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Article

Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies

by
Dorota Swędrzyńska
1,
Jan Bocianowski
2,*,
Agnieszka Wolna-Maruwka
1,
Arkadiusz Swędrzyński
3,
Anna Płaza
4,
Rafał Górski
5,
Łukasz Wolko
6 and
Alicja Niewiadomska
1
1
Department of Soil Science and Microbiology, Poznań University of Life Sciences, Szydłowska 50, 60-656 Poznań, Poland
2
Department of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
3
Department of Grassland and Natural Landscape Sciences, Poznań University of Life Sciences, Dojazd 11, 60-632 Poznań, Poland
4
Institute of Agriculture and Horticulture, Faculty of Agricultural Sciences, University of Siedlce, 08-110 Siedlce, Poland
5
Faculty of Engineering and Economics, Ignacy Mościcki University of Applied Sciences in Ciechanów, 06-400 Ciechanów, Poland
6
Department of Biochemistry and Biotechnology, Poznań University of Life Sciences, Dojazd 11, 60-632 Poznań, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(3), 1468; https://doi.org/10.3390/app15031468
Submission received: 22 November 2024 / Revised: 28 January 2025 / Accepted: 29 January 2025 / Published: 31 January 2025
(This article belongs to the Special Issue Role of Microbes in Agriculture and Food, 2nd Edition)
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Abstract

:

Featured Application

Our research can inspire others to determine whether reduced tillage systems under different crop species, not only Fabacea, will always contribute to the development of beneficial microbial species in the soil, which are important for reducing anthropogenic factors influencing ongoing climate change and soil degradation. Moreover, it will also indicate whether only legumes have such properties for the development of beneficial microbe species, which would further justify the need for their use in crop rotation.

Abstract

Modern agriculture should limit its degrading impact on the soils, the natural environment, and the climate. No-tillage soil cultivation technologies, which have been in use for many years and are constantly being improved, are a good example of these actions; although, in-depth studies on their impact on the soil microbial community are currently scarce. The aim of our study was to evaluate the effect of cultivation technology on the soil bacterial community to assess differences that can be reflected in the environmental and agricultural functionality, identifying possible bacterial species with ecological properties. In this context, the composition of bacterial communities (at the phyla, order, class, and species levels) was evaluated under different conditions, such as conventional tillage (CT) (plophing), reduced tillage (RT) (stubble cultivator), strip tillage (ST), and no-tillage (direct sowing on stubble and fallow buffer zone of the experimental field), in a horse bean plantation. Metagenomic methods (next generation sequencing technology, NGS) were used to determine the percentage of individual operational taxonomic units (OTUs). Our study showed that no-tillage cultivation technologies, mainly strip and no-tillage methods, had a positive effect on microbiological communities. In fact, key species related to soil fertility and crop yield, such as Gemmatimonas aurantiaca (a microorganism that reduce nitrous oxide, N2O in soil) and Aeromicrobium ponti (a beneficial species for the soil environment, essential for the proper functioning of the crop agroecosystem), increased in reduced cultivation technologies. These species can determine soil fertility and crop yields, and therefore, they are very important for sustainable and even regenerative agriculture. Further studies of soil samples collected from other crop plantations under different cropping systems may indicate beneficial microbial species that are important for soil fertility.

1. Introduction

Modern agriculture faces two major challenges. On the one hand, it must feed the growing world population. On the other hand, it must reverse its current degrading influence on soils, the natural environment, and the climate [1,2]. It is possible to achieve these goals simultaneously by following one of many parallel paths, i.e., the development of conservation and regenerative agriculture and, especially, the rational implementation of the widest possible spectrum of its principles into practices of intensive commercial agriculture. No-tillage soil cultivation technologies, which have been used for many years and are constantly being improved, are an example of such activities. They limit soil degradation and help to preserve the production, biological, environmental, and climatic potential of soils [3,4].
No-tillage technologies involve the use of simplified soil cultivation methods or even complete abandonment of tillage. As a result, it is possible to reduce input costs, including fuel consumption [5]. No-tillage systems have a positive influence on the physical, chemical, and biological properties of soils, because they limit, among other things, their drying. In consequence, the rate of mineralization of organic matter and CO2 emissions is reduced. Leaving some or all of the crop residues on the surface or in the subsurface layer of soil increases its protection from drying and erosion. Apart from that, it improves the transformation of soil organic matter and carbon sequestration [6,7].
However, these technologies sometimes also have negative effects, such as excessive soil compaction and the differentiation of physical properties (especially within the surface, humus, and enriched A horizon). Also, sometimes the deterioration of the chemical properties, including acidification is being reported due to the nitrogen fertilization of the topsoil. These phenomena may negatively influence the yield of some crops [5]. Moreover, the absence of tillage usually favors the expansion of some weeds, which may cause the need to use larger amounts of herbicides [8,9]. The specific physical and chemical properties of soils cultivated in different systems also result in their characteristic biological properties, i.e., mainly the size and diversity of the edaphon, especially the population of microorganisms and the enzyme activity [10]. Individual cultivation systems significantly influence soil aeration and moisture as well as the amount and distribution of the biomass of crop residue [11]. Soil cultivation simplifications, especially the complete abandonment of tillage, usually favor greater soil bioactivity and positively affect the size and diversity of the microbial population. This applies to the total count of bacteria and fungi as well as individual taxonomic and trophic groups. At the same time, the populations of some microorganisms, e.g., bacteria of the Azotobacter genus, are larger in traditionally ploughed soils [12].
The current knowledge of the influence of the cultivation system on the soil microbiome is still very general. There have been few studies covering a wide spectrum of individual taxa of soil microorganisms and their communities [13]. Detailed studies in this field became possible only with the development and greater availability of molecular and genetic research techniques.
Our study assumed that the soil samples collected from a horse bean plantation would exhibit differences in the composition of bacterial communities at the phylum, order, classes, and species levels due to different tillage systems. The differences would be manifested by the pro-environmental and agricultural roles of the microorganisms in the soil cultivation system-dependent manner and would indicate the bacterial species with environmentally friendly properties. The aim of the study was to determine the percentages of operational taxonomic units (OTUs) of bacterial communities and to assess the trend of changes in the microbiome in the soil under horse beans grown in a four-field cereal rotation system (75% cereals) (horse beans, winter wheat, spring barley, winter triticale) in four different cultivation technologies (traditional (ploughing), simplified (stubble cultivator), strip till, and direct drilling into stubble).

2. Materials and Methods

2.1. Study Site Description

The research was based on soil samples collected from a horse bean plantation in the twentieth year of a static field experiment, in which four levels of the experimental factor (tillage system) were used as follows: conventional tillage (ploughing), reduced tillage (stubble cultivator), strip tillage (strip-till seed drill), and no tillage (no-tillage seed drill). Horse beans was grown in a four-year crop rotation cycle (horse beans, winter wheat, spring barley, and winter triticale).
The field experiment (split-block, four replication blocks) was started in 1999, at the Brody Agricultural Experimental Station (52°26′ N; 16°17′ E) belonging to the Poznań University of Life Sciences, Poland. The area of the experiment with horse beans was 1008 m2. The surface of a single plot was 36 m2 (9 m × 4 m), each for a specific cultivation system in four replications (blocks). Due to the use of different cultivation systems, the treatments were not allocated randomly within blocks but established in identical fixed orders within each block (Scheme 1). Blocks were selected randomly. There were no gaps between individual blocks and objects. In the experiment, seven cultivation systems were used for each plant in the rotation (horse beans, winter wheat, spring barley, and winter triticale). Objects, including conventional tillage (CT), reduced tillage (RT), strip tillage (ST), and no tillage (NT) marked green in Scheme 1, were included in the soil microbiological analyses in horse beans.
The soils of the area were classified as the typical clay–illuvial soils, according to the Polish Soil Classification [14], or as the Albic Luvisols, according to the World Reference Base for Soil Resources [15]. Clay–illuvial soils are the most widely distributed soils in the country with the largest impact on the volume of agricultural production in Poland [16]. The studied soil revealed the typical textural features with loamy sand in the surface horizons and loams in the bottom part of the soil profiles.
In the autumn of 2018, a mineral fertilizer was applied at 60 kg of phosphorus and 90 kg of potassium per 1 ha. In the spring, 40 kg N·ha−1 was applied. In early April, horse beans of the Albus cultivar were sown at a density of 60 seeds·m−2 (approx. 390 kg·ha−1). Weeds were controlled with Wing P 462.5 EC (after sowing) and Corum 502.4 SL (after the emergence of plants). The Bulldock 025 EC pesticide was applied during the pod formation period when necessary. One week before harvesting horse bean seeds, the Dessicash 20 SL herbicide was applied for desiccation. The crops were harvested with a field combine harvester in early August in 2019. During the same period, samples of soil for microbial analysis were collected.

2.2. Weather Conditions

The weather conditions (rainfall and air temperatures) during the growing season (Table 1) are shown as the Selyaninov hydrothermal coefficient (HTC), according to the following formula [17,18]:
H T C = ∑ P 0.1   ∑ T > 8 ° C ,
where ∑ P > 8 ° C —ten-day/monthly rainfall (periods with an average daily temperature above 8 °C), ∑ T > 8 ° C —ten-day/monthly average daily air temperature (periods with an average daily temperature above 8 °C).
Despite its limitations, this simple-to-calculate coefficient is useful for monitoring agricultural conditions during the growing season and drought. The HTC clearly indicates periods of excessive or optimal humidity and drought. It is flexible enough for use in both the monthly and ten-day monitoring of weather conditions [19].
Drought prevailed during the growing season. June was the driest month, with the extreme HTC values in all ten-day periods. There was no drought, with near-optimal conditions, only in May and September. In mid-May, humidity was too high, as evidenced by the HTC value.

2.3. Soil Sample Collection

The composition of the soil microbiome under the horse bean plantation was analyzed in 2019, i.e., in the twentieth year of the field experiment. Our study only included the analyses of OTU (operational taxonomic unit) composition, and indicators such as microbial biomass or sequencing read count were not considered. Soil samples were collected from the topsoil (0–20 cm) once, immediately after the harvesting of horse beans in 2019. An Egner probe was used for sampling. Because there were no spaces between the plots, soil samples for microbiological analyses and soil physicochemical properties were collected from the central part of the plot (width 2 m, ten samples per plot). For each experimental treatment, forty primary samples were collected from random points of all plots (ten samples from each plot × four replicates, blocks). They were merged into composite soil samples, each weighing about 1 kg. Apart from that, a protective strip (a fallow field, 2 m wide) was used around the entire experiment, which was not exposed to the tillage system, and from this zone, 40 primary samples were taken for the composite sample “0”, a plantless, fallow buffer zone of the field experiment. As a result, five treatments of the soil samples were distinguished (one treatment for sample “0” and four treatments representing tillage systems). They were used in microbiological analyses, where they were marked in the following way:
  • Plantless, fallow buffer zone of the field experiment—sample “0” (FA);
  • Conventional tillage (CT);
  • Reduced tillage (RT);
  • Strip tillage (ST);
  • No tillage (NT).
Both containers and tools for collecting soil samples were washed with water and ethanol (70% solution) before taking the next samples. Soil samples intended for soil microbiome analyses were stored in the dark at 4 °C for no longer than 24 h. Before laboratory analyses, roots were removed from soil samples, and the soil was sieved through a 2 mm sieve. The regular soil samples before soil chemical analysis were air-dried and crushed in a mortar to obtain homogenized material and sieved through the sieve of 2 mm mesh. The undisturbed soil samples of known volume (100 cm3) were collected by using steel rings for bulk density and water properties determination.

Chemical and Physical Analyses of Soil

Soil chemical and physical analyses were performed for each soil sample collected in different cultivation systems (CT, RT, ST, NT). Total carbon (TC) and total nitrogen (TN) content were determined using a VarioMax elemental analyzer. If inorganic carbon (in the form of carbonates) was present, TC values were corrected (inorganic carbon content is subtracted from TC content) and expressed as the soil organic carbon (SOC) content. The content of plant-available phosphorus and potassium was determined with the Egner-Riehm method; whereas, the content of plant-available magnesium was determined with the Schachtschabel method [20] (Table 2). In addition to the chemical properties of the soil, physical properties were determined, including capillary water capacity, bulk density (BD), and soil moisture (Table 3). The capillary water capacity was determined using the Richards pressure chamber method [21]. Bulk density (BD) values were determined in undisturbed samples (100 cm3) using the dry-weighing method [20]. Soil moisture was determined by using a Delta-T WET sensor (Delta-TDevicesLtd., Burwell, UK).

2.4. DNA Extraction and Next Generation Sequencing (NGS)

For DNA extraction, for each experimental treatment, 500 mg (in triplicate) was collected from a homogeneous bulk soil sample using the Genomic Mini AX Soil kit (A&A Biotechnology), according to the manufacturer’s instructions [22]. This allowed for three independent DNA extractions. DNA quantity and purity were assessed using the Quant-iT HS dsDNA assay kit (Invitrogen) on a Qubit2 fluorometer. When three DNA samples did not show differences in purity and quantity, the materials were combined and mixed to increase OTU richness, as already reported by Soliman et al. [23]. The authors demonstrated that combining DNA extractions from individual soil samples increased OTU richness.
The metagenomic analysis was based on the hypervariable region V3–V4 of the 16S rRNA gene. Polymerase chain reaction (PCR) was performed using the Q5 Hot Start High-Fidelity DNA Polymerase Kit (New England Biolabs). The reaction mixture consisted of 15 ng DNA, 1 µL of primers 341F: TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG and 785R: GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC, 12.5 µL of Q5 Hotstart High-Fidelity 2× Master Mix (New England Biolabs), and Milli-Q water to a final volume of 25 µL. The following PCR conditions were used: 98 °C for 30 s (initial denaturation), followed by 25 cycles of 98 °C for 10 s, 55 °C for 30 s, 72 °C for 20 s, with the final step performed at 72 °C for 2 min [24]. The resulting amplicons were purified using AMPure XP Beads (Beckman Coulter) at a ratio of 0.8 times the sample volume. Sequencing was performed using a MiSeq sequencer with 2250 bp paired-end (PE) technology, 144,429.7 of 23 using the Illumina v2 chemistry kit, according to the Illumina MiSeq PE300 software (Genomed S.A., Warsaw, Poland) [24,25].

2.5. Bioinformatics and Statistical Analyses

The sequences were subject to bioinformatics analyses, such as clustering and separation of OTUs. The reads were demultiplexed and classified into taxonomic categories based on the GreenGenes version 13.8 database (LBNL, Berkeley, CA, USA) [26]. As a result, the taxonomic profiles of the bacteria of each experimental treatment were generated, including the number of reads for each taxon. The data are available under accession number BioProject ID PRJNA1208264 (GenBank, NCBI, ID 1208264—BioProject—NCBI).
The normality of the distributions for the studied traits was tested using Shapiro–Wilk’s normality test. The homogeneity of variance was verified using Bartlett’s test, while Box’s M test checked the multivariate normality and the homogeneity of the variance–covariance matrices. Statistical analysis of the collected data was performed using a mixed-model analysis of covariance. Cultivation systems were specified as a fixed factor and blocks as a random factor. The location variable was treated as a covariate to analyze trends in the data across the four non-random treatments. Mean values and least significant differences (LSDs) were calculated. A comparative analysis of genus composition between experimental treatments was visualized using several types of plots [27]. Differences in the mean numbers of bacteria between the treatments were calculated and visualized. The significance of differences was tested using the two-sided Student’s t-test. Data were also analyzed using multivariate statistical methods. All analyses were conducted using the statistical package Genstat version 23.1 [28].

3. Results and Discussion

The Shapiro–Wilk normality test showed that all traits had a normal distribution, with test statistic W values ranging from 0.7444 to 0.9694. The values of Bartlett’s test for homogeneity of variances ranged from 20.17 to 84.23.
The metapopulation analysis based on the analysis of 16S rRNA sequences showed that different cultivation technologies influenced the number of operational taxonomic units (OTUs) of the bacteria found in the soil under the horse beans (treatments 2–5), as compared with the plantless control soil (sample “0”) collected from the fallow buffer zone of the experiment (treatment 1, FA). Although our results are from one obtained composite sample for each experimental treatment, we found a positive effect of horse bean cultivation technology on the development of beneficial microorganisms in the soil that are important for the healthy functioning of the agroecosystem. Depending on the soil experimental field with various treatments, a total of 32 phyla, 63 classes, 133 orders, and 1900 species of bacteria were identified in the analyzed taxa; however, only those whose average number of OTUs exceeded 1% were presented.
The results showed that, in each of the soil samples collected from the individual experimental treatments of cultivation (1–5) at the horse bean plantation, the percentage of OTUs of the Bacteria domain was over 99.96–99.98% of the microbiome; whereas, the percentage of OTUs of the Archaea domain amounted to 0.02–0.03% (Table S1). The 16sRNA analyses indicated the dominance of the Bacteria domain in soils with different cultivation systems and a small percentage of the Archaea domain, characterized by dominance in extreme environments, i.e., high salinity and alkalinity [29].

3.1. Dominant Phyla of Soil Bacteria Under Horse Beans Cultivated in Different Systems

The 16S rRNA metagenomic analysis of the soil metabiome revealed the dominance of three phyla of bacteria: Actinobacteria, Firmicutes, and Proteobacteria, which were found in all experimental treatments. There were similar findings presented in publications on arable soils [30,31,32].
The metagenomic analyses showed that, among all bacterial phyla identified in sample “0” and in the soil samples collected from the horse bean plantation, Actinobacteria were predominant. The percentage of OTUs was as follows: sample “0” collected before the experiment—41.19% (treatment 1), traditional tillage (treatment 2)—39.57%, reduced tillage (treatment 3)—43.10%, strip tillage (treatment 4)—50.72%, and direct drilling (treatment 5)—40.04% (Figure 1). The reads of Actinobacteria were particularly abundant from soil DNA, where the strip tillage system was applied (treatment 4) (Figure 1).
Apart from the assessment and identification of the dominant phyla in the soil samples, differences in the number of OTUs between the soil samples collected from the horse beans grown in different cultivation systems and the control soil were analyzed: CT vs. FA, RT vs. FA, ST vs. FA, and NT vs. FA. They are shown in Figure 2.
All four comparisons showed that, in the experimental treatments, the Acidobacteria and Gemmatimonadetes phyla were more abundant than in sample “0” collected from the fallow buffer zone of the experiment. An inverse relationship was observed for the Verrucomicrobia phylum. The percentage of OTUs in sample “0” was always greater than in the soils cultivated in different systems. The largest positive difference in the number of OTUs (9.54%) in relation to sample “0” was observed for the Actinobacteria phylum in the strip-till treatment. In the same cultivation system, the largest negative difference (−7.39%) was observed for the Proteobacteria phylum (Figure 2).
As observed by Swędrzyńska and Małecka-Jankowiak [11], Actinobacteria are a saprophytic group of microorganisms which adapt and proliferate intensively in an environment with high availability of organic matter. This effect could be seen in the strip tillage system, as well as in the soil under a horse bean plantation. Bao et al. [33] also observed the dominance of Actinobacteria, especially in less fertile soils with a supply of additional organic matter (rice straw). The researchers indicated the important eco-physiological role of these microorganisms. Actinobacteria communities broadly adapt to the decomposition of plant residues. They are of potential significance for the decomposition of these residues and carbon sequestration in the soil. This phylum mineralizes organic material. Similarly to oligotrophic microorganisms, it spares carbon in the soil, which additionally proves its ecological role in the pedon [34,35]. It is important to note that Actinobacteria can quickly adapt to unfavorable environmental conditions, such as drought by producing conidia. This is why they are capable of decomposing organic matter even at low soil moisture. Our study confirmed this fact, as evidenced by the weather conditions during the experiment (Table 1).
Proteobacteria was another dominant phylum in our study. Its relative OTU numbers ranged from 24.60% in the strip-till treatment to 35.67% in the reduced tillage system (Figure 1). The study by Mahnkopp-Dirks et al. [36] also showed that Proteobacteria was the dominant phylum in agricultural soils. Fierer et al. [35] proposed a concept of bacterial classification in which Proteobacteria phyla were described as fast-growing copiotrophs, i.e., microorganisms developing in environments with a high supply of carbon. Their numbers were closely correlated with the degree of carbon mineralization in the soil.
Our study also showed that Firmicutes, Planctomycetes, Chloroflexi, Acidobacteria, Bacteroidetes, and Verucomicrobia were dominant in all soil treatments (1–5). Gemmatimonadates was also a dominant phylum but only in the soil under horse beans in various cultivation systems. Its number of OTUs was the greatest in the direct drilling system—3.29% (Figure 1).
The Firmicutes, Planctomycetes, Chloroflexi, Acidobacteria, Bacteroidetes, and Verrucomicrobia phyla were isolated less frequently (Figure 1).
Chloroflexi is a phylum of anaerobic or microaerophilic nitrifying bacteria, which can survive in extreme and intensively changing conditions. Chloroflexi occurred more frequently in treatment 1 in sample “0” (fallow). This can be explained by the fact that these bacterial communities develop by using cellular compounds from dead microorganisms and their metabolites, which is characteristic of uncultivated (fallow) or exhausted soils. Tang et al. [37] observed a similar dominance of this group of microorganisms. The researchers used rice straw and biochar to effectively improve the soil quality and, thus, reduce the numbers of this bacterial phylum.
The Firmicutes phylum includes bacteria of the Bacillus and Clostridium genera, which produce spores in unfavorable environmental conditions. The phylum was dominant in treatment 1; whereas, in the treatments with horse beans grown in different cultivation systems, the percentage of its OTUs was on average 1–2% lower (Figure 1).
Bacteria of the Verrucomicrobia phylum are cosmopolitans in the rhizosphere. Their adaptations and functions are enigmatic, because so far, a low percentage of members of the phylum have been cultured. However, research has shown that Verrucomicrobia plays a key role in environmental carbon cycling and (poly)saccharide degradation, because they have a high capacity to encode glycoside hydrolase genes [38].
The occurrence of the Gemmatimonadates phylum in the soil samples of the four cultivation systems collected from the horse bean plantation was higher than in the fallow soil sample “0” (Figure 1). According to the data in reference publications, Gemmatimonadota is the eighth most abundant phylum of soil bacteria, with a share of about 1–2% worldwide [39]. DeBruyn et al. [40] proved that, although Gemmatimonadota can be found in various environments, the maximum number of their sequences comes from soils used in different ways, including grassland soils, agricultural soils, forest soils, and contaminated soils. The cosmopolitan distribution of Gemmatimonadota in different soils suggests that they are generalist species with a versatile metabolism, and they can adapt to a wide range of nutrients. Mujakić et al. [41] and Liu et al. [42] found that Gemmatimonadota are a bacterial phylum whose numbers in soil increase with the presence of vegetation in the field. The relative OTU numbers within the phylum then increase strongly and exceeds 2%. Moreover, the bacteria are positively correlated with plant species richness and soil nutrients, mainly carbon. Gemmatimonadota are one of the seven more dominant bacterial phyla, with numbers above 1%. The bacteria are positively correlated with total carbon, nitrogen, and phosphorus in the soil. Studies by Deng et al. [43] and Ye et al. [44] showed that the high concentration of nutrients stimulated the numbers of Gemmatimonadota and suggested that the bacteria could play a key role in soil ecosystems. In our study, there was an increased relative OTU number of Gemmatimonadota due to the applied cultivation systems and the crop, i.e., horse bean (Figure 2). These results were in line with the properties of Gemmatimonadota described in the reference publications. Legumes have been widely studied due to their significant ecological benefits. They enrich the soil with organic matter by leaving a large mass of crop residues (straw and roots), i.e., 3–6 t ha−1. They are capable of biological nitrogen fixation by establishing symbiosis with bacteria from the Rhizobiaceae family. This is particularly important on light soils, because it increases the sorption complex [45] and creates a better environment for the biodiversity of the soil microbiome.
The analysis of differences (Figure 2) showed that Actinobacteria in the soils cultivated in different systems (except CT) was statistically significant (p < 0.05), greater than in sample “0”. In CT, Actinobacteria was statistically (p < 0.05) smaller than in FA (Figure 2). Acidobacteria in the RT was statistically (p < 0.05) greater than in sample “0”. According to Lee et al. [46], the occurrence of the Acidobacteria phylum is correlated with the physicochemical properties of soils. It is characteristic of soils on which rice is grown as well as orchard soils, with limited oxygen access due to soil compaction and generally deteriorating conditions for bacteria. Li et al. [47] conducted a fifteen-year experiment, in which the no-tillage cultivation system was mostly used. The researchers observed an increased number of the Acidobacteria phylum and concluded that conservation tillage increased the biodiversity of the microbiome. Our observations of changes in the numbers of bacterial communities belonging to specific phyla in the soil samples collected from different cultivation systems under the horse bean plantation were in line with the findings of the aforementioned studies. Statistically significant differences were also observed for Firmicutes, Gemmatimonadetes, Planctomycetes, and Proteobacteria between CT and FA; for Chloroflexi, Firmicutes, Gemmatimonadetes, Planctomycetes, and Proteobacteria between RT and FA; for Proteobacteria between ST and FA; as well as for Chloroflexi, Firmicutes, Gemmatimonadetes, Planctomycetes, and Proteobacteria between NT and FA (Figure 2).
The first two principal coordinates explained 96.45% of the variance in the cultivation systems based on the percentages of operational taxonomic units’ dominant phyla of bacteria (Figure 3A). The cultivation systems formed three groups. One of them was FA and CT, another was RT and NT, and the other was ST, which was clearly different from the others (Figure 3A).

3.2. Dominant Classes and Orders of Soil Bacteria Under Horse Beans Cultivated in Different Systems

The metagenomic analysis showed that the type of soil cultivation system used at the horse bean plantation affected the content of bacterial OTUs within classes and orders. Also, in this case, only the orders and classes with >1% are reported (Figure 4). Actinobacteria and Alphaproteobacteria were the dominant classes with percentages 6.09–7.05% (Figure 4). These differences were statistically significant (p < 0.05).
Khmelevtsova et al. [48] observed similar dependencies related to the use of different reduced cultivation technologies. The researchers found a large number of OTUs in the classes of Actinobacteria and Alphaproteobacteria in no-tillage (NT) and reduced tillage (RT) systems. They explained that the increased growth of Actinobacteria was caused by their greater sensitivity to physical disturbances due to their hyphal structure. Deep ploughing disrupted their mycelium, which broke the hyphae of Actinobacteria. Although the diameter of S. coelicolor cells is smaller than 1 μm, it may reach 100 μm due to the elongation of hyphae at the ends by the membrane vesicle transporter [49].
Our study showed that Alphaproteobacteria was another class that was frequently isolated in the soils under horse beans grown in different cultivation systems. The percentages of (OTUs) of this class amounted to 18.34% in sample “0”, 18.98% in the traditional cultivation treatment (ploughing), 20.41% in the reduced tillage treatment (stubble cultivator), 13.96% in the strip till treatment, and 20.43% in the treatment with direct drilling into stubble (Figure 4). Alphaproteobacteria are classified as oligotrophs, as they use organic resources very sparingly. Apart from oligotrophic bacteria, this class also includes the bacteria of agricultural significance, capable of fixing nitrogen in symbiosis with plants [50,51]. Batut et al. [52] observed that many Alphaproteobacteria interacted with higher eukaryotes. These interactions range from pericellular colonization, through facultative intracellular multiplication, to enforcing an intracellular lifestyle. This wide range of interactions has a common feature—the modulation of proliferation of host cells. This sometimes leads to the formation of structures known as nodules in which bacteria can grow.
Apart from the assessment and indication of the dominant classes in the soil samples, relative differences in the number of OTUs between a specific soil treatment collected from under horse beans grown in different cultivation systems (traditional tillage, reduced tillage, strip tillage, and direct drilling), and the control soil sample were also analyzed (CT vs. FA, RT vs. FA, ST vs. FA, ST vs. NT). The results are shown in Figure 5. In all four comparisons, the numbers of Actinobacteria and Gemmatimonadetes classes in the soils cultivated in different systems was significant (p < 0.05) greater than in sample “0”—plantless, fallow buffer zone of the field experiment. There was an inverse relationship observed for the Acidimicrobiia, Brocadiae, and Clostridia classes. The relative OTU numbers belonging to these classes in sample “0” was always statistically significant (p < 0.05) greater than in the other experimental treatments. The comparison with sample “0” (plantless, fallow buffer zone of the field experiment) revealed the highest relative difference (10.63%) for Actinobacteria in the strip-till system (ST vs. FA). The greatest decrease in OTUs was observed for Alphaproteobacteria in the same cultivation system (Figure 5). Moreover, statistically significant differences were observed for Betaproteobacteria, Clostridia, Deltaproteobacteria, Planctomycetia, and Thermoleophilia between CT and FA; for Bacilli, Betaproteobacteria, Clostridia, and Deltaproteobacteria between RT and FA; for Betaproteobacteria, Clostridia, Deltaproteobacteria, and Sphingobacteriia between ST and FA; as well as for Bacilli, Betaproteobacteria, Clostridia, Deltaproteobacteria, Gammaproteobacteri, Sphingobacteriia, and Thermoleophilia between NT and FA (Figure 5).
The first two principal coordinates explained 95.18% of the variance in the cultivation systems based on the percentages of operational taxonomic units’ dominant classes of bacteria (Figure 3B). The cultivation systems formed three groups. One of them was FA and CT, another was RT and NT, and the other was ST, which was clearly different from the others (Figure 3B).
The share of OTUs of unclassified bacterial orders ranged from 7.18% to 9.49%, depending on the cultivation system. The dominant orders were Actinomycetales, followed by Bacillales and Rhizobiales (Figure 6).
According to Anandan et al. [53], there are 16 orders in the Actinobacteria class. These are Actinomycetales, Actinopolysporales, Bifidobacteriales, Catenulisporales, Corynebacteriales, Frankiales, Glycomycetales, Jiangellales, Kineosporiales, Micrococcales, Micromonosporales, Propionibacteriales, Pseudonocardiales, Streptomycetales, Streptosporangiales, and Incertae sedis.
In our study, Actinomycetales was the only order whose percentage of OTUs exceeded 1%. The highest relative share of OTUs of this order, i.e., 44.21%, was found in treatment 4 (strip-till cultivation); whereas, the lowest share, i.e., 33.62% was found in sample “0” (plantless, fallow buffer zone of the field experiment) (Figure 6). The results of our study are in line with the findings of the research conducted by Bao et al. [33], who observed the dominance of this group of bacteria, especially in less fertile soils with the inflow of additional organic matter. According to Mokni-Tlili et al. [54], the dominance (numbers and distribution) of Actinomycetales, which play an important role in the decomposition of organic matter, may indicate good soil fertility.
Apart from the Actinomycetales order, there was also a large percentage of OTUs of the Bacillales order, which belongs to the Firmicutes phylum. The dominance of this group of bacteria depends on the source of carbon rather than the pH of the soil environment due to their ability to produce spores. In our study, the largest numbers of OTUs of this order were found in treatments RT, ST, and NT, in which reduced tillage technologies (reduced tillage, strip tillage, and direct drilling) were used (Figure 6). On average, the shares of this order in these treatments were 1.5–2% greater than in the conventional tillage (ploughing) treatment and in the soil sample “0” collected from the plantless, fallow buffer zone of the experiment. According to the data provided in the reference publications, the presence of these bacteria in soil ecosystems is crucial for the decomposition of organic matter, as they decompose dead plant and animal material and, thus, release nutrients back into the soil. The decomposition process not only enriches the soil but also facilitates the formation of humus, a stable organic component that improves soil structure, water retention, and aeration. The activity of Bacillales bacteria in the nutrient cycle helps to maintain plant growth by creating a dynamic balance in the soil ecosystem. Many species within the Bacillales order interact with other soil organisms, which indicates the ecological importance of these bacteria. Bacillales often colonize the rhizosphere and, thus, establish symbiosis with plants. They facilitate the uptake of nutrients in this microenvironment by converting them into forms available to plants. In consequence, the health and immunity of plants improve. This interrelation may increase agricultural productivity, thus indicating the integral role of Bacillales in supporting sustainable agriculture [55].
Unlike Bacilalles, there was an inverse relationship observed for the Rhizobiales order. Its numbers were lower in the treatments with reduced tillage (Figure 6). This order of bacteria includes both plant and animal pathogens, such as the Brucella and Bartonella genera, the Agrobacterium genus, as well as nitrogen-fixing bacteria, including the Rhizobium, Sinorhizobium, and Bradyrhizobium genera [56]. The decrease in the number of OTUs of bacteria belonging to the Rhizobiales order can be explained by the fact that the proliferation and activity of symbiotic diazotrophic bacteria are inhibited by the inflow of mineralized organic matter, especially the available forms of nitrogen [57]. The results of our study were in line with the aforementioned assumptions. The numbers of the Rhizobiales order were most reduced in treatment 4 (strip-till cultivation) (Figure 6).
The first two principal coordinates explained 95.07% of the variance in the cultivation systems based on the percentages of operational taxonomic units’ dominant orders of bacteria (Figure 3C). The cultivation systems formed three groups. One of them was FA and CT, another was RT and NT, and the other was ST, which was clearly different from the others (Figure 3C).

3.3. Dominant Bacterial Species in Different Soil Cultivation Technologies Under Horse Bean Plantation

Our study also included an assessment of the dominance of specific bacterial species in the soil samples collected from individual cultivation systems (conventional tillage, reduced tillage, strip tillage, and no tillage) in relation to the uncultivated soil (NC—no cultivation). The percentages of OTUs of unclassified bacterial species ranged from 58.44% to 61.83% (Figure 7). The dominant species were Arthrobacter psychrochitiniphilus, Cohnella soli, and Nocardioides islandensis. In order to interpret the results more precisely, our analyses also included finding relative differences in the numbers of the dominant species between the samples of soil collected from different cultivation systems under the horse bean plantation and the zero-sample collected from the plantless, fallow buffer zone (Figure 7). The comparisons of all four treatments with sample “0” revealed an increase in the OTUs of the following species: Aeromicrobium ponti, Arthrobacter psychrochitiniphilus, Cohnella soli, and Gemmatimonas aurantiaca. By contrast, the numbers of the Candidatus Scalindua brodae and Nocardioides islandensis species in all four treatments was lower than in sample “0”. The greatest increase (p < 0.05) in the share of OTUs (3.90%) in relation to sample “0” was observed for the Arthrobacter psychrochitiniphilus species in the no-tillage treatment. The greatest decrease in the share of OTUs (−1.25%) in relation to sample “0” was observed for the Nocardioides islandensis species in the reduced tillage treatment (Figure 8). These differences were statistically significant (p < 0.05) between CT vs. FA and RT vs. FA. However, comparisons of ST vs. FA and NT vs. FA did not show statistically significant differences (p > 0.05) (Figure 8). Moreover, statistically significant differences were observed for Candidatus Scalindua brodae and Chondromyces pediculatus between CT and FA; for Candidatus Scalindua brodae between RT and FA; as well as for Candidatus Scalindua brodae and Frankia alni between ST and FA (Figure 8).
Aeromicrobium ponti is a species known for its potential to produce a variety of natural products and secondary metabolites with antimicrobial, antioxidative, and plant growth-stimulating properties [58]. It is a beneficial species for the soil environment and important for the proper functioning of the crop agroecosystem, especially in sustainable agriculture. The Arthrobacter psychrochitiniphilus species has oligocarbophilic properties, i.e., economical carbon management. The bacteria have low temperature requirements. According to the reference publications, the Arthrobacter genus belongs to the group of plant growth-promoting bacteria (PGPB) due to its metabolic activity (the production of hormones, increasing the availability of nutrients, the production of antifungal substances, the colonization of plant roots, etc.). It offers an environment-friendly approach to improved plant production and counteracting the negative effects of abiotic stress [59,60].
Gemmatimonas aurantiaca is another species with an important environmental role. In our study, the greatest percentages of OTUs of this species were observed in treatments 3 (1.05%), 4 (0.93%), and 5 (2.53%, i.e., in all no-tillage technologies (Figure 7). This species was also found in sample “0” and in the conventional cultivation treatment, but the shares of OTUs were much lower, i.e., 0.12% and 0.59%, respectively. Studies have shown that Gemmatimonas aurantiaca can reduce nitrous oxide (N2O). N2O is one of the most important greenhouse gases degrading the ozone layer of the stratosphere. Since the beginning of the industrial era, its concentration in the atmosphere has increased significantly (from 270 ppb to 332 ppb). One of the reasons for this increase is the widespread use of nitrogen fertilizers in agriculture [61,62,63,64]. Microorganisms synthesizing nitrous oxide reductase (NosZ), including Gemmatimonas aurantiaca, are the only known biological factor capable of reducing the emission of soil-derived N2O to an extent that is significant for the environment [65].
The first two principal coordinates explained 94.97% of the variance in the cultivation systems based on the percentages of operational taxonomic units’ dominant species of bacteria (Figure 3D). The cultivation systems formed three groups. One of them was FA and CT, another was RT and NT, and the other was ST, which was clearly different from the others (Figure 3D).

4. Conclusions

It is widely known that both soil fungi and bacteria play a key role in the course of most biochemical changes occurring in the soil as well as in the maintenance of soil health. In recent years, there have been numerous studies on the influence of agrotechnical factors related to the use of new technologies, including no-tillage farming systems, on the composition of communities of soil bacteria. However, it is still difficult to clearly determine the influence of individual factors on the numbers and diversity of the soil microbiome and to directly relate these parameters to soil fertility and crop productivity. This is due to the large diversity of soils as well as other environmental and agrotechnical factors. So far, there have been controversial results of studies on the influence of a specific farming technology on communities of soil bacteria. There are a few criteria defining the optimal quantitative, trophic, and taxonomic structure of the microbiome in the context of soil health and environmental functions. Therefore, further research is necessary in order to indicate the phyla or even species of bacteria or other groups of environmentally beneficial microorganisms for climate change and for the fertility of the soil.
Our study showed that the no-tillage cultivation technologies, mainly the strip-till and no-tillage methods, applied at the horse bean plantation had a positive influence on microbial communities. The percentages of OTUs of species, such as Gemmatimonas aurantiaca and Aeromicrobium ponti, increased. The numbers of these species can determine soil fertility and the yield of crops and are, therefore, very important for sustainable or even regenerative agriculture. They are also environment- and climate-friendly. Hence, further analyses are necessary to confirm our results. Although, at present, it is impossible to make an unequivocal statement, the results of our unpublished studies in soil samples collected from the plantations of other species from the Fabaceae family (soybean, white lupine) pointed to the presence of Gemmatimonas aurantiaca only at the plantations of species representing this botanical family, regardless of the cultivation system. Further investigations of soil samples collected from the plantations of crops belonging to the Fabaceae family may indicate the beneficial species of microorganisms that are important for the healthy functioning of the agroecosystem and that can be important for climate change. A larger number of results based on further investigations would not only unambiguously confirm the fact that the cultivation of species of the Fabaceae family has a positive influence on soil fertility. They would also facilitate limiting climate change by reducing the emissions of N2O, which is one of the most important greenhouse gases and a factor degrading the stratospheric ozone layer. These emissions could be reduced by a soil biological factor, i.e., the Gemmatimonas aurantiaca species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app15031468/s1, Table S1: The Kingdom classification results.

Author Contributions

Conceptualization, D.S., A.N., A.W.-M., and J.B.; methodology, D.S., A.N., Ł.W., and A.W.-M.; software, J.B. and R.G.; validation, D.S., A.N., A.W.-M., A.P., and Ł.W.; formal analysis, D.S., A.N., A.W.-M., A.P., and J.B.; investigation, D.S., A.N., and A.W.-M.; resources, R.G. and J.B.; data curation, D.S., A.N., and A.W.-M.; writing—original draft preparation, D.S., J.B., A.W.-M., A.S., and A.N.; writing—review and editing, D.S., A.N., A.W.-M., A.S., J.B., and Ł.W.; visualization, J.B., R.G., and A.P.; supervision, D.S., A.N., and J.B.; project administration, D.S., A.S., and A.N.; funding acquisition, J.B. All authors have read and agreed to the published version of the manuscript.

Funding

Project 222/2015/3 “Increasing the use of domestic feed protein for the production of high-quality animal products in sustainable development conditions” (2016–2020). Research area no. 3 “Agrotechnical methods for increasing the use of the biological potential of legumes in terms of production, environmental, and economic effects”, Ministry of Agriculture and Rural Development. Thanks to retired Professor Irena Małecka from the Department of Agronomy, Poznań University of Life Sciences.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are available under accession number BioProject ID PRJNA1208264 (GenBank, NCBI, ID 1208264—BioProject—NCBI).

Conflicts of Interest

The authors declare no conflicts of interest.

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Applsci 15 01468 sch001
Scheme 1. A field experiment with horse bean. A, B, C, D—blocks, Columns 1–7—objects with different cultivation systems: 1. Conventional tillage used annually (CT). 2. Reduced tillage used annually (RT). 3. Direct sowing in stubble alternating with reduced tillage. 4. Direct sowing in stubble for two years interrupted by one year of reduced tillage. 5. Strip tillage used annually (ST). 6. Direct sowing in stubble for five years interrupted by one year of conventional tillage. 7. No-tillage—direct sowing in stubble is used annually (NT).
Scheme 1. A field experiment with horse bean. A, B, C, D—blocks, Columns 1–7—objects with different cultivation systems: 1. Conventional tillage used annually (CT). 2. Reduced tillage used annually (RT). 3. Direct sowing in stubble alternating with reduced tillage. 4. Direct sowing in stubble for two years interrupted by one year of reduced tillage. 5. Strip tillage used annually (ST). 6. Direct sowing in stubble for five years interrupted by one year of conventional tillage. 7. No-tillage—direct sowing in stubble is used annually (NT).
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Figure 1. The percentages of operational taxonomic units (OTUs) of dominant phyla of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
Figure 1. The percentages of operational taxonomic units (OTUs) of dominant phyla of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
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Figure 2. Relative OTU numbers of dominant phyla of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
Figure 2. Relative OTU numbers of dominant phyla of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
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Figure 3. Principal coordinate analysis (PCoA) was performed to detect the percentages of operational taxonomic units (OTUs) between individual cultivation systems dominant: (A) phyla, (B) classes, (C) orders, and (D) species of bacteria. FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage.
Figure 3. Principal coordinate analysis (PCoA) was performed to detect the percentages of operational taxonomic units (OTUs) between individual cultivation systems dominant: (A) phyla, (B) classes, (C) orders, and (D) species of bacteria. FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage.
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Figure 4. The percentages of operational taxonomic units (OTUs) of the dominant classes of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
Figure 4. The percentages of operational taxonomic units (OTUs) of the dominant classes of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
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Figure 5. Relative OTU numbers of dominant classes of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
Figure 5. Relative OTU numbers of dominant classes of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
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Figure 6. The percentages of operational taxonomic units (OTUs) of the dominant orders of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
Figure 6. The percentages of operational taxonomic units (OTUs) of the dominant orders of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
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Figure 7. The percentages of operational taxonomic units (OTUs) of the dominant species of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
Figure 7. The percentages of operational taxonomic units (OTUs) of the dominant species of bacteria. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage).
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Figure 8. Relative OTU numbers of dominant bacteria species. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
Figure 8. Relative OTU numbers of dominant bacteria species. The classifications with less than 1% numbers are gathered into the category “Other” (FA—plantless, fallow buffer zone of the field experiment—sample “0”; CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; “red” means negative difference; “green” means positive difference). * p < 0.05; ns—not significant.
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Table 1. The monthly and ten-day values of the HTC in the growing season.
Table 1. The monthly and ten-day values of the HTC in the growing season.
PeriodMonth
AprMayJuneJulyAugSep
1st ten days0.001.730.030.320.651.75
2nd ten days0.964.710.061.390.500.62
3rd ten days0.521.670.281.320.221.94
month0.452.560.131.050.441.47
>3.02.6–3.02.1–2.61.7–2.11.4–1.71.1–1.40.8–1.10.4–0.8<0.4
Extremely humidVery humidHumidQuite humidOptimumQuite dryDryVery dryExtremely dry
Table 2. Chemical properties of soil after 19 years of using different cultivation systems (mean values for 2019 Agricultural Experimental Station in Brody).
Table 2. Chemical properties of soil after 19 years of using different cultivation systems (mean values for 2019 Agricultural Experimental Station in Brody).
ParameterCultivation SystemLSD0.05
CTRTSTNT
SOC (g kg−1)7.629.029.6610.640.73
Total N (g kg−1)0.931.021.171.10.07
C/N8.28.99.19.70.6
P (mg kg−1)208198200199n.s.
K (mg kg−1)14118218819617.5
Mg (mg kg−1)27.841.844.753.74.6
Abbreviation: CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; SOC—soil organic carbon; LSD—least significant difference; n.s.—not significant.
Table 3. Physical properties of soil after harvesting horse beans (Agricultural Experimental Station in Brody, mean values for 2016–2019).
Table 3. Physical properties of soil after harvesting horse beans (Agricultural Experimental Station in Brody, mean values for 2016–2019).
Cultivation SystemSoil Moisture%Bulk Density
g cm−3		Capillary Water Capacity%
0–20 cm0–20 cm0–20 cm
CT14.11.4435.6
RT15.61.5532.9
ST
-row14.71.4636.6
-inter-row15.91.5730.6
NT16.41.6031.6
LSD0.050.70.082.1
Abbreviation: CT—conventional tillage; RT—reduced tillage; ST—strip tillage; NT—no tillage; SOC—soil organic carbon.
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Swędrzyńska, D.; Bocianowski, J.; Wolna-Maruwka, A.; Swędrzyński, A.; Płaza, A.; Górski, R.; Wolko, Ł.; Niewiadomska, A. Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies. Appl. Sci. 2025, 15, 1468. https://doi.org/10.3390/app15031468

AMA Style

Swędrzyńska D, Bocianowski J, Wolna-Maruwka A, Swędrzyński A, Płaza A, Górski R, Wolko Ł, Niewiadomska A. Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies. Applied Sciences. 2025; 15(3):1468. https://doi.org/10.3390/app15031468

Chicago/Turabian Style

Swędrzyńska, Dorota, Jan Bocianowski, Agnieszka Wolna-Maruwka, Arkadiusz Swędrzyński, Anna Płaza, Rafał Górski, Łukasz Wolko, and Alicja Niewiadomska. 2025. "Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies" Applied Sciences 15, no. 3: 1468. https://doi.org/10.3390/app15031468

APA Style

Swędrzyńska, D., Bocianowski, J., Wolna-Maruwka, A., Swędrzyński, A., Płaza, A., Górski, R., Wolko, Ł., & Niewiadomska, A. (2025). Diversity of Bacterial Communities in Horse Bean Plantations Soils with Various Cultivation Technologies. Applied Sciences, 15(3), 1468. https://doi.org/10.3390/app15031468

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