This PhD thesis investigates the potential and effectiveness of proximal and remote sensing systems in different agricultural scenarios, particularly in crop management and production processes. The research aims to support the development of advanced decision-support systems (DSS) for optimising control strategies involving new organic pesticide products. Specific attention is devoted to the optimisation of targeted distribution strategies for biologically derived plant protection products (PPPs), with the aim of increasing their efficiency and reducing their environmental impact. The research is organised into three chapters, each demonstrating how multitemporal surveys combined with advanced digital processing techniques can provide robust, efficient, and effective tools for monitoring and managing both perennial (grapevine) and horticultural (artichoke) crops. The findings highlight the reliability of these approaches for precision crop management and their suitability for organic agricultural practices.

This PhD thesis investigates the potential and effectiveness of proximal and remote sensing systems in different agricultural scenarios, particularly in crop management and production processes. The research aims to support the development of advanced decision-support systems (DSS) for optimising control strategies involving new organic pesticide products. Specific attention is devoted to the optimisation of targeted distribution strategies for biologically derived plant protection products (PPPs), with the aim of increasing their efficiency and reducing their environmental impact. The research is organised into three chapters, each demonstrating how multitemporal surveys combined with advanced digital processing techniques can provide robust, efficient, and effective tools for monitoring and managing both perennial (grapevine) and horticultural (artichoke) crops. The findings highlight the reliability of these approaches for precision crop management and their suitability for organic agricultural practices.

Distribution of biological products by autonomous platforms for weed control in Mediterranean agricultural systems

DEIDDA, ALESSANDRO
2026

Abstract

This PhD thesis investigates the potential and effectiveness of proximal and remote sensing systems in different agricultural scenarios, particularly in crop management and production processes. The research aims to support the development of advanced decision-support systems (DSS) for optimising control strategies involving new organic pesticide products. Specific attention is devoted to the optimisation of targeted distribution strategies for biologically derived plant protection products (PPPs), with the aim of increasing their efficiency and reducing their environmental impact. The research is organised into three chapters, each demonstrating how multitemporal surveys combined with advanced digital processing techniques can provide robust, efficient, and effective tools for monitoring and managing both perennial (grapevine) and horticultural (artichoke) crops. The findings highlight the reliability of these approaches for precision crop management and their suitability for organic agricultural practices.
27-feb-2026
Inglese
This PhD thesis investigates the potential and effectiveness of proximal and remote sensing systems in different agricultural scenarios, particularly in crop management and production processes. The research aims to support the development of advanced decision-support systems (DSS) for optimising control strategies involving new organic pesticide products. Specific attention is devoted to the optimisation of targeted distribution strategies for biologically derived plant protection products (PPPs), with the aim of increasing their efficiency and reducing their environmental impact. The research is organised into three chapters, each demonstrating how multitemporal surveys combined with advanced digital processing techniques can provide robust, efficient, and effective tools for monitoring and managing both perennial (grapevine) and horticultural (artichoke) crops. The findings highlight the reliability of these approaches for precision crop management and their suitability for organic agricultural practices.
FALCE, MICHELE
GAMBELLA, Filippo
Università degli studi di Sassari
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/359039
Il codice NBN di questa tesi è URN:NBN:IT:UNISS-359039