Automated estimation of leaf area index from grapevine canopies using cover photography, video and computational analysis methodsAustralian Journal of Grape and Wine Research


S. Fuentes, C. Poblete-Echeverría, S. Ortega-Farias, S. Tyerman, R. De Bei


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

S. FUENTES1, C. POBLETE-ECHEVERRÍA2, S. ORTEGA-FARIAS2, S. TYERMAN1 and R. DE BEI1 1 Plant Research Centre, The University of Adelaide, Waite Campus, PMB 1, Glen Osmond, SA 5064, Australia 2 Research and Extension Center for Irrigation and Agroclimatology (CITRA), Universidad de Talca,

Avenida Lircay S/N, Talca, Chile

Corresponding author: Dr Carlos Poblete-Echeverría, email


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.

Keywords: canopy cover, digital image analysis, MATLAB programming, porosity, satellite imagery


Leaf area index (LAI) has been defined as the total one-sided area of leaf tissue per unit ground surface area (Watson 1947).

Most of the currently available methods for monitoring LAI are based on manual measurement points, which have low spatial resolution and are time consuming. Thus, it is difficult to assess efficiently the spatial and temporal variability of LAI from vineyards, usually caused by differences in soil characteristics and management.

Studies based on remote sensing have shown that monitoring variation in LAI could be a good spatial indicator of canopy vigour for grapevines using airborne platforms (Johnson et al. 2003b, Hall et al. 2008) and satellite platforms (Johnson 2003a,

Zarco-Tejada et al. 2005, Martin et al. 2007). These same studies, however, pointed out that the canopy discontinuity from vineyards posed an analysis problem for accurate LAI estimation due to the inter-row component, especially when a cover crop is present.

Measuring leaf area index and canopy structure as vigour indicators for management purposes

Canopy vigour can be managed with different training systems to regulate the microclimate of canopies to affect yield and grape composition (Smart 1985). Adjusting canopy vigour to decrease disease incidence can be also achieved by removing leaves (English et al. 1989) or by summer pruning (Wermelinger and

Koblet 1990, Guidoni et al. 1997, Rügner et al. 2002).

It is well known that canopy structure and size can also be altered, as a management strategy, by reducing the amount of water applied to control vigour. Increments in irrigation have resulted in increased LAI, indicative of a more vigorous vine (Esteban et al. 1999, 2001, Acevedo-Opazo et al. 2010).

Another effect sought by reducing LAI is to obtain greater light penetration to bunches and the renewal zone (area where the fruiting canes originate) to improve fruit composition and productivity for the next season (Dokoozlian and Kliewer 1995).

Berries with increased sun exposure are generally higher in phenolic substances along with decreased acidity when compared to that of non-exposed fruit (Bergqvist et al. 2001).

Therefore, there is an inverse relationship between vigour and gap fraction that affects fruit composition. This effect needs to be taken into account for optimal management purposes and has been the main subject for many experimental trials in the past.

Monitoring canopy cover and LAI has been also proposed as a way to estimate accurately crop coefficients (Kc) for grapevines to assess water requirements for irrigation scheduling purposes (Williams and Ayars 2005). In general, the Kc value for grapevines can be obtained from the literature (Allen et al.

Fuentes et al. New automated canopy vigour monitoring tool 1 doi: 10.1111/ajgw.12098 © 2014 Australian Society of Viticulture and Oenology Inc. 1998). These values, however, are generic, developed in different agroclimatic conditions and do not account for differences between canopy size, row orientation, training system and vine spacing, among other factors (Martin et al. 2007, PobleteEcheverría et al. 2012, Poblete-Echeverría and Ortega-Farias 2013).

Measuring leaf area index as an indicator of vigour for experimental purposes

For experimental purposes, LAI is a critical parameter widely used for: (i) experiments that involve the estimation of growth and development of plants (Fuentes et al. 2008); (ii) modelling growth and water use (Williams and Ayars 2005); (iii) functional plant modelling (Whitley et al. 2008); and (iv) scaling up leaf-based physiological measurements to the whole plant or tree (Ewert 2004) and tree-based measurements (e.g. sap flow) that can also be upscaled to the whole field or region (Zeppel et al. 2008). The magnitude of LAI in a vineyard depends on environmental and management factors, such as training systems, water and nutrient supply and the use of cover crops, among others (Oliveira and Santos 1995). Therefore, there is the requirement to determine accurately spatio-temporal variations of LAI for scientific experiments to verify the effect of treatments on canopy vigour and, from the management perspective, to assess precision irrigation strategies, such as regulated deficit irrigation and partial root-zone drying, to maximise yield and quality of grapes.