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.
最新文献
Innovations in Agronomy and Their Impact on Greenhouse Vegetable Yields: Species-Specific Perspectives

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A hybrid SE-ResNet50 deep learning framework for high-accuracy and explainable cotton leaf disease classification

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Advancing site-specific disease and pest management in precision agriculture: From reasoning-driven foundation models to adaptive, feedback-based learning

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A Hybrid Deep Learning Approach for Mango Leaf Disease Classification: Integrating InceptionV3 and Vision Transformer

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A Transfer Learning-Based Fine-Tuned Hybrid Deep Learning Framework Combining ResNet101 and Vision Transformer (ViT-B16) Models for Enhanced Jackfruit Leaf Disease Classification and Detection

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Plant Genetic Engineering: Technological Pathways, Application Scenarios, and Future Directions

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Comparative Evaluation of Deep Features and Traditional Classifiers in the Detection of Potato Leaf Diseases

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Impact of dimethyl disulfide fumigation on soil nitrification and community assembly of ammonia-oxidizing archaea and bacteria

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Explainable and lightweight deep learning models for tea leaf disease detection: A systematic review and future research directions

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Advancing plant disease classification using an attention-based CNN for intra-dataset and cross- dataset training

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近5年高被引文献
Using Machine Learning to Identify Diseases and Perform Sorting in Apple Fruit

article Full Text OpenAlex 963 FWCI487.2683

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

article Full Text OpenAlex 388 FWCI337.8961

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

article Full Text OpenAlex 363 FWCI58.5911

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

article Full Text OpenAlex 333 FWCI48.8584

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

article Full Text OpenAlex 328 FWCI57.8125

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

article Full Text OpenAlex 312 FWCI51.5835

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

article Full Text OpenAlex 306 FWCI55.5191

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

article Full Text OpenAlex 284 FWCI45.1599

Intelligent robots for fruit harvesting: recent developments and future challenges

article Full Text OpenAlex 283 FWCI46.6703

Plant Disease Identification Using a Novel Convolutional Neural Network

article Full Text OpenAlex 269 FWCI46.7215