AIMC Topic: Vitis

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Lightweight grape leaf disease recognition method based on transformer framework.

Scientific reports Aug 7, 2025
Grape disease image recognition is an important part of agricultural disease detection. Accurately identifying diseases allows for timely prevention and control at an early stage, which plays a crucial role in reducing yield losses. This study addres...
Plant Leaves Vitis Plant Diseases Algorithms Image Processing, Computer-Assisted
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YOLO-LeafNet: a robust deep learning framework for multispecies plant disease detection with data augmentation.

Scientific reports Aug 5, 2025
Plant diseases significantly harm crops, resulting in significant economic losses across the globe. In order to reduce the harm that these diseases produce, plant diseases must be diagnosed accurately and timely manner. In this work, a YOLO-LeafNet a...
Plant Diseases Image Processing, Computer-Assisted Zea mays Algorithms Capsicum Plant Leaves Deep Learning Vitis
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Fruit wines classification enabled by combing machine learning with comprehensive volatiles profiles of GC-TOF/MS and GC-IMS.

Food research international (Ottawa, Ont.) Feb 5, 2025
Fruit wines, produced through the fermentation of various fruits, are well-documented for their distinct flavor profiles. Intelligent sensory analysis, GC-TOF/MS and GC-IMS were used for the analysis of the volatile profile of eight types of fruit wi...
Neural Networks, Computer Vitis Fruit Gas Chromatography-Mass Spectrometry Machine Learning Wine Prunus persica Volatile Organic Compounds Fermentation Blueberry Plants Taste
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Real-Time Classification of Ochratoxin a Contamination in Grapes Using AI-Enhanced IoT.

Sensors (Basel, Switzerland) Jan 28, 2025
Ochratoxin A (OTA) contamination presents significant risks in viticulture, affecting the safety and quality of wine and grape-derived products. This study introduces a groundbreaking method for early detection and management of OTA, leveraging envir...
Artificial Intelligence Food Contamination Wine Vitis Ochratoxins
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Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach.

Scientific reports Jan 28, 2025
In agriculture, promptly and accurately identifying leaf diseases is crucial for sustainable crop production. To address this requirement, this research introduces a hybrid deep learning model that combines the visual geometric group version 19 (VGG1...
Vitis Plant Diseases Plant Leaves Capsicum Solanum lycopersicum Deep Learning Image Processing, Computer-Assisted
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Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of Grapevines.

Sensors (Basel, Switzerland) Jan 13, 2025
Assessing vines' vigour is essential for vineyard management and automatization of viticulture machines, including shaking adjustments of berry harvesters during grape harvest or leaf pruning applications. To address these problems, based on a standa...
Unmanned Aerial Devices Remote Sensing Technology Vitis Support Vector Machine Plant Leaves Machine Learning Geographic Information Systems
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A high-throughput ResNet CNN approach for automated grapevine leaf hair quantification.

Scientific reports Jan 10, 2025
The hairiness of the leaves is an essential morphological feature within the genus Vitis that can serve as a physical barrier. A high leaf hair density present on the abaxial surface of the grapevine leaves influences their wettability by repelling f...
Vitis Image Processing, Computer-Assisted Plant Leaves Neural Networks, Computer Algorithms Phenotype
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Artificial Intelligence Techniques in Grapevine Research: A Comparative Study with an Extensive Review of Datasets, Diseases, and Techniques Evaluation.

Sensors (Basel, Switzerland) Sep 25, 2024
In the last few years, the agricultural field has undergone a digital transformation, incorporating artificial intelligence systems to make good employment of the growing volume of data from various sources and derive value from it. Within artificial...
Vitis Plant Diseases Algorithms Agriculture Neural Networks, Computer Artificial Intelligence Machine Learning
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Enhancing agriculture through real-time grape leaf disease classification via an edge device with a lightweight CNN architecture and Grad-CAM.

Scientific reports Jul 11, 2024
Crop diseases can significantly affect various aspects of crop cultivation, including crop yield, quality, production costs, and crop loss. The utilization of modern technologies such as image analysis via machine learning techniques enables early an...
Plant Leaves Vitis Image Processing, Computer-Assisted Agriculture Neural Networks, Computer Crops, Agricultural Machine Learning Plant Diseases
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End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure.

Scientific reports Feb 29, 2024
Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for example, to assess plant health and quality and monitor physiological traits or diseases. However, detecting functional and degraded plant tissues in-vivo ...
Vitis Plant Diseases Artificial Intelligence Imaging, Three-Dimensional Machine Learning Workflow
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