Smart and Data-Driven Technologies for Precision Agriculture: Integrated Approaches to Crop Monitoring and Sustainable Optimization of Agricultural Practices

Agriculture is currently facing several challenges, particularly global population rise and climate change, which are threatening food security. In this context, precision agriculture aims to enhance crop yield and quality while optimizing the use of inputs and reducing waste of natural resources. To this end, over the last decades, smart technologies, such as sensors, robotics, the Internet of Things (IoT), and artificial intelligence (AI), have been increasingly introduced into farming practices. These advanced technologies have driven innovation across all agricultural domains, from monitoring plants, soil and environmental field conditions to managing agricultural practices (e.g., irrigation, plant nutrition status) and predicting various parameters (e.g., weather, yield, maturation). In addition, new sustainable solutions such as plant biostimulants (PBs) have gained prominence due to their effectiveness in enhancing plant tolerance to abiotic/biotic stresses and increasing crop yield and quality without negative consequences on the environment. Similarly, plant micronutrients represent a sustainable solution for targeted nutrient supplementation that mitigates deficiencies, improvement of stress mitigation and crop productivity. Within this framework, the crop species investigated in this Ph.D. thesis were selected based on their agronomic relevance and strategic importance within the Italian agricultural context. Tomato represents the most important crop in Emilia-Romagna, a region with a leading role in intensive horticultural production. Olive is among the most widespread and economically relevant crops at the national scale in Italy, deeply rooted in Mediterranean agriculture and particularly exposed to climate change–driven stresses. Hop represents an emerging and innovative crop, for which Emilia-Romagna currently hosts the largest cultivated surface in Italy and the most significant investments in technological and supply-chain innovation. Together, these species provide complementary models to address sustainability challenges across different cropping systems and production stages. For this reason, in this Ph.D. thesis, different approaches, both involving cutting-edge technologies and conventional methods, such as PBs and micronutrients, have been applied to key crops in the Italian market (tomato, hop, and olive tree) to address the individual challenges presented by each. For instance, smart technologies have been integrated into tomato cultivation that is currently suffering from water deficiency due to climate change. New IoT-based irrigation systems have been designed for the real-time monitoring of field conditions and the efficient management of water resources, achieving high yields while saving water. Specifically, three irrigation water regimes have been evaluated (100%, 60% and 30% of the Irriframe service) and best results, both in terms of yield and plant physiology, have been obtained applying mild water stress, allowing savings of 823.70 m3/ha of water compared to control conditions. Building on these findings, the following year, a novel IoT-based irrigation system has been developed, which saved 0.13 m³/m² of water compared to the prior setup. However, tomato cultivation is also endangered by increasing frequency of heavy precipitation. For this reason, the effects of water stress conditions, both deficit and excess, on the soil microbiome composition and the tomato physiology were evaluated. An inverse correlation between chlorophyll contents and soil microbial diversity was observed, highlighting a strong relationship between soil microbiome and plant resilience. Furthermore, the effectiveness of novel biostimulants derived from discarded kiwifruit, either subjected to lactic acid bacteria fermentation or protein hydrolysation, has been tested on tomatoes grown under both water deficit and excess conditions. These new PBs showed positive effects on free amino acids accumulation, lycopene content and volatile compounds. Notably, tomatoes under water stress but treated with these kiwi-derived PBs exhibited quality attributes comparable to well-watered controls, despite the adverse conditions. Advanced technologies have also been applied to hop cultivation, which relies on female inflorescences for brewing while male flowers prove essential in breeding programs. Since sex determination currently requires time-consuming and expensive genetic analyses, an innovative IoT system for rapid, non-destructive plant gender recognition was implemented. In addition, a smart system for hop cone maturation assessment was deployed using IoT technologies and AI tools (e.g., machine learning (ML) models). To this end, field conditions were monitored over three growing seasons, during which hop cones were morphologically and chemically characterized. These data trained two ML algorithms, which accurately predicted harvest timing in the fourth year, representing the first such prediction ever made for hops. Moreover, advancements in hop storage have been achieved by testing refrigerated temperatures and anaerobic conditions over three years to preserve quality parameters. Results from two cultivars with distinct properties highlighted that temperature has a greater impact on hop storage than the anaerobic atmosphere, with varietal differences indicating that bitter cultivars can tolerate higher temperatures without quality loss. This also offers environmental benefits, as reduced storage temperature requirements lower energy consumption. Olive cultivation, traditionally practiced in marginal Mediterranean areas, currently faces climate change impacts such as reduced rainfall and higher temperatures. Smart technologies, including IoT sensors and ML models for monitoring and predicting soil moisture, combined with non-technological approaches such as biochar to improve soil properties, were evaluated and achieved over 97% prediction accuracy for soil water content. Additionally, the role of micronutrients for enhancing plant tolerance to abiotic stress was investigated. The effects of selenium, boron, and glycine betaine, individually or combined, on olive yield and extra virgin olive oil (EVOO) quality revealed significant treatment differences. Selenium promoted fruit growth and oil accumulation, while boron and betaine improved sensory attributes. Despite addressing different crops and production stages, all the studies included in this thesis are unified by a coherent scientific and methodological framework based on a systems-oriented approach. Quantitative field monitoring, physiological and chemical characterization, and the validation of sustainable management strategies are consistently integrated to improve resource-use efficiency, stress resilience, yield and product quality. Within this unified precision agriculture paradigm, technological tools (e.g., IoT systems and data-driven models) and non-technological solutions (e.g., biostimulants and micronutrients) act as complementary components, allowing crop-specific challenges to be effectively addressed while preserving environmental sustainability. As a result, this thesis demonstrates how integrated technological and agronomic approaches can enhance the performance of key economically relevant Italian crops (e.g., tomato, hop, and olive). Beyond the individual case studies, the outcomes confirm the potential of smart technologies for optimizing agricultural practices and the effectiveness of sustainable inputs in improving yield and quality, ultimately providing a robust and extensible framework applicable to other crops and agro-environmental contexts.