专题:Plant Disease Management Techniques

This cluster of papers explores the advances in vegetable grafting techniques, including the use of grafting to improve tolerance to abiotic stresses, manage soilborne pathogens, enhance fruit quality, and promote disease resistance. It also delves into the mechanisms of rootstock-scion interactions, hormonal signaling, and genetic exchange in grafted plants. Additionally, the cluster discusses alternative strategies for soil disinfestation and the impact of grafting on plant responses to various environmental stressors.
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Using Machine Learning to Identify Diseases and Perform Sorting in Apple Fruit

article Full Text OpenAlex 963 FWCI501.1338

A survey on using deep learning techniques for plant disease diagnosis and recommendations for development of appropriate tools

article Full Text OpenAlex 348 FWCI63.2002

A fast accurate fine-grain object detection model based on YOLOv4 deep neural network

article Full Text OpenAlex 321 FWCI61.937

Soil Acidification caused by excessive application of nitrogen fertilizer aggravates soil-borne diseases: Evidence from literature review and field trials

article Full Text OpenAlex 314 FWCI52.7012

Deep learning and computer vision in plant disease detection: a comprehensive review of techniques, models, and trends in precision agriculture

review Full Text OpenAlex 306 FWCI359.775

A Novel Deep Learning Model for Detection of Severity Level of the Disease in Citrus Fruits

article Full Text OpenAlex 302 FWCI59.8478

A novel framework for potato leaf disease detection using an efficient deep learning model

article Full Text OpenAlex 300 FWCI55.2194

Intelligent robots for fruit harvesting: recent developments and future challenges

article Full Text OpenAlex 278 FWCI50.3905

A deep learning based approach for automated plant disease classification using vision transformer

article Full Text OpenAlex 274 FWCI48.7106

Plant Disease Identification Using a Novel Convolutional Neural Network

article Full Text OpenAlex 261 FWCI49.9703