Proceedings
Authors
| Filter results3 paper(s) found. |
|---|
1. On-the-Go Nir Spectroscopy and Thermal Imaging for Assessing and Mapping Vineyard Water Status in Precision ViticultureNew proximal sensing technologies are desirable in viticulture to assess and map vineyard spatial variability. Towards this end, high-spatial resolution information can be obtained using novel, non-invasive sensors on-the-go. In order to improve yield, grape quality and water management, the vineyard water status should be determined. The goal of this work was to assess and map vineyard water status using two different proximal sensing technologies on-the-go: near infrared (NIR) reflectance spectroscopy... J. Tardaguila, M. Diago, S. Gutierrez, J. Fernandez-novales, E.A. Moreda |
2. Innovative Assessment of Cluster Compactness in Wine Grapes from Automated On-the-Go Proximal Sensing ApplicationGrape cluster compactness affects berry ripening homogeneity, fungal disease incidence, grape composition and wine quality. Therefore, assessing cluster compactness is crucial for sorting wine grapes for the wine industry. Nowadays, cluster compactness assessing methodology is based either on visual inspection performed by trained evaluators (OIV method) or on morphological features of clusters. The goal of this work was to develop an innovative and automated, non-destructive method to assess... J. Tardaguila, F. Palacios, M. Diago, E.A. Moreda |
3. In-season Nitrogen Prediction Evaluation Using Airborne Imagery with AI Techniques in Commercial Potato ProductionIn modern agriculture, timely and precise nitrogen (N) monitoring is essential to optimize resource management and improve trade benefits. Potato (Solanum tuberosum L.) is a staple food in many regions of the world, and improving its production is inevitable to ensure food security and promote related industries. Traditional methods of assessing nitrogen are labour-intensive, time-consuming, and require subjective observations. To address these limitations, a combination of multispectral... B. Javed, A. Cambouris, M. Duchemin, L. Longchamps, P.S. Basran, S. Arnold, A. Fenech, A. Karam |