Thermal imaging of crop canopies has been proposed more than a decade ago as a sensitive methodology to determine water status of different crops.This paper describes the development of a semi-automated and automated methodology using MATLAB® programming techniques to analyse infrared thermal images taking into consideration the pitfalls pointed out previously in the literature. The proposed method was tested in an irrigation reduction and recovery trial for Chardonnay in the 2010-11 season and in the 2009-10 season from seven varieties in field conditions. There was a clear separation (assessed by principal component analysis) between control and recovery compared to stress treatments using leaf area index (LAI), stomatal conductance, stem water potential and indices derived from canopy temperatures measured by infrared imaging. High and significant correlations were found between canopy temperature indices and other measures of water stress obtained in the same vines that were independent of LAI. Furthermore, a fully automated analysis method has been proposed using ancillary weather 2 information obtained from the same locations of infrared thermal images. This paper is a first step towards automation of infrared thermography acquisition and analysis in the field for grapevines and other crops.
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.
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