Results 121 to 130 of about 1,983 (197)

EscaYard: Precision viticulture multimodal dataset of vineyards affected by Esca disease consisting of geotagged smartphone images, phytosanitary status, UAV 3D point clouds and Orthomosaics. [PDF]

Data Brief
Vélez S, Ariza-Sentís M, Valente J.
europepmc   +1 more source

The AI-viticulture nexus: Robotics and precision technologies for sustainable vineyards

Automation technologies, such as Artificial Intelligence (AI), robotics, IoT and remote sensing, are transforming viticulture by addressing labour shortages, climate resilience challenges and resource optimization.
Balachandar, D, Moganapathi, B, Kavitha, P S, Mahendran, P P, Muthuvel, I, Senthil, A   +5 more
core   +1 more source

Dataset of RGB images of healthy grapevine leaves and with downy mildew, powdery mildew, Esca complex, and erineum mite symptoms. [PDF]

Data Brief
Portela F, Carneiro G, Ferreira L, Paredes CA, Sousa JJ, Peres E, Morais R, Pádua L.   +7 more
europepmc   +1 more source

Phenological modeling for ecological double-cropping of grapes with rain and pest resilience strategies based on MobileNet developed by Augmented Dream Optimizer. [PDF]

Front Plant Sci
Gan X.
europepmc   +1 more source

Application of proximal and remote sensing on precision viticulture in Sardinia (Italy) – Preliminary results

, 2016
The anthocyanin content of colored grapes is a useful tool when making decisions in viticulture. The optical portable sensor Multiplex3® (FORCE-A, Paris, France) is a rapid and non-destructive method for screening the colored component of grapes.
Dore A, Guido V, Caria M, Sistu L, Piccirilli D, Pazzona A, Gambella F, Molinu M G   +7 more
core  

Preliminary Study of Vision-Based Artificial Intelligence Application to Evaluate Occupational Risks in Viticulture. [PDF]

Sensors (Basel)
Cividino SRS, Cappelli A, Belluco P, Rinaldi F, Avramovic L, Zaninelli M.   +5 more
europepmc   +1 more source

Direct UAV-Based Detection of <i>Botrytis cinerea</i> in Vineyards Using Chlorophyll-Absorption Indices and YOLO Deep Learning. [PDF]

Sensors (Basel)
Montalban-Faet G, Pérez-Mateo E, Fayos-Jordan R, Benlloch-Caballero P, Lada A, Segura-Garcia J, Garcia-Pineda M.   +6 more
europepmc   +1 more source

Experiences and Prospects of Precision Viticulture on Chianti terroir

, 2008
Gli autori riportano le esperienze del settore della ingegneria delle produzioni viticole nella valorizzazione del terroir. In particolare viene messa in evidenza l'esperienza di raccolta delle uve ocn controllo della qualità e relativa mappatura.
PAGNI, PIER PAOLO, G. Spezia, VIERI, MARCO   +2 more
openaire   +1 more source

Automated air-flow cytometry enables real-time monitoring of <i>Plasmopara viticola</i> sporangia in vineyards. [PDF]

Appl Environ Microbiol
Malvessi Cattani A, Zeder Y, Graf E, Schwendimann A, Coronelli R, Smit-Sadki T, Burdet J-P, Alfonso E, Jaccard A, Niederberger E, Rienth M.   +10 more
europepmc   +1 more source

TLS-grapevine2024: A terrestrial laser scanner point cloud dataset of grapevines at different phenological stages. [PDF]

Data Brief
Ferreira L, Marques P, Portela F, Sousa JJ, Peres E, Morais R, Pádua L.   +6 more
europepmc   +1 more source