The accuracy and utility of a low cost thermal camera and smartphone-based system to assess grapevine water status

Abstract

Smartphones have several advantages over specialist monitoring systems including ubiquity, price, and ease of implementing updates. Thermal imaging can be used to assess plant water status and allow more informed irrigation decisions; unfortunately, this technique has not been widely adopted due to the high cost of equipment and the lack of a system to provide analysis and results in real-time. Several inexpensive thermal cameras that connect to smartphones have recently been released and one of these (FLIR One) was evaluated as part of a system to assess grapevine water status. Irrigation treatments were established on Cabernet Sauvignon and Chardonnay vines in an arid region. Thermal images were taken from the shaded side of the grapevine canopy and software was developed to automatically determine the temperature of the canopy and artificial reference leaves. The temperature readings and metrological inputs were used to calculate five indices of water status including the Crop Water Stress Index (CWSI) and the stomatal conductance index. The best performing was the CWSI, which does not require input from a weather station. Over 30 days of assessment, and a range of irrigation levels, measurements collected with the thermal camera were correlated with stem water potential (R2 = 0.61) and stomatal conductance (R2 = 0.74). Windy conditions appeared to be the major cause of variation between CWSI and stomatal conductance. Inexpensive thermal cameras have the potential to be an easy and accessible tool for the assessment of plant water status and to make better irrigation decisions.

Plant phenotyping relevance

低価格熱画像カメラとスマートフォンを用いたブドウ樹の水分状態推定システムを開発・評価しており、植物生理状態の取得方法が研究の中心である。

Code and data availability

The supplied blocks describe the thermal imaging methods, CWSI/IG calculations, and smartphone application, but contain no public phenotype/trait dataset, image deposit, author analysis code, or trained model with an explicit availability statement or authors' public URL. Analysis was done in proprietary tools (Excel,

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