Zito et al. (2025) SolarFertigation: A Unified Cloud Platform for Smart Fertigation and Agrivoltaic System Integration

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Springer Link (Chiba Institute of Technology)
• Year: 2025
• Date: 2025-12-05
• Authors: Francesco Zito, Nicola Ivan Giannoccaro, Sergio Strazzella, Vincenzo Tucci
• DOI: 10.1051/bioconf/202519901002/pdf

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This paper presents the architecture of SolarFertigation, an intelligent solar-powered fertigation system designed for precise, adaptive management in agrivoltaic contexts. While demonstrating effective data transmission and system integration, initial field validation revealed a significant crop yield reduction, exceeding 80%, under photovoltaic panels compared to open-field conditions.

Objective

• To present the architecture of SolarFertigation, an intelligent, solar-powered fertigation system, and outline future scenarios for scalable farm management aligned with ecological transition objectives, particularly within agrivoltaic systems.

Study Configuration

• Spatial Scale: Field, zone, and crop levels, with field validation campaigns.
• Temporal Scale: Real-time monitoring and dynamic adjustment of fertigation schedules.

Methodology and Data

• Models used: Advanced automation models for dynamic fertigation scheduling based on crop phenology, weather conditions, soil characteristics, topography, and machine status.
• Data sources: Smart farming sensors providing real-time environmental, agronomic, and operational data (e.g., nutrient composition and dosage in grams, distributed water volumes in litres, crop stages, field operations, solar radiation, light intensity indices). LoRaWAN network data for signal coverage and transmission reliability.

Main Results

• The SolarFertigation system demonstrated effective LoRaWAN signal coverage and reliable data transmission, even with structural obstacles.
• Experimental field campaigns showed a significant reduction in solar radiation and light intensity indices beneath agrivoltaic modules.
• A general reduction in crop yield under photovoltaic panels was observed, in some cases exceeding 80% compared to open-field conditions.
• The system tracks detailed metrics such as nutrient composition and dosage (grams), distributed water volumes (litres), crop stages, and field operations, supporting compliance with Italian Guidelines for Agrivoltaic Systems (MASE), including a Land Area Occupation Ratio (LAOR) limited to 40% photovoltaic coverage.

Contributions

• Introduction of SolarFertigation, a novel intelligent, solar-powered fertigation system with a modular, scalable cloud-based architecture for precise and adaptive management.
• Designed for seamless integration within agrivoltaic contexts, incorporating smart farming sensors and machines.
• Provides advanced automation models for dynamic fertigation scheduling based on comprehensive real-time data.
• Acts as a strategic enabling technology to operationalize and scale principles from national (MASE) and international (IEA PVPS Task 13) agrivoltaic guidelines.
• Presents initial field validation results, highlighting both system effectiveness in data handling and the significant challenge of crop yield reduction under PV panels in agrivoltaic setups.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Zito2025SolarFertigation,
  author = {Zito, Francesco and Giannoccaro, Nicola Ivan and Strazzella, Sergio and Tucci, Vincenzo},
  title = {SolarFertigation: A Unified Cloud Platform for Smart Fertigation and Agrivoltaic System Integration},
  journal = {Springer Link (Chiba Institute of Technology)},
  year = {2025},
  doi = {10.1051/bioconf/202519901002/pdf},
  url = {https://doi.org/10.1051/bioconf/202519901002/pdf}
}