Precision Agriculture for Nutraceutical Crops: A Comprehensive Scientific Review

Precision Agriculture (PA) is reshaping nutraceutical crop production by enabling high-resolution monitoring and adaptive management strategies that simultaneously optimize yield, stabilize phytochemical composition, and enhance environmental sustainability. Nutraceutical crops derive their economic and functional value from bioactive compounds whose concentration, uniformity, and temporal stability are highly sensitive to spatial and environmental variability. To address these constraints, PA integrates advanced sensing technologies, unmanned aerial vehicle (UAV)–based multispectral, hyperspectral, thermal, and LiDAR observations, Internet of Things (IoT)–enabled soil–plant–atmosphere monitoring, and artificial intelligence (AI) and machine-learning (ML) analytics within data-driven decision-support frameworks. This review synthesizes recent scientific evidence demonstrating how PA improves agronomic performance, stabilizes phytochemical profiles, and increases resource-use efficiency in nutraceutical systems through precision irrigation, site-specific nutrient management, three-dimensional canopy characterization, and real-time stress detection. Particular emphasis is placed on Moringa oleifera Lam. as a model nutraceutical crop for climate-sensitive Mediterranean agroecosystems. Recent field applications show that the integration of UAV-based spectral and thermal imaging, LiDAR-derived canopy metrics, and IoT-guided management enhances canopy assessment, optimizes harvest timing, improves phytochemical consistency, and strengthens traceability and quality control along the value chain. Emerging developments—including AI-enabled predictive decision-support systems, digital twins, and blockchain-based traceability—are discussed as key enablers for scalable, quality-oriented nutraceutical production. Collectively, the evidence positions PA as a foundational approach for resilient, climate-smart, and standardized nutraceutical agriculture, fully aligned with smart farming paradigms based on sensors, robotics, and artificial intelligence.