Tree Genetics and Molecular Breeding 2024, Vol.14, No.6, 304-312 http://genbreedpublisher.com/index.php/tgmb 307 practices. This integration allows for the assessment of spatial variability in vine health and soil moisture, which is crucial for targeted management practices and optimizing water-use efficiency (Mucalo et al., 2024). GIS tools help in generating detailed maps that guide viticulturists in making informed decisions about resource allocation and vineyard management. 3.4 Machine learning and data analytics Machine learning and data analytics are transforming precision viticulture by predicting disease outbreaks, yield, and quality metrics. The integration of IoT with machine learning models provides predictive tools that are essential for improving land productivity and crop quality (Rezk et al., 2020). These models are used to forecast vineyard conditions, such as frost damage and grapevine diseases, offering agronomists advanced tools for sustainable vineyard management (Pero et al., 2024). The use of AI models in processing and interpreting big data helps in understanding the agronomic and physiological status of vineyards, enabling proactive management strategies (Ferro and Catania, 2023). 4 Case Studies in Precision Viticulture 4.1 Achieving higher yields Precision viticulture (PV) has been instrumental in enhancing grape yields by employing site-specific management practices. A French winery has successfully implemented precise fertilization and irrigation techniques to optimize grape production. This approach involves the use of advanced technologies such as variable rate application (VRA) and remote sensing to monitor and manage vineyard conditions effectively. By analyzing soil moisture levels and employing variable rate nutrient applications, the winery has been able to tailor its fertilization and irrigation strategies to the specific needs of different vineyard zones, thereby increasing yields while minimizing environmental impact (Matese and Gennaro, 2015; Balafoutis et al., 2017). The integration of IoT and machine learning technologies further supports these efforts by providing predictive tools that enhance land productivity and crop quality (Pero et al., 2024). 4.2 Precision pest and disease management In Italy, a vineyard has adopted artificial intelligence (AI) to enhance its pest and disease management strategies, particularly for combating downy mildew. By integrating AI with IoT-driven machine learning models, the vineyard can predict high-risk periods for disease outbreaks, allowing for timely and precise pesticide applications. This method not only reduces the amount of chemicals used but also minimizes the environmental footprint of vineyard operations (Mucalo et al., 2024; Pero et al., 2024). The use of satellite data and ground-based measurements provides detailed insights into vine health and environmental conditions, enabling the vineyard to implement targeted management practices that improve sustainability and productivity (Spachos and Gregori, 2019; Mucalo et al., 2024). This case exemplifies how advanced analytics and AI can revolutionize traditional viticulture practices, leading to more sustainable and efficient vineyard management (Santesteban, 2019; Ferro and Catania, 2023). 4.3 Improving resource utilization efficiency In the context of precision viticulture, the implementation of sensor networks has proven to be a pivotal strategy for enhancing resource utilization efficiency, particularly in water management. An Australian vineyard successfully reduced its irrigation water usage by 50% through the deployment of advanced sensor networks. These networks integrate data from various sources, including remote and proximal sensors, to monitor the hydric stress status of the vineyard. This approach allows for precise irrigation scheduling, ensuring that water is applied only when necessary, thus conserving this vital resource (Finco et al., 2022). Additionally, a vineyard in Lleida, Spain, has further enhanced the precision of water management practices by integrating satellite data with ground-based measurements. This approach optimized water-use efficiency and reduced the environmental impact of vineyard operations (Figure 3) (Bellvert et al., 2020; Mucalo et al., 2024).. By adopting these technologies, the vineyard not only achieved significant water savings but also maintained or improved grape yield and quality, demonstrating the economic viability of precision irrigation systems (Bellvert et al., 2020).
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