For an agricultural region such as the Vojvodina Province in northern Serbia, soil quality monitoring is very important. Enzymatic activities are proposed as good indicators as they respond to even the slightest changes in the soil. This study aimed to analyze the enzymatic activity levels across three different soil types in Vojvodina and to examine their connection to soil chemical properties and land use. All soil types (chernozem, vertisol, solonchak) were sampled at nine locations, each with 3 field plots. The activities of acid and alkaline phosphatase, β-glucosidase, dehydrogenase, and catalase were measured in samples, as well as the selected chemical properties. Results showed differences in enzymatic activity across different soil types and land use. The most active enzymes in vertisol were acid phosphatase and β-glucosidase; in solonchak, it was alkaline phosphatase; in chernozem, it was dehydrogenase. A high correlation between enzymatic activities and certain soil chemical properties (pH reaction, organic matter, organic carbon, total nitrogen) was also observed, underlining the existence of a relationship between different soil components. The highest determined correlation was between acid phosphatase and pH (r=-0.7), alkaline phosphatase and total nitrogen (r=0.7), and organic matter (r=0.72); the obtained correlations were found to be statistically significant.

Having scarce information about ultrasound assisted extraction (UAE) and microwave assisted extraction (MAE) of white horehound (Marrubium vulgare L.), the idea has emerged to determine the optimal process parameters for the maximization of polyphenols and to compare the efficiency of these green extraction technologies. The optimal UAE parameters are temperature of 73.6 °C, extraction time of 40 min and ultrasound power of 30.3 W/L, while the optimal MAE parameters are 63.8% ethanol, extraction time of 15 min and microwave power of 422 W. Extract obtained at optimal UAE parameters shows the highest antihyperglycemic activity (α-amylase inhibition: 50.63% and α-glucosidase inhibition: 48.67%), which can potentially be explained by the presence of chlorogenic acid and quercetin, which were not identified in the macerates. The most sensitive bacterial strain to optimal ultrasonic extract is Bacillus cereus, whereas the most sensitive fungal strain is Saccharomyces cerevisiae.

Summary: Solonchaks are soils characterized by high concentrations of soluble salts. These soils form unique ecosystems that provide habitats for organisms adapted to such extreme conditions. Invertebrates are one of the groups of organisms that inhabit these soils and play a significant role in ecosystem resilience contributing to soil health and fertility. However, the diversity of invertebrates inhabiting the solonchaks remains underexplored. The development of eDNA metabarcoding method has facilitated the detection of soil invertebrates, overcoming the limitations of conventional labor-intensive and time-consuming methods. eDNA metabarcoding made it possible to study/monitor changes in soil invertebrate diversity. This pilot study employed eDNA metabarcoding to detect soil invertebrates in solonchak soils at two agricultural fields in Vojvodina, Serbia. Furthermore, we compared two analytical methods of eDNA metabarcoding data – clustering and denoising sequences. eDNА metabarcoding method proved to be effective in detection of invertebrates. Using BOLD database, 0.21% OTUs and 0.11% ESVs were successfully assigned to expected Invertebrate phyla (Arthropoda, Annelida and Nematoda), with two specific species identified: Aporrectodea jassyensis and Sminthurinus elegans. Comparison of the two analytical approaches, denoising and clustering, revealed that these approaches identified the same taxonomic categories. However, given the limited sample size, further studies should compare these two approaches using a more extensive dataset to better estimate their usefulness.

Soil quality monitoring is essential in agricultural regions such as the Autonomous Province of Vojvodina, Serbia. The abundance of bacterial functional groups involved in the nitrogen cycle presents a good indicator of nitrogen forms in soil and soil fertility. This study aimed to assess the abundances of selected bacterial functional groups across three different soil types in Vojvodina and to examine their correlation with soil chemical properties. Analyzed soil types (chernozem, solonchak, vertisol) were sampled at nine locations, with two agricultural and one control plot at each location. The abundances of nitrogen-fixing bacteria, ammonifiers, nitrifiers, denitrifiers, and total heterotrophic bacteria were determined. Results showed differences in the abundances of nitrogen-fixing bacteria, ammonifiers, and nitrifiers across different soil types. Chernozem had the highest abundance of nitrogen-fixing bacteria and ammonifiers. Denitrifiers were most abundant in solonchak, while vertisol had the highest abundance of nitrifiers and total heterotrophic bacteria. A statistically significant moderate correlation was observed between the abundance of bacteria and certain soil chemical properties. Namely, moderate negative correlation between nitrifiers and pH in KCl (r=-0.57), pH in H2O (r=-0.53), and CaCO3 content (r=-0.4) and moderate positive correlation between denitrifiers and P2O5 content (r=0.4) were determined. Moderate correlation of bacterial counts and soil properties could indicate that bacterial count variability is also linked to other factors, such as soil vegetation cover type, soil use, anthropogenic activities and climate change. Thus, bacterial functional groups could be useful as an indicator of overall soil health and fertility, especially in connection with nitrogen, as an essential element.

Soil is the largest reservoir of biodiversity, with distinct physical, chemical, and biological properties. Microorganisms play essential roles in soil formation and fertility. This study aimed to analyze the microbiomes of three selected soil groups in an important agricultural region of Vojvodina (Serbia) by 16S rRNA gene metabarcoding and explore their association with soil properties. Soil samples from a total of 26 field plots (in 5 replicates) were analyzed using Illumina MiSeq paired-end sequencing and processed through the QIIME2 pipeline. The obtained results indicate that the analyzed soils generally exhibit physicochemical properties typical for the respective soil groups. Alpha diversity indices revealed the highest microbiome diversity in Chernozem, consistent with its favourable physicochemical characteristics. Based on beta diversity, clear separation of soil groups according to their properties was determined. Proteobacteria, Acidobacteriota, and Actinobacteriota dominate the microbial community composition at the phylum level. Redundancy analysis revealed that soil properties account for 53.8 % of the variation in community composition, with pH value, iron availability, and CaCO₃ content having the strongest influence, pH being particularly significant. The functional potential of microbial communities showed dominance of functions related to metabolism, with significant representation of functions belonging to the following groups: genetic information processing, environmental information processing, and cellular processes. The analysis of genes involved in nitrogen cycling using Kruskal-Wallis test showed no statistically significant differences in their abundances across different soil groups (p-value > 0.05). This study provides the first detailed analysis of soil microbial communities across Serbia and highlights factors shaping them. These findings underscore the importance of microbial diversity for ecosystem functioning and offer a framework for soil health monitoring, while providing insights relevant for sustainable agriculture.

Soil is the largest reservoir of biodiversity, with distinct physical, chemical, and biological properties. Microorganisms play essential roles in soil formation and fertility. This study aimed to analyze the microbiomes of three selected soil groups in an important agricultural region of Vojvodina (Serbia) by 16S rRNA gene metabarcoding and explore their association with soil properties. Soil samples from a total of 26 field plots (in 5 replicates) were analyzed using Illumina MiSeq paired-end sequencing and processed through the QIIME2 pipeline. The obtained results indicate that the analyzed soils generally exhibit physicochemical properties typical for the respective soil groups. Alpha diversity indices revealed the highest microbiome diversity in Chernozem, consistent with its favourable physicochemical characteristics. Based on beta diversity, clear separation of soil groups according to their properties was determined. Proteobacteria, Acidobacteriota, and Actinobacteriota dominate the microbial community composition at the phylum level. Redundancy analysis revealed that soil properties account for 53.8 % of the variation in community composition, with pH value, iron availability, and CaCO3 content having the strongest influence, pH being particularly significant. The functional potential of microbial communities showed dominance of functions related to metabolism, with significant representation of functions belonging to the following groups: genetic information processing, environmental information processing, and cellular processes. The analysis of genes involved in nitrogen cycling using Kruskal-Wallis test showed no statistically significant differences in their abundances across different soil groups (p-value > 0.05). This study provides the first detailed analysis of soil microbial communities across Serbia and highlights factors shaping them. These findings underscore the importance of microbial diversity for ecosystem functioning and offer a framework for soil health monitoring, while providing insights relevant for sustainable agriculture.