Abstract
Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.
Highlights
Monitoring grapevine canopy architecture is critical for the assessment of growth, vigor and light transmission through the canopy and water requirements of plants
The discrepancy, which is a slight underestimation (3%) for the Matlab code compared to VitiCanopy for six out of 113 images, could be explained by differences in precision in the automatic luminosity thresholding, based on the blue channel, used by the two systems [1]
The algorithms used for filtering in the Matlab code compared to VitiCanopy are different and for the above-mentioned images this creates underestimations of canopy size due to loss of segmentation of images, in particular at the edges of the canopy or on over-illuminated leaves
Summary
Monitoring grapevine canopy architecture is critical for the assessment of growth, vigor and light transmission through the canopy and water requirements of plants. Direct planimetric measurements can give very accurate LAI results, since they require stripping the whole canopy and scanning every leaf with a scanning planimeter (e.g., Li-3000/3100, Li-Cor, Lincoln, NE, USA) to obtain the total area of leaves per unit area of soil [7] This method is extremely time consuming and destructive so it is of little value in a commercial setting other than for the calibration of non-destructive and indirect techniques [5,8]. The gravimetric method is based on the correlation between leaf area and dry weight [5,7,9], which can be applied with a high percentage of accuracy This technique is site and species/cultivar specific and yet another time-consuming and extremely labor intensive method to obtain accurate results [10]. Other methods that are widely applied in vineyards, use the relationship between leaf area and leaf length or shoot length [11,12]; these are common because they are simple, but time consuming and season, site, climate and cultivar specific
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