Abstract
In the face of a surging global population, the imperative to secure a resilient food supply has reached a critical juncture, magnified by the looming threats of epidemics and the far-reaching impacts of climate change. Simultaneously, the drive for economic development accentuates the urgency of optimizing the judicious use of natural resources. This challenge is further compounded by the scarcity of new agricultural areas, intensifying the imperative to enhance productivity within existing land units. Navigating these intricate challenges, the amplification of almond and walnut cultivation emerges as a pivotal strategy, offering a multifaceted solution to the complexities of global food security while steadfastly championing sustainable resource management. This initiative, driven by state-of-the-art U-Net-driven machine learning, is steadfastly dedicated to elevating both productivity and sustainability within the almond and walnut cultivation sector. Its key objectives include maximizing energy consumption, responding swiftly to potential hazard factors, and ensuring correctness in estimates. By exploiting U-Net’s powerful deep learning capabilities, we pioneer prediction models that significantly enhance energy efficiency in almond and walnut harvest. Furthermore, as proven by the models provided, producers have real-time access to data on energy consumption trends, allowing them to make informed resource allocation decisions. Furthermore, we harness U-Net’s prowess to extend its application to the critical realm of evaluating orchard damage. Our solution guarantees unparalleled accuracy in identifying, categorizing, and mitigating damage caused by environmental conditions, pests, and illnesses through the seamless integration of machine learning and image analysis. This agricultural prowess facilitates precise yield preservation and swift, informed reactions. Our research establishes a comprehensive framework for sustainable practices and furnishes recommendations for maximizing energy efficiency, controlling crop health, and making judicious choices. These transformative outcomes hold profound implications, particularly for the almond and walnut industries. The present research signifies the inauguration of a new era in precision farming for almond and walnut production, showcasing how cutting-edge technology seamlessly melds with traditional agricultural practices.
Original language | English |
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Title of host publication | Environmental Monitoring Using Artificial Intelligence |
Publisher | Wiley-Blackwell |
Pages | 279-301 |
Number of pages | 23 |
ISBN (Electronic) | 9781394270392 |
ISBN (Print) | 9781394270361 |
DOIs | |
Publication status | Published - 1 Jan 2025 |
Keywords
- agricultural optimization
- almond and walnut farming
- damage assessment
- optimizing energy consumption
- U-net-based farming optimization