Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress

TLDR

Thermal imaging can estimate plant temperature, an indicator of stomatal closure and water deficit stress. The study develops a new method for processing and analysing thermal images. The authors combine thermal and visible images with remote sensing software, classify leaf area into sunlit and shaded parts, compute temperature statistics for each component, and apply the method to greenhouse Vicia faba and field Vitis vinifera experiments, deriving thermal indices that are compared with stomatal conductance and temperature distributions under different irrigation regimes. The method produces more accurate thermal indices that correlate better with stomatal conductance and yields precise temperature distributions for shaded and sunlit canopy parts, enabling quantification of their relationship with stomatal conductance.

Abstract

Thermal imaging is a potential tool for estimating plant temperature, which can be used as an indicator of stomatal closure and water deficit stress. In this study, a new method for processing and analysing thermal images was developed. By using remote sensing software, the information from thermal and visible images was combined, the images were classified to identify leaf area and sunlit and shaded parts of the canopy, and the temperature statistics for specific canopy components were calculated. The method was applied to data from a greenhouse water‐stress experiment of Vicia faba L. and to field data for Vitis vinifera L. Vaseline‐covered and water‐sprayed plants were used as dry and wet references, respectively, and two thermal indices, based on temperature differences between the canopy and reference surfaces, were calculated for single Vicia faba plants. The thermal indices were compared with measured stomatal conductance. The temperature distributions of sunlit and shaded leaf area of Vitis vinifera canopies from natural rainfall and irrigation treatments were compared. The present method provides two major improvements compared with earlier methods for calculating thermal indices. First, it allows more accurate estimation of the indices, which are consequently more closely related to stomatal conductance. Second, it gives more accurate estimates of the temperature distribution of the shaded and sunlit parts of canopy, and, unlike the earlier methods, makes it possible to quantify the relationship between temperature variation and stomatal conductance.