Hot movements on soil surfaces – Innovative insights into microbial dynamics using passive infrared thermography

Abstract

Passive infrared thermography (IRT) has great potential for detecting and imaging microbial hot spots and hot moments on soil surfaces. A combined evaluation of such phenomena is considered in this study in so-called “hot movements”. This study identifies optimal soil incubation conditions and data preprocessing for the reliable identification of microbial activity on soil surfaces at high temporal and spatial resolution using IRT and substrate-induced respiration techniques. Two soil samples varying in microbiological properties were used for all experimental setups. Incubation conditions for thermal imaging were optimized with a focus on the application of varying glucose concentrations, glucose application techniques, relative air humidity, and ambient air temperature. Experimental data was optimized mathematically using a sequence of preprocessing methods. For data validation, the microbial activity of the soil surfaces determined by surface temperature was related to soil respiration, monitored by conventional CO2 determination. Generally, the application of glucose resulted in a temperature increase on the soil surfaces. A linear relationship (R2 = 0.84, *P < 0.05) between glucose application rate and surface temperature increase indicated that the thermal response on the soil surfaces was clearly related to a substrate-induced increase of microbial activity. With respect to the glucose application techniques, homogenous glucose mixing into the bulk soil sample allows analyzing the total microbial activity of disturbed soil samples via IRT in temporal perspective. However, homogeneous spatial glucose application on to the soil surface shows great potential to identify hot spot dynamics on undisturbed soil surfaces via IRT in a high temporal as well as spatial resolution. IRT measurements require a relative air humidity > 95% since less relative humidity levels resulted in intensive evaporation so that the associated cooling effect controlled the thermal dynamics on the surfaces. Ambient air temperature fluctuations influence soil surface temperatures, but these can be easily monitored and then eliminated by subtraction. After optimized incubation setup and optimized mathematical data-preprocessing, surface temperature differences between glucose treated and control samples reached up to 1 K. Additionally, the soil surface temperature associated microbial activity was reliably validated using respiration rates. In conclusion, it is demonstrated that the identification of microbial activity via IRT is highly sensitive to the incubation setup but a powerful technique is provided for the detection of “hot movements” on soil surfaces, characterizing microbial hot spot dynamics in size, shape, and intensity over time.