Article

Remote Sensed Spectral Imagery to Detect Late Blight in Field Tomatoes

2005-12-01

Abstract excerpt

Late blight, caused by the fungal pathogen Phytophthora infestans, is a disease that quickly spreads in tomato fields under suitable weather conditions and can threaten the sustainability of tomato farming in California, USA. This paper explores the applicability of remotely sensed images to detect disease spectral anomalies for precision disease management. We used the indices approach and generated a 5-index ima...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 18b54d17-deab-547c-8f37-8cc6c2c46763
DOI: 10.1007/s11119-005-5640-x

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Remote Sensed Spectral Imagery to Detect Late Blight in Field TomatoesDOI 10.1007/s11119-005-5640-xRead

Advanced Disease Monitoring and Severity Quantification for Greenhouse Management Using Multispectral ImagingSemantic proximity Read

Automatic late blight lesion recognition and severity quantification based on field imagery of diverse potato genotypes by deep learningSemantic proximity Read

Detection of tomato disease using texture features and genetic bee colony algorithmSemantic proximity Read

Prediction of late blight severity in a large panel of potato genotypes using low-altitude aerial images and machine learning methodsSemantic proximity Read

Detection of grapevine leafroll disease based on 11-index imagery and ant colony clustering algorithmSemantic proximity Read

An Improved YOLOv5 for Accurate Detection and Localization of Tomato and Pepper Leaf DiseasesSemantic proximity Read

A Comprehensive Image Dataset of Fruit and Leaf Diseases Across Six Horticultural Crops for Deep Learning ApplicationsSemantic proximity Read

Deep Learning for Tomato Disease Detection and Severity Assessment: A Systematic Analytical Review of Methods, Datasets, and ChallengesSemantic proximity Read

An Efficient Dynamic Deep Learning Methodology for Identification of Plant Disease and it’s classificationSemantic proximity Read

Aiming at decision making in plant disease protection and phenotyping by the use of optical sensorsSemantic proximity Read

Deep Learning for Early Disease Detection: A CNN Approach to Classify Potato, Tomato, and Pepper Leaf DiseasesSemantic proximity Read

Towards high throughput in-field detection and quantification of wheat foliar diseases with deep learningSemantic proximity Read