Random forests as a tool for analyzing partial drought stress based on CO<inf>2</inf>concentrations in the rootzone of longan trees

Abstract

This study aims at establishing a relationship between water supply and CO2concentration in the rootzone, and to identify disturbing factors using data-driven modelling. In our previous study, 10 longan trees were planted in split-root technique and kept under controlled conditions. During six months, 5 trees were partially irrigated on one side of the root system, while the other side was kept non-irrigated. The sides were switched in a two-week interval. Five control trees received full irrigation on both sides. Monitoring results on CO2concentration in the rootzone, soil moisture and stomatal conductance indicated a weak correlation between the CO2concentration in the rootzone and the soil moisture, but without a statistically significant correlation, partially because air temperature was a main disturbing factor. In this study, Random Forests was applied to establish a CO2-water stress relationship based on air temperature, relative humidity, vapour pressure deficit and soil moisture. It was shown that the most important factor on CO2concentration in the rootzone was soil moisture, followed by air temperature. Together with the information retrieved, the results suggest a potential of CO2monitoring in the rootzone for assessing plant water status continuously and with a minimum level of invasion.