AIMC Topic: Vitis

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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
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...

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure.

Scientific reports
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 ...

Effects of grape juice intake on the cell migration properties in overweight women: Modulation mechanisms of cell migration in vitro by delphinidin-3-O-glucoside.

Food research international (Ottawa, Ont.)
Overweight and obesity are typical conditions of chronic low-intensity systemic inflammatory responses, and both have become more common in recent decades, which emphasizes the necessity for healthier diet intake. Fruits such as grapes are rich in an...

Taylor Remora optimization enabled deep learning algorithms for percentage of pesticide detection in grapes.

Environmental science and pollution research international
In the world, grapes are considered as the most significant fruit, and it comprises various nutrients, like Vitamin C and it is utilized to produce wines and raisins. The major six general grape leaf diseases and pests are brown spots, leaf blight, d...

A Deep Learning Approach for Precision Viticulture, Assessing Grape Maturity via YOLOv7.

Sensors (Basel, Switzerland)
In the viticulture sector, robots are being employed more frequently to increase productivity and accuracy in operations such as vineyard mapping, pruning, and harvesting, especially in locations where human labor is in short supply or expensive. Thi...

Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.

Molecules (Basel, Switzerland)
Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, an...

In-Field Automatic Detection of Grape Bunches under a Totally Uncontrolled Environment.

Sensors (Basel, Switzerland)
An early estimation of the exact number of fruits, flowers, and trees helps farmers to make better decisions on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on ma...

Spectrofluorometric analysis combined with machine learning for geographical and varietal authentication, and prediction of phenolic compound concentrations in red wine.

Food chemistry
Fluorescence spectroscopy is rapid, straightforward, selective, and sensitive, and can provide the molecular fingerprint of a sample based on the presence of various fluorophores. In conjunction with chemometrics, fluorescence techniques have been ap...

Research on nondestructive identification of grape varieties based on EEMD-DWT and hyperspectral image.

Journal of food science
Grape varieties are directly related to the quality and sales price of table grapes and consumed products (raisin, wine, grape juice, etc.). To satisfy the identification requirements of rapid, accurate, and nondestructive detection, an improved deno...

Non-invasive setup for grape maturation classification using deep learning.

Journal of the science of food and agriculture
BACKGROUND: The San Francisco Valley region from Brazil is known worldwide for its fruit production and exportation, especially grapes and wines. The grapes have high quality not only due to the excellent morphological characteristics, but also to th...