This thesis explores the application of precision viticulture and artificial intelligence (AI) technologies to optimize vineyard agronomic management. Viticulture, especially significant in Mediterranean regions, faces increasing threats from extreme climate events, such as heatwaves and drought. The adoption of precision agriculture (PA), supported by remote sensing technologies, including unmanned aerial vehicles (UAV) and proximal sensors, allows for accurate grapevine physiological status monitoring, improving resource efficiency and reducing environmental impact. The main objective of this research was to develop innovative agronomic protocols using advanced algorithms and spectral data to accurately model grapevine growth. Among the key topics addressed is the application of innovative canopy segmentation methodologies using deep learning, which significantly improved the accuracy of vegetation index-derived information and enabled a detailed assessment of plant vigor. The results demonstrated the effectiveness of these approaches in identifying three distinct vineyard vigor levels, offering new perspectives for agronomic management. The analyses revealed significant correlations between agronomic variables and vegetation indices, confirming their use as predictive indicators of yield and shoot pruning weight, which is a pivotal parameter for vine vigor assessment. In addition, research has highlighted the defining role of cover crops in sustainable vineyard management, showing a positive correlation between the vigor of cover crops and grapevine growth. In conclusion, this thesis demonstrates that integrating AI and advanced technologies is a valuable tool for addressing current and future viticulture challenges, providing practical insights to make these solutions more accessible to agricultural operators, with the goal of fostering broader adoption and enhancing the economic efficiency of wine-growing enterprises. In conclusion, this thesis demonstrates that the integration of AI and advanced technologies is a valuable tool to address current and future challenges in viticulture, providing practical insights to make these solutions more accessible to agricultural operators, with the goal of fostering wider adoption and improving the economic efficiency of viticulture.
(2024). APPLICATIONS OF UAV MULTISPECTRAL IMAGING AND DIGITAL TECHNOLOGIES IN PRECISION VITICULTURE.
APPLICATIONS OF UAV MULTISPECTRAL IMAGING AND DIGITAL TECHNOLOGIES IN PRECISION VITICULTURE
FERRO, Massimo Vincenzo
2024-11-19
Abstract
This thesis explores the application of precision viticulture and artificial intelligence (AI) technologies to optimize vineyard agronomic management. Viticulture, especially significant in Mediterranean regions, faces increasing threats from extreme climate events, such as heatwaves and drought. The adoption of precision agriculture (PA), supported by remote sensing technologies, including unmanned aerial vehicles (UAV) and proximal sensors, allows for accurate grapevine physiological status monitoring, improving resource efficiency and reducing environmental impact. The main objective of this research was to develop innovative agronomic protocols using advanced algorithms and spectral data to accurately model grapevine growth. Among the key topics addressed is the application of innovative canopy segmentation methodologies using deep learning, which significantly improved the accuracy of vegetation index-derived information and enabled a detailed assessment of plant vigor. The results demonstrated the effectiveness of these approaches in identifying three distinct vineyard vigor levels, offering new perspectives for agronomic management. The analyses revealed significant correlations between agronomic variables and vegetation indices, confirming their use as predictive indicators of yield and shoot pruning weight, which is a pivotal parameter for vine vigor assessment. In addition, research has highlighted the defining role of cover crops in sustainable vineyard management, showing a positive correlation between the vigor of cover crops and grapevine growth. In conclusion, this thesis demonstrates that integrating AI and advanced technologies is a valuable tool for addressing current and future viticulture challenges, providing practical insights to make these solutions more accessible to agricultural operators, with the goal of fostering broader adoption and enhancing the economic efficiency of wine-growing enterprises. In conclusion, this thesis demonstrates that the integration of AI and advanced technologies is a valuable tool to address current and future challenges in viticulture, providing practical insights to make these solutions more accessible to agricultural operators, with the goal of fostering wider adoption and improving the economic efficiency of viticulture.File | Dimensione | Formato | |
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