Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermogravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R2 ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.

Understanding the roles of natural drivers in greenhouse gas (GHG) emissions of arable fields is crucial for adequate agricultural management. This study investigated the combined effect of two tillage treatments (NT - no-tillage; CT - tillage with mouldboard ploughing) and environmental (air pressure, air temperature) and soil factors (total organic carbon, gravimetric water content and soil penetration resistance) on soil carbon dioxide (CO2) emissions in maize in 2020 and 2021. The soil tubes required for the laboratory measurement were derived from three different altitudes of the two differently cultivated fields from Fejér county, Hungary. The typical soil type was Chernozem in both fields. At the time of soil sampling, soil penetration resistance was measured with a 06.15SA Penetrologger in 10 repetitions. To preserve the moisture content of the soil columns during the investigation, moisture replenishment was performed equal to the degree of weekly theoretical evapotranspiration. Emissions measurements of soil columns were performed by close chamber technique for five weeks from sampling, 15 times, in 3 repetitions in laboratory conditions. The data were evaluated by two-way ANOVA, followed by the Tukey HSD multiple comparison test and two-tailed Student’s T-test at a significance level of p<0.05. The combined effect of environmental factors on soil carbon dioxide emissions was investigated using stepwise multiple linear regression. It has been proved that the observed difference between soil penetration resistance and soil carbon dioxide emissions was significant between CT and NT cultivation at different stages of the growing season. The analysis of the interaction of the experimental factors revealed that the combined effect of soil penetration resistance, total organic carbon and moisture content in tillage system (adjusted R2=0.92 at a significance level of p=0.05) in 2020, while the combined effect of moisture content and air temperature in the no-tillage system (adjusted R2=0.79 at a significance level of p=0.085) has the most significant effect on soil CO2 emissions in 2020. In 2021, the air temperature for the tillage system (adjusted R2=0.74 at a significance level of p=0.05) and the combined effect of air temperature and pressure for no-tillage systems (adjusted R2=0.69 at a significance level of p=0.1) played an important role in soil CO2 emissions. These observations highlight that different soil and environmental factors of different tillage significantly impact the soil carbon dioxide emissions in different years.