A Precision Imaging Approach to Assess Photovoltaic- Induced Shading Dynamics in Grapevine

Technical Summary: A Precision Imaging Approach to Assess Photovoltaic-Induced Shading Dynamics in Grapevine

Problem Statement
Viticulture in Mediterranean environments faces increasing constraints from rising temperatures and excessive solar radiation, which accelerate ripening and compromise grape quality. While agrivoltaic (AV) systems offer a dual solution of renewable energy generation and partial shading, the light environment they create is highly dynamic and spatially heterogeneous, driven by sun position, panel geometry, and canopy architecture. Traditional methods for assessing shading, such as ground coverage ratios (GCR) or static layout proxies, fail to capture the real-time, plant-scale light regimes experienced by vines. Furthermore, existing modeling approaches often rely on simplifying assumptions about canopy transmittance that may not reflect the complex, intermittent shading patterns in commercial vineyards. There is a critical need for field-based, non-destructive methods to quantify these spatio-temporal shading dynamics and link them directly to plant physiological responses.

Methodology
The study was conducted during the 2025 growing season in a Vitis vinifera cv. Falanghina vineyard in Southern Italy, situated beneath an agrivoltaic structure with amorphous silicon thin-film panels. The research employed a near-surface, time-lapse RGB imaging approach combined with radiometric and physiological measurements.

• Experimental Design: Two distinct vine positions were monitored: Agrivoltaic Shade (AVS), characterized by high exposure to panel-induced shading, and Agrivoltaic Light (AVL), with lower exposure.
• Imaging System: Two Brinno BCC2000 time-lapse cameras were installed 2.0 m above ground, oriented orthogonally to the PV mounting posts to capture eastern (07:00–13:00) and western (14:00–18:00) canopy sides. Images were acquired hourly from July to September.
• Image Analysis: A dedicated workflow using photoQuad software was implemented. This involved:
  1. Calibration: Using the known width of the PV support pole (9.30 cm) to convert pixels to real-world distances.
  2. Segmentation: Applying a multi-scale Statistical Region Merging (SRM) algorithm to distinguish shaded areas from illuminated canopy.
  3. Quantification: Calculating the percentage of canopy area shaded within defined quadrats (7910.12 cm²) for each treatment.
• Physiological & Radiometric Measurements:
  • Stomatal Conductance ($g_s$) & Leaf Temperature: Measured twice monthly on 18 vines (9 per treatment) using a portable porometer.
  • Radiometry: Continuous Photosynthetically Active Radiation (PAR) was monitored beneath the panels and in a full-sun control area. Spectral data (PPFD, band-specific photon flux densities for blue, green, red, and Red:Far-Red ratio) were collected using a portable spectrometer.
• Statistical Analysis: Non-parametric tests (Kruskal-Wallis, Dunn's test) were used for treatment comparisons, and Kendall's rank correlation ($\tau$) was employed to assess relationships between shading metrics and physiological variables.

Key Results

• Shading Dynamics: The AVS treatment exhibited significantly higher mean shading (76.14%) compared to AVL (39.45%, $p < 0.0001$). AVS remained consistently shaded throughout the day (peaking at 89.49% in the late afternoon), whereas AVL showed lower, more variable shading. Seasonal trends differed: AVS shading decreased in September, while AVL shading increased, reflecting the interaction between solar phenology and panel geometry.
• Radiometric Impact: Mean PAR beneath the panels was 379.53 µmol m⁻² s⁻¹, representing a 64% reduction compared to the full-sun control (1054.4 µmol m⁻² s⁻¹). The AVS treatment experienced extreme photon limitation (PPFD $\approx$ 52 µmol m⁻² s⁻¹) compared to AVL (PPFD $\approx$ 1485 µmol m⁻² s⁻¹).
• Physiological Correlations:
  • Stomatal Conductance ($g_s$): Showed a moderate negative correlation with shading ($\tau = -0.41$) and a moderate-to-strong positive correlation with PPFD ($\tau = 0.52$) and spectral photon flux densities.
  • Spectral Quality: The Red:Far-Red (R:FR) ratio was significantly lower in AVS (0.46) than AVL (0.98), indicating a strong "shade signal."
  • Diurnal Patterns: $g_s$ was significantly higher in the morning (east-facing) than in the afternoon (west-facing), a pattern attributed to diurnal hydraulic constraints and vapor pressure deficit rather than shading differences between sides.
  • Temperature: Leaf temperature showed no significant relationship with $g_s$, suggesting that thermal variability was not the primary driver of stomatal behavior in this context.
• Yield Implications: Referencing concurrent production data from the same site, the study notes that AVL vines achieved the highest productivity. AVS vines showed a 25% reduction in cluster number and 35% reduction in yield compared to AVL, while full-sun vines showed even greater reductions, suggesting an "optimal compromise" in the AVL treatment.

Key Contributions

1. Methodological Innovation: The paper presents a low-cost, non-destructive workflow using proximal RGB time-lapse imaging to derive temporally explicit shading metrics. This approach moves beyond static geometric estimates to provide field-resolved data on light interception.
2. Physiological Validation: The study demonstrates that image-derived shading metrics are strongly correlated with plant-relevant radiometric and physiological variables, specifically stomatal conductance and photon flux availability.
3. Characterization of AV Heterogeneity: The research quantifies the stark contrast between high-density shading (AVS) and intermediate shading (AVL) within the same agrivoltaic layout, highlighting how panel positioning creates distinct microenvironments with different physiological implications.

Significance and Claims
The authors claim that this workflow offers a practical tool for the precision monitoring and management of agrivoltaic systems. By providing direct, temporally explicit data on shading dynamics, the approach supports site-specific assessment of crop microenvironments. The study suggests that while high-density shading (AVS) can buffer against extreme radiation, it may limit carbon assimilation and yield in sun-loving crops like grapevines. Conversely, intermediate shading (AVL) may offer an optimal balance, maintaining photosynthetic capacity while mitigating thermal stress. The paper concludes that such imaging-based metrics can guide the design of agrivoltaic systems (panel spacing, height, orientation) to better match crop-specific light requirements, moving from theoretical modeling to empirically grounded management strategies.