research paper on plant disease

According to the difference of network structure, this study outlines the research on plant diseases and pests detection based on deep learning in recent years from three aspects of classification network, detection network and segmentation network, and the advantages and disadvantages of each method are summarized.

In this Review, we examine how plant disease pressures are likely to change under future climate scenarios and how these changes will relate to plant productivity in natural and agricultural...

Detecting plant diseases at an early stage is crucial, and this research paper proposes a deep convolutional neural network model that can rapidly and accurately identify plant diseases.

Existing techniques for detection of plant diseases have been reviewed, and an overview of innovative methods enabling identification of symptoms and preventive actions against pathogens spreading has been provided.

Plant disease quantification, mainly the intensity of disease symptoms on individual units (severity), is the basis for a plethora of research and applied purposes in plant pathology and related disciplines. These include evaluating treatment effect, monitoring epidemics, understanding yield loss, and phenotyping for host resistance.

A lightweight deep learning approach is proposed based on the Vision Transformer (ViT) for real-time automated plant disease classification.

The automated plant disease detection systems suggest identifying and categorizing plant diseases by fusing CNNs with the expertise of phytopathology specialists and the capacity to extract symptomatic signals.

Plant Disease is the leading international journal for rapid reporting of research on new, emerging, and established plant diseases. The journal publishes papers that describe translational and applied research focusing on practical aspects of disease diagnosis, development, and management in agricultural and horticultural crops.

Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof).

Plant pathogens cause plant diseases that significantly decrease crop yields, posing a serious threat to global food security. While plant disease resistance has traditionally been understood as the trait determined by the plant innate immune system and the pathogen virulence system, recent research underscores the pivotal role of the plant microbiome in disease resistance. Plant-associated ...