Identifying reliable visible-spectrum reflectance metrics for monitoring cucumber leaf development

Accurate and continuous monitoring of plant development is crucial for managing closed cultivation systems effectively. Optical reflectance-based sensors offer a non-destructive, scalable, and cost-efficient method to track plant growth, physiological status and stress responses. However, existing vegetation indices predominantly utilize wavelengths in the near-infrared ( > 800nm) range, a spectral range typically absent in horticultural LED lighting systems, limiting their applicability in horticultural LED-lit environments. This study investigates spectral metrics within the visible spectrum (440nm - 740nm) that robustly correlate with leaf order, a proxy for leaf age, in cucumber ( Cucumis sativus ) plants grown under controlled artificial lighting conditions. We systematically compared adaxial and abaxial leaf surfaces, identifying significant spectral variations associated with leaf order. Results demonstrate that abaxial leaf reflectance strongly correlates with leaf order, especially in the blue and red spectral regions. While adaxial reflectance showed weaker correlations, specific reflectance ratios (e.g., ρ 720 /ρ 700 ) enhanced this relationship, providing metrics suitable for sensor integration. These findings supply metrics for the development of simple optical sensors optimized for growth monitoring in greenhouse or indoor farming systems.