An Open-Architecture Precision Vertical Farming System for Sesame Microgreens: Audit-Ready Telemetry for Dynamic Lighting and Energy–Biomass Benchmarking

• IoT-based PVFS delivers audit-ready telemetry for dynamic lighting profiles. • Gaussian profiles increased energy costs with limited dry-mass gains across spectra. • Red-Constant maximized dry-mass efficiency (lowest SEC, highest EEMS). • SEC/EEMS captured energy-biomass outcomes not explained by instantaneous PSII traits. • Open-source PVFS stack enables reproducible lighting and energy-biomass benchmarking. The reproducibility of lighting protocols in Plant Factories with Artificial Lighting (PFALs) is frequently constrained by the scarcity of auditable operational data. This study presents and validates an open-architecture Precision Vertical Farming System (PVFS) capable of executing dynamic photosynthetic photon flux density (PPFD) profiles under controlled Daily Light Integral (DLI), ensuring traceability via IoT telemetry. The system was applied to sesame microgreens grown using a 2 × 4 factorial design, combining temporal profiles (Constant vs. Gaussian) and light spectra (White, Blue, Red, and RBW), with DLI equalized at 10.8 mol m − 2 d − 1 . Telemetric validation demonstrated high stability (jitter ≈ 0) and data completeness ( > 98%), enabling the precise calculation of Specific Energy Consumption (SEC) and Energy-to-Mass Efficiency (EEMS). Results indicated that, under equivalent DLI, the Gaussian profile increased energy costs (higher SEC) without proportional biomass gains for most spectra. The Red–Constant treatment achieved the highest efficiency ( 10.02 g kWh − 1 ), whereas white light exhibited the highest energy cost. Principal Component Analysis (PCA) reinforced that energy performance (SEC/EEMS) was more strongly associated with production outcomes (biomass) than with instantaneous photosynthetic metrics (e.g., F v / F m ), underscoring the importance of continuous monitoring of energy use and yield. The PVFS proved to be a robust tool for energy benchmarking and the standardization of lighting recipes in vertical farming.