| Autor: |
Borja Millan, Maria Paz Diago, Arturo Aquino, Fernando Palacios, Javier Tardaguila |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
OENO One, Vol 53, Iss 2 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2494-1271 |
| DOI: |
10.20870/oeno-one.2019.53.2.2416 |
| Popis: |
Aim: Pruning weight is an indicator of vegetative growth and vigour in grapevine. Traditionally, it is manually determined, which is time-consuming and labour-demanding. This study aims at providing a new, non-invasive and low-cost method for pruning weight estimation in commercial vineyards based on computer vision. Methods and results: The methodology relies on computer-based analysis of RGB images captured manually and on-the-go in a VSP Tempranillo vineyard. Firstly, the pruning weight estimation was evaluated using manually taken photographs using a controlled background. These images were analysed to generate a model of wood pruning weight estimation, resulting in a coefficient of determination (R2) of 0.91 (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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