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.

Background and Aims:Near infrared (NIR) spectroscopy techniques are not only used for a variety of physical and chemical analyses in the food industry, but also in remote sensing studies as tools to predict plant water status. In this study, NIR spectroscopy was evaluated as a method to estimate water potential of grapevines. Methods and Results: Cabernet Sauvignon, Chardonnay and Shiraz leaves were scanned using an Integrated Spectronic (300-1100 nm) or an ASD FieldSpec ® 3 (Analytical Spectral Devices, Boulder, Colorado, USA) (350-1850 nm) spectrophotometer and then measured to obtain midday leaf water potential using a pressure chamber. On the same shoot, the leaf adjacent the one used for midday leaf water potential measurement was used to measure midday stem water potential. Calibrations were built and NIR showed good prediction ability (standard error in cross validation (SECV) <0.24 MPa) for stem water potential for each of the three grapevine varieties. The best calibration was obtained for the prediction of stem water potential in Shiraz (R = 0.92 and a SECV = 0.09 MPa). Conclusion: Differences in the NIR spectra were related to the leaf surface from which the spectra were collected, and this had an effect on the accuracy of the calibration results for water potential. We demonstrated that NIR can be used as a simple and rapid method to detect grapevine water status. Significance of the Study: Grapevine water potential can be measured using NIR spectroscopy. The advantages of this new approach are speed and low cost of analysis. It may be possible for NIR to be used as a non-destructive, in-field tool for irrigation scheduling. AbbreviationsYleaf midday leaf water potential; Ystem midday stem water potential; g leaf conductance; NIR near infrared;PC principal component; PCA principal component analysis; PLS partial least squares regression; PRESS prediction residual error sum of squares; R coefficient of correlation; RWC relative water content;SECV standard error in cross validation; SD standard deviation; WUE water use efficiency. Data were obtained during the season 2006-07. n, number of samples used in calibration; R, coefficient of correlation; SD, standard deviation; SECV, standard error of cross validation. De Bei et al. Measure of grapevine water potential using NIR Manuscript

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