相关论文: Wine Characterisation with Spectral Information an…

Classifying wine as "good" is a challenging task due to the absence of a clear criterion. Nevertheless, an accurate prediction of wine quality can be valuable in the certification phase. Previously, wine quality was evaluated solely by…

One of the major goals of tomorrow's agriculture is to increase agricultural productivity but above all the quality of production while significantly reducing the use of inputs. Meeting this goal is a real scientific and technological…

The classification of different grapevine varieties is a relevant phenotyping task in Precision Viticulture since it enables estimating the growth of vineyard rows dedicated to different varieties, among other applications concerning the…

As an alcoholic beverage, wine has remained prevalent for thousands of years, and the quality assessment of wines has been significant in wine production and trade. Scholars have proposed various deep learning and machine learning…

Early detection of vine disease is important to avoid spread of virus or fungi. Disease propagation can lead to a huge loss of grape production and disastrous economic consequences, therefore the problem represents a challenge for the…

Grapevine varieties are essential for the economies of many wine-producing countries, influencing the production of wine, juice, and the consumption of fruits and leaves. Traditional identification methods, such as ampelography and…

Digital agriculture has evolved significantly over the last few years due to the technological developments in automation and computational intelligence applied to the agricultural sector, including vineyards which are a relevant crop in…

In table grape cultivation, harvesting depends on accurately assessing fruit quality. While some characteristics, like color, are visible, others, such as Soluble Solid Content (SSC), or sugar content measured in degrees Brix ({\deg}Brix),…

Nitrogen (N) is one of the most critical nutrients in winegrape production, influencing vine vigor, fruit composition, and wine quality. Because soil N availability varies spatially and temporally, accurate estimation of leaf N…

The extraction of phenotypic traits is often very time and labour intensive. Especially the investigation in viticulture is restricted to an on-site analysis due to the perennial nature of grapevine. Traditionally skilled experts examine…

In (grapevine) breeding programs and research, periodic phenotyping and multi-year monitoring of different grapevine traits, like growth or yield, is needed especially in the field. This demand imply objective, precise and automated methods…

This work proposes a framework using temporal data and domain knowledge in order to analyze complex agronomical features. The expertise is first formalized in an ontology, under the form of concepts and relationships between them, and then…

In viticulture, there are several applications where bud detection in vineyard images is a necessary task, susceptible of being automated through the use of computer vision methods. A common and effective family of visual detection…

This study examines the role of Artificial Intelligence (AI) in enhancing sustainability and efficiency within the wine industry. It focuses on AI-driven intelligent management in viticulture, wine production, and enotourism. As the wine…

Crops hold paramount significance as they serve as the primary provider of energy, nutrition, and medicinal benefits for the human population. Plant diseases, however, can negatively affect leaves during agricultural cultivation, resulting…

Agricultural applications such as yield prediction, precision agriculture and automated harvesting need systems able to infer the crop state from low-cost sensing devices. Proximal sensing using affordable cameras combined with computer…

This paper presents an end-to-end, IoT-enabled robotic system for the non-destructive, real-time, and spatially-resolved mapping of grape yield and quality (Brix, Acidity) in vineyards. The system features a comprehensive analytical…

Confronting the critical challenge of insufficient training data in the field of complex image recognition, this paper introduces a novel 3D viewpoint augmentation technique specifically tailored for wine label recognition. This method…

A major unaddressed challenge for food science remains the accurate characterisation of contents in sealed containers with a non-invasive method. This issue is particularly pressing for tackling fraud in the red wine industry, valued at…

We present WineSensed, a large multimodal wine dataset for studying the relations between visual perception, language, and flavor. The dataset encompasses 897k images of wine labels and 824k reviews of wines curated from the Vivino…