Automated estimation of leaf area index from grapevine canopies using cover photography, video and computational analysis methods

BACKGROUND AND AIMS: Monitoring of canopy vigour is an important tool in vineyard management to obtain balanced vines (vegetative vs reproductive organs). Leaf area index is the main parameter representing canopy vigour. Our aim was to test an automated computational method to obtain leaf area index and canopy vigour parameters from grapevines with digital photography and video analysis using MATLAB programming techniques for rapid data uptake and gap size analysis. METHODS AND RESULTS: The proposed method was tested against allometry at a Chilean experimental site planted with cv. Merlot. A temporal and spatial assessment of the method was also tested in a drought and drought/recovery experiment with cv. Chardonnay in the Riverland, South Australia. These data were geo‐referenced and compared to the normalised difference vegetation index extracted from the WorldView‐2 satellite images at a 2 m² per pixel resolution. CONCLUSIONS: The maximum leaf area index data obtained with cover digital photography and video analysis are an accurate, cost‐effective and easy‐to‐use method to estimate spatial and temporal canopy LAI and structure when compared to standard measurements (allometry and plant canopy analyser). SIGNIFICANCE OF THE STUDY: This study has demonstrated that the method proposed is an accurate and inexpensive tool for application in experiments and by the industry to monitor spatio‐temporal distribution of vigour.