This paper presents a survey on methods that use digital image processing techniques to
detect, quantify and classify plant diseases from digital images in the visible spectrum …

There is intense pressure on agricultural productivity due to the ever‐growing population.
Several diseases affect crop yield and thus, effective control of these can significantly …

Tomato production can be greatly reduced due to various diseases, such as bacterial spot,
early blight, and leaf mold. Rapid recognition and timely treatment of diseases can minimize …

In this paper, we address a comprehensive study on disease recognition and classification
of plant leafs using image processing methods. The traditional manual visual quality …

The rapid, recent development of image recognition technologies has led to the widespread
use of convolutional neural networks (CNNs) in automated image classification and in the …

This study evaluated the potential of using machine vision in combination with deep learning
(DL) to identify the early blight disease in real-time for potato production systems. Four fields …

This manuscript represents a study and methods the use of digital image processing method
to identify and classify crops diseases. It's show by digital image in the observable spectrum …

Anthracnose crown rot (ACR) is one of the major diseases affecting strawberry crops grown
in warm climates and causes huge yield losses each year. ACR is caused by the fungus …

Fusarium damage in wheat reduces the quality and safety of associated food and feed
products. In this study, a specific Fusarium head blight (FHB) classification index (FCI) for …

Lettuce is one of the most widely planted leafy vegetables in plant factories. The lack of trace
elements in nutrient solutions has caused huge losses to the lettuce industry. Non-obvious …