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.

Phacelia tanacetifolia, an excellent cover, green manure and honey crop is now widely cultivated throughout the world. One of its principal European seed production regions is north-western Hungary, where the recent withdrawal of a potent herbicide, linuron, created a new challenge for many growers. The goal of this study is to identify the main factors determining weed species composition in the phacelia fields of the region and to assess the efficiency of tine harrow and clopyralid herbicide in reducing weed abundance and biomass. We carried out a series of weed surveys across the study region following a two-level design: (i) we estimated the cover of all weed species in 205 fields (broad-scale survey, BS); and (ii) in 22 of these fields, we provided more precise biomass measurements (counting the individuals and measuring the dry weights of all weed species) in microplots samples (fine-scale survey; FS). To characterize the fields, 34 background variables were also collected for all of the studied fields. In both investigations, Chenopodium album was by far the most abundant weed. Within the BS, using a minimal adequate model containing 11 terms with significant net effects, 20.93% of the total variation in weed species data could be explained. The variation in species composition was determined by environmental factors (soil pH, clay and K; precipitation and temperature), non-chemical management variables (crop cover, preceding crop, irrigation and tillage system) and herbicides (linuron and clopyralid). Variation partitioning demonstrated the dominance of environmental and cultural components in shaping the weed species composition. Although the effect of mechanical treatments was most likely masked in the BS by the soil properties, our FS suggests that tine harrow could efficiently decrease the total number and biomass of weeds and can be a useful tool in the phacelia management of the future.

The current study compares the phosphorus (P) analysis methods of ammonium lactate (AL), Mehlich 3 (M3); water extraction (P-WA(P)&P-WA(PO4)), cobalt hexamine (CoHex) and X-ray fluorescence (XRF) as an estimate of total soil P. The ratio of the P-content/XRF was first calculated and compared with the whole dataset. Based on the comparison of all the data, there were significant differences between the results of P-WA(P) and P-WA(PO4) vs. M3 and AL, CoHex vs. M3 and CoHex vs. AL methods (p < 0.001). The second step was the analysis of the influencing factors based on their categories for a more in-depth understanding of their role (CaCO3-content, pH, soil texture and clay content). The results showed that higher CaCO3 content (>1%) resulted in lower correlations (6/10 cases). The extraction methods, the soil, the classification method of the soil properties and the statistical analyses affect the evaluation. The dataset covers a good range of the analysed factors for the evaluation of phosphorus in the majority of Hungarian soil types in arable use. There were two methods that detected the largest amount of P from the total P in the soil: AL and M3.

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.

This report presents the outcome of Task 4.2 in the POWER4BIO project. The aim of this this report is to give an overview of public policies and regulations for the bio-based economy (BBE) with special attention to policy integration over different scales (from EU, national to regional) and across different policy domains (environmental, sustainable development policy, energy, bioeconomy policy, etc.). First it presents what type of policies can regulate and stimulate the development of a bioeconomy in a direction that is environmentally and economically sustainable. For this overview it is first explained how we can define the bioeconomy sector by presenting a bioeconomy system overview. This overview then provides an ordering mechanism to explain the different types of policies that can regulate and stimulate the bioeconomy in a region directly or indirectly.