium fertilizer, re-application of bell mouth fertilizer, implementation of maize-soybean intercropping, or intercropping with wheat, peanuts, sweet potatoes and other crops, wide and narrow row planting; rational irrigation, attention to field drainage in low-lying areas. Due to the limitation of objective conditions such as plant height and density, spraying control can focus on the high-yielding experimental fields such as seed production and intercropping fields. Generally, before and after maize bolting, when the disease rate in the field is over 70% and the disease leaf rate is about 20%, spraying begins. The effective insecticides are: 50% carbendazim wettable powder, 50% carbendazim wettable powder or 90% mancozeb, adding 500 times water, or 40% grams of aerosol powder 800 times the spray. Each mu of medicinal liquid 50-75 kg, spraying once every 7-10 days, a total of 2-3 times of prevention and control.

Corn Maize Leaf Disease

## Overview

Corn Maize Leaf Disease is a dataset for classification tasks - it contains Corn annotations for 4,186 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The Corn Leaf Infection Dataset contains over 1,000 high-resolution images of corn leaves, categorized into healthy and pest-infected classes. Infected samples include pests such as the Fall Armyworm, with annotations created using VoTT. The dataset is designed to support AI-based solutions for crop health monitoring and pest detection.

Dataset Card for "maize-leaf-disease"

More Information needed

In this dataset lies 2355 images of maize leaves with different diseases. The images were taken over a variety of times and locations in South Africa. The diseases labelled herein are:

Grey Leaf Spot (GLS) Northern Corn Leaf Blight (NCLB) Common Rust (CR) Southern Rust (SR) Phaeosphaeria Leaf Spot (PLS)

The data contains a realistic representation of field conditions where it shows images of leaves destroyed by bugs, protein deficiencies, leaves with hands occluding them, different lighting conditions, some leaves are wet, backgrounds vary wildly, anthers, bird droppings, several simultaneous and sometimes even overlapping diseases.The Readme.txt or the file description of the parent folder gives more details as to how the images are stored and annotated.

Corn Leaf Disease Detection

## Overview

Corn Leaf Disease Detection is a dataset for object detection tasks - it contains Corn Leaf Disease Rust Disease Fjq0 annotations for 2,685 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset contains 4,776 augmented corn leaf disease images generated using a Reinforcement Learning–based Neural Style Transfer (RL-NST) framework. The images extend existing resources, including PlantVillage, CCMT, and field-collected samples. The dataset contains: Common Rust (960), Leaf Blight (783), Leaf Spot (944), Streak Virus (1,890), and Healthy (199). All images are in JPEG format with standardized resolution, intended for training and benchmarking deep learning models for plant disease detection.

The RL-NST implementation code is available at: https://github.com/kanch-git/RL-NST/

Maize Leaf Diseases

## Overview

Maize Leaf Diseases is a dataset for classification tasks - it contains Maize annotations for 4,186 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset

This dataset was created by Khaoula E.

Contents

The dataset consists of two parts: leaf disease image data and corresponding text description data, totaling 1653 sets. Among them, the image modal data is sourced from open source datasets such as AI Challenger, Plant Village, OpenDataLab (CD&S), as well as existing self built, jointly constructed, and purchased sources. High definition images of nine typical leaf diseases, including large spot disease, small spot disease, brown spot disease, curved mold leaf spot disease, common rust disease, southern rust disease, gray spot disease, round spot disease, and dwarf mosaic disease, have been collected and organized; The text modality involves manually annotating diagnostic text descriptions of images based on prior knowledge such as literature, professional books, and scientific data. The content of the text modality covers key information such as disease types, pathological features, and severity.

Corn Leaf Diseases Annotation

## Overview

Corn Leaf Diseases Annotation is a dataset for instance segmentation tasks - it contains Leaf annotations for 2,142 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This dataset contains images of multiple types of crop leafs with both healthy and diseased samples. The dataset is designed for plant disease detection, classification, and deep learning applications in agriculture.

Crops Covered: Corn, Potato, Rice, Tomato, Cashew Categories: Healthy and diseased leafs Data Format: JPG images, organized by crop and disease type Total Images: 6895 Image Resolution: 400 × 400

Special thanks to:

https://www.kaggle.com/datasets/smaranjitghose/corn-or-maize-leaf-disease-dataset

Citations: Singh D, Jain N, Jain P, Kayal P, Kumawat S, Batra N. PlantDoc: a dataset for visual plant disease detection. InProceedings of the 7th ACM IKDD CoDS and 25th COMAD 2020 Jan 5 (pp. 249-253).

J, ARUN PANDIAN; GOPAL, GEETHARAMANI (2019), “Data for: Identification of Plant Leaf Diseases Using a 9-layer Deep Convolutional Neural Network”, Mendeley Data, V1, doi: 10.17632/tywbtsjrjv.1

The application of Artificial Intelligence (AI) has been evident in the agricultural sector recently. The main goal of AI in agriculture is to improve crop yield, control crop pests/diseases, and reduce cost. The agricultural sector in developing countries faces severe in the form of disease and pest infestation, the knowledge gap between farmers and technology, and a lack of storage facilities, among others. To help address some of these challenges, this work presents crop pests/disease datasets sourced from local farms in Ghana. The dataset is presented in two folds; the raw images which consists of 24,881 images ( 6,549-Cashew, 7,508-Cassava, 5,389-Maize, and 5,435-Tomato) and augmented images which is further split into train and test set consists of 102,976 images (25,811-Cashew, 26,330-Cassava, 23,657-Maize, and 27,178-Tomato), categorized into 22 classes. All images are de-identified, validated by expert plant virologists, and freely available for use by the research community.

Corn rust. Corn rust is an important disease in South and Southwest China. It mainly infects leaves, ears, bracts and even male flowers in severe cases. In the early stage, only light yellow long to oval Brown pustular scars were scattered on both sides of the leaves, and then the bullae ruptured and the rust powder, i.e. summer spores, was scattered. In the later stage, black near-circular or Long-circular protuberances appeared on the lesions, and black-brown winter embroiders appeared after cracking. [Control methods]. [Planting disease-resistant varieties] The resistance of different maize varieties to rust is quite different, and using disease-resistant varieties is an effective way to control maize rust. [Scientific field management] timely sowing; appropriate reduction of nitrogen fertilizer, increased application of phosphorus and potassium fertilizer, timely spraying of foliar nutrients to improve disease resistance of maize plants; rational control of density, improve permeability. Early removal of plant debris in and around the field before planting, if found in the growing period should be timely pulled out and centralized destruction, maize harvest should also be timely removal of residual plants, stems and leaves, centralized burning or fertilization. Rotation and non-gramineous crop rotation can reduce the accumulation of pathogens. For sporadic maize, the diseased plants and residual disease bodies should be pulled out at any time. [Pharmaceutical control, prevention mainly] Spraying agents containing difenoconazole, tebuconazole, triazolone, propiconazole, pyrimethyl ester, ethermycin ester and pyrazole ether ester can effectively alleviate the occurrence of Southern rust in late stage of maize trumpet-silking. Prevention plan: in order to prevent the occurrence of Southern rust, farmers can use 25% powder, 20%, three zolone pesticide spray control. If there is no prevention in the early stage, spraying in the early stage of rust can also control the incidence of rust and reduce the impact on production to a certain extent.

This Dataset focuses on Leaf Disease Detection to identify and classify diseases affecting plant leaves. The goal is to develop a method for early detection, improving agricultural practices, reducing pesticide use, and increasing crop yields. The study includes four plant species: ● Beans (2032)
● Corn ( 706) ● Red Amaranth (401) Location: Leaf images, both healthy and diseased, were collected from different sources Located in Bangladesh.

Dataset Amount: 1.Original Data: 3139

The dataset consists of visual images aimed at training models for disease detection and classification.