The importance of studying various aspects of Integrated Pest Management (IPM) cannot be overlooked, as it represents a multifaceted approach crucial for sustainable agriculture. Investigating insect behavior at different trophic levels is fundamental for enhancing biocontrol strategies. A comprehensive understanding of the reproductive behavior of key biocontrol organisms enables the development of more effective pest management techniques. Simultaneously, the exploration of the role of abiotic stressors, including UV-B radiation and electromagnetic fields (EMFs), provides insights into their potential impact on insect physiology and behavior, influencing the dynamics of ecological interactions. Additionally, the integration of precision agriculture techniques, exemplified by advanced monitoring technologies and deep learning applications, enhances the efficacy of IPM programs. These technologies contribute to timely and accurate pest detection, facilitating the implementation of intervention strategies based on climate parameters and crop conditions. The imperative of developing green insecticides is underscored by the environmental consequences of synthetic alternatives. The study of novel environmentally friendly pesticides, such as essential oils, not only addresses the need for effective pest management but also emphasizes the importance of comprehending their sub-lethal effects on insect life-history traits and behaviors. The pursuit of green insecticides aligns with the broader goal of creating sustainable and ecologically alternatives for pest control in agriculture. In a nutshell, a holistic exploration of insect behavior, innovative monitoring techniques, and the development of green insecticides collectively contribute to the advancement of IPM, fostering environmentally friendly and economically viable approaches to crop protection.

Behavioural insights and biocontrol of arthropod pests of fruit and horticultural crops in the Mediterranean area

ZENI, VALERIA
2024

Abstract

The importance of studying various aspects of Integrated Pest Management (IPM) cannot be overlooked, as it represents a multifaceted approach crucial for sustainable agriculture. Investigating insect behavior at different trophic levels is fundamental for enhancing biocontrol strategies. A comprehensive understanding of the reproductive behavior of key biocontrol organisms enables the development of more effective pest management techniques. Simultaneously, the exploration of the role of abiotic stressors, including UV-B radiation and electromagnetic fields (EMFs), provides insights into their potential impact on insect physiology and behavior, influencing the dynamics of ecological interactions. Additionally, the integration of precision agriculture techniques, exemplified by advanced monitoring technologies and deep learning applications, enhances the efficacy of IPM programs. These technologies contribute to timely and accurate pest detection, facilitating the implementation of intervention strategies based on climate parameters and crop conditions. The imperative of developing green insecticides is underscored by the environmental consequences of synthetic alternatives. The study of novel environmentally friendly pesticides, such as essential oils, not only addresses the need for effective pest management but also emphasizes the importance of comprehending their sub-lethal effects on insect life-history traits and behaviors. The pursuit of green insecticides aligns with the broader goal of creating sustainable and ecologically alternatives for pest control in agriculture. In a nutshell, a holistic exploration of insect behavior, innovative monitoring techniques, and the development of green insecticides collectively contribute to the advancement of IPM, fostering environmentally friendly and economically viable approaches to crop protection.
5-feb-2024
Italiano
AI
ethology
parasitoid
physiology
predators
Benelli, Giovanni
Canale, Angelo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/216714
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-216714