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Mixed irrigation affects the composition and diversity of the soil bacterial community

  • Jieru Zhao , Juan Wang , Bingjian Cui , Biyu Zhai , Chao Hu , Yuan Liu , Lu Xia , Chuncheng Liu EMAIL logo and Zhongyang Li EMAIL logo
Published/Copyright: July 11, 2024
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Open Geosciences
From the journal Open Geosciences Volume 16 Issue 1

Abstract

Water resource shortage has become an important factor limiting agricultural sustainability in China. In addition, the development and utilization of unconventional water resources are greatly important for alleviating agricultural water resource deficit. The Pakchoi was cultivated by using the surface soil (0–20 cm) from the field in this pot experiment. The experiment lasted for approximately 1 month to study microbial community structure variation under brackish water and reclaimed water irrigation. The 16S rDNA high-throughput assays revealed that soil bacteria mainly consisted of Proteobacteria and Actinobacteria at the Phylum level, along with Arenimonas and Nocardioides at the Genus level under mixed irrigation with brackish water and reclaimed water. In summary, irrigation with pure reclaimed water promoted part of microbial communities and irrigation with pure brackish water inhibited the growth and activities of certain microbial communities. We found that mixed irrigation improved the microbial community structure diversity compared with that in response to pure brackish water irrigation, while decreased the community structure diversity compared with that in response to fresh water irrigation and pure reclaimed water irrigation.

Keywords: brackish water; reclaimed water; mixed irrigation; microbial diversity

1 Introduction

With the rapid growth of the economy, water shortage has become an important factor restricting agricultural development. The available fresh water resource only accounts for 0.26% of the total water resource, drought, and water shortage phenomena are becoming more and more severe [1]. The contradiction between the supply and demand of agricultural water resources is extremely prominent in arid areas in the north part of China, where irrigated area accounts for 35% of total national cultivated land. Moreover, there are even few water resources per capita in the northwest part, and this imbalance is particularly prominent, seriously restricting the stable development of agricultural production [2].

In arid and semiarid areas, unconventional water resources such as brackish water have to be used for irrigation to ensure crop yield [3]. As a high sodium adsorption ratio (SAR) in brackish water may have negative impacts on soil, measures should be taken to use it as an irrigation water source. These measures include (1) soil improvements by adding gypsum and other soil amendments to reduce sodium ion content and improve soil structure, water permeability, and permeability [4]; (2) establishing effective drainage systems to prevent soil salinization and maintain soil health [5]; (3) controlling the amount and frequency of irrigation water to avoid excessive soil salinization, regularly monitoring soil salinity, and adjusting irrigation strategies based on monitoring results [6]; and (4) selecting salt-tolerant crops for planting to mitigate adverse effects on crop growth [7]. Therefore, the development and utilization of brackish water, reclaimed water, and other unconventional water resources are highly important for alleviating agricultural water resource problems.

The main unconventional water resources include reclaimed water, brackish water, rainwater, mine water, and seawater. Agricultural irrigation is dominated by reclaimed water and brackish water. Brackish water is generally distributed underground and refers to water with a mineralization degree of 2–5 g L−1. Reclaimed water refers to water that, after being treated with appropriate regeneration processes for domestic sewage, industrial wastewater, and collected rainwater, meets the specified water quality standards and certain functional requirements, and can be reused for beneficial purposes. Within a certain range, brackish water irrigation can stimulate crop growth, not only by significantly reducing or increasing yield but also by improving water use efficiency [8]. However, brackish water contains large amounts of Na+ and Cl−. Salt ions in the soil will increase the soil bulk density [9], reduce soil porosity [10], decrease soil permeability [11], increase soil cohesion [12] and pH, reduce soil organic matter (SOM) content [13], and cause soil water repellency [14]. Studies have shown that salinity has adverse effects on soil microbial activity and community structure, and that application of brackish water is restricted by the secondary salinization of soil caused by impractical irrigation [15]. Compared with untreated wastewater, reclaimed water contains nutrients such as nitrogen, phosphorus, and kalium and has a lower salinity, which can reduce the number of soil bacteria and the relative abundance of Acidobacteria and Actinobacteria [16]. The reclaimed water is relatively inexpensive and has a low salinity, and it is stable and reliable and has become an important supplementary water source for agricultural irrigation worldwide, especially in arid and semiarid areas of China [17].

At present, most of the research on mixed irrigation using brackish water and reclaimed water has focused on the effects of brackish water irrigation or reclaimed water irrigation on crop physiological characteristics, soil properties, as well as crop growth and development. Research on the related aspects of mixed irrigation has involved mainly soil repellency [18], soil enzyme activity [19], soil characteristics [8], and the physiological characteristics of crops [20]. However, it is not clear whether mixed irrigation using brackish water and reclaimed water will affect soil microbial diversity.

Therefore, the effects of different mixing ratios of brackish water and reclaimed water on soil microbial diversity were investigated through pot experiments with Pakchoi as the test material in this study. The objectives of this study were as follows: (1) to analyze the alpha diversity and species of soil microbiota and determine the species number under different irrigation conditions; (2) to obtain species names at the Genus and Phylum levels based on the analysis of species composition under different irrigation conditions; and (3) to analyze the correlations between environmental factors and species evolution under different irrigation conditions; thereby providing a new method for the rational utilization of unconventional water resources.

2 Materials and methods

2.1 Test materials

The tested soil was taken from the 0–20 cm field surface in the Qiliying Test Base, Xinxiang City, Henan Province, and was air dried, ground, and passed through a 2 mm sieve. The bulk density of the soil was 1.40 g cm−3, the field capacity by mass was 23.02%, the conductivity of the 1:5 soil–water ratio of the soil extract was 372 μS cm−1, and the organic matter content was 2.66%. The experiment was conducted in the greenhouse of the Xinxiang Agricultural Soil and Water Environment Field Scientific Observation and Experiment Station of the Chinese Academy of Agricultural Sciences. The station is located at 35°27′ north latitude and 113°93′ east longitude, with an altitude of 73.2 m. The average annual temperature is 14.1°C, the average annual precipitation is 588 mm, the evaporation is 2,000 mm, and the frost-free period is 210 days. The average annual sunshine duration is 2,398 h. The size of the trial pot was 25 cm in upper diameter, 14.5 cm in lower diameter, and 19 cm in height. In addition, 7 kg of soil was added to each pot, and compound fertilizer was applied to all the treatments (N:P2O5:K2O in a ratio of 15:15:15) as the base fertilizer. The fertilizer amount was selected according to the local conventional fertilizer standard (1 g fertilizer per 1 kg soil). The tested crop was “Pakchoi” (commonly known as Shanghai Green), and all the plants were irrigated with fresh water before sowing. After seeding, five plants were kept in each pot at the two-leaf stage for irrigation with different water sources when the soil moisture was lower than 75% of the field capacity. The irrigation amount was 400 mL each time.

Four treatments were used in the experiment, namely, pure reclaimed water irrigation, pure brackish water irrigation, 1:1 mixed irrigation of brackish-reclaimed water, and 1:2 mixed irrigation of brackish-reclaimed water, which were recorded as T1, T2, T3, and T4, respectively. Fresh water irrigation was used as the control (CK), and the salinity in brackish water was 3 g L−1.

The reclaimed water used in the experiment was taken from the Luotuowan Domestic Sewage Treatment Plant in Xinxiang City, Henan Province, which adopted the A/O treatment process [21]. The water quality after sewage treatment met the “Water Quality Standard for Farmland Irrigation” (GB 5084-2021). Fresh water was tap water, and brackish water was prepared by adding sea salt to the tap water. The quality of the brackish water and reclaimed water is shown in Table 1.

Table 1

Water quality of reclaimed water, brackish water and tap water

Water sources EC (dS m−1) SAR (mmol L−1)0.5 Ion content (mg.L−1)
Na+ K+ Ca2+ Mg2+ Cl− HCO 3 ‒ SO 4 2 − CO 3 2 −
Tap water 0.321 0.34 10 1.6 39 15 30 120 104 —
Reclaimed water 0.212 5.82 310 13.9 91 74 314 278 507 —
Brackish water 0.610 43.3 1,330 2.1 43 17 1,921 142 92 —

Note: EC represents electrical conductivity; SAR represents the sodium adsorption ratio; “–” indicates not detected: the concentration was below the instrumental detection limit.

2.2 Analysis of soil properties

  1. Soil physical and chemical properties: The soil water content was measured via the drying method. The soil was mixed with distilled water at a 1:5 ratio to obtain the soil extract, and the electrical conductivity was determined with a conductivity meter. The SOM content was determined via low-temperature external thermal potassium dichromate oxidation colorimetry. The water drop penetration time (WDPT) of the soil was determined by the WDPT method.

  2. Soil enzyme activity: Soil enzyme activity detection kits (Solarbio, Beijing) were used to detect soil sucrase (S-SC) activity, soil alkaline phosphatase (S-AKP/ALP) activity, soil urease (S-UE) activity, and soil polyphenol oxidase (S-PPO) activity.

2.3 High-throughput sequencing of the 16S rDNA gene

The 16S rDNA V3–V4 region primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) were used to amplify the genomic DNA of each sample by PCR [22]. Using Trimmomatic (version 0.35) [23] software, for the raw data sequences, the sliding window method was first used to scan the sequences. When the mass was less than 20, the sliding window whose average base mass was lower than the threshold was removed, and the sequence whose length was less than 50 bp was removed. Flash (version 1.2.11) [24] software was used to splice the qualified double-ended raw data in the previous step, the maximum overlap in sequence splicing was 200 bp, and a complete paired-end sequence was obtained.

The qualified double-ended raw data from the previous step were spliced, and the maximum overlap was 200 bp to obtain a complete paired-end sequence. Split libraries (version 1.8.0) [25] software was used in QIIME to remove sequences containing N bases from paired-end sequences, sequences with single-base repeats greater than 8, and sequences whose length was less than 200 bp to obtain clean tag sequences. UCHIME (version 2.4.2) [26] software was used to remove the chimeras from the clean tags, and finally, valid tags for subsequent OTU partitioning were obtained. Finally, the quality control process statistics are analyzed, and the summary file is obtained.

3 Results

3.1 Dilution curves and alpha diversity analysis

By comparing the rarefaction curves of different samples, the difference in species abundance between samples can be visually displayed, and this difference can also be used to evaluate whether the sequencing amount of samples is reasonable. Species screening was performed on the OTU table, and the OTU clustering of the samples and corresponding species classification were determined. A total of 7,818 OTUs were detected, including 33 phyla, 95 classes, 212 orders, 374 families, and 808 genera. A random sampling of sequences was adopted. A rarefaction curve was constructed with the number of sequences drawn and their corresponding number or diversity of species (OTUs). As shown in Figure 1, each index of the sample increased with increasing sequencing data, and the curve subsequently tended to flatten, indicating that the current sequencing depth objectively reflects the composition of the soil microbes in each sample.

Figure 1 Rarefaction curves of bacterial communities under different treatments. (a) shannon index; (b) simpson index.
Figure 1

Rarefaction curves of bacterial communities under different treatments. (a) shannon index; (b) simpson index.

The indices of soil microbial alpha diversity under the different treatments are shown in Table 2. As shown in Table 2, the species coverage was close to 1, and the coverage in the 1:1 mixed irrigation treatment was significantly greater than that in the other treatments, indicating that the sequencing results can well reflect microbial diversity. Compared with those in the CK treatment, the Chao1 index, Shannon index, and Simpson index in the T1, T2, and T4 treatments increased significantly (p < 0.05), indicating that the species and diversity were greater under mixed irrigation conditions, which could increase community abundance. Compared with that in the pure brackish water irrigation (T2) treatment, the Chao1 index increased slightly, and the Simpson index decreased slightly in the 1:2 mixed irrigation (T4) treatment; however, these differences were not significant. The greatest number of species was detected under reclaimed water irrigation (T1), followed by T4, but the difference between the two was not significant, indicating that a moderate proportion of brackish water and reclaimed water mixed with irrigation could increase the diversity of the bacterial community.

Table 2

Alpha diversity indices of treated samples

Treatment PD_whole_tree Chao1 Goods_coverage Observed_species Shannon Simpson
CK 102.45 ± 2.36b 3,319.15 ± 94.82b 0.9925 ± 0.00036a 2,745.33 ± 102.97c 8.65 ± 0.18b 0.9882 ± 0.0035b
T1 116.42 ± 8.79a 3,820.80 ± 160.48a 0.9908 ± 0.00036b 31,98.6 ± 231.61a 8.87 ± 0.27ab 0.9905 ± 0.0038ab
T2 112.06 ± 4.48ab 3,795.09 ± 183.73a 0.9906 ± 0.00071b 3,098.53 ± 168.36ab 8.99 ± 0.07a 0.9934 ± 0.00033a
T3 103.99 ± 2.49b 3,396.34 ± 81.05b 0.9920 ± 0.00017a 2,823.73 ± 62.56bc 8.66 ± 0.07b 0.9911 ± 0.0005ab
T4 112.77 ± 6.06ab 3,819.82 ± 212.04a 0.9903 ± 0.00069b 3,145.43 ± 172.74ab 8.82 ± 0.16ab 0.9915 ± 0.002ab

Note: Different lowercase letters in the same column indicate significant differences between treatments at the 0.05 level.

3.2 Analysis of the species Venn diagram

The Venn diagram visually shows the number of OTUs common and unique to different processes. As shown in Figure 2, the species abundance was the highest under the T1 treatment, while the microbial abundance was the lowest under the T3 treatment. CK, T1, T2, T3, and T4 contained 4,394, 5,076, 4,725, 4,463, and 4,720 core bacterial genera, respectively. The percentage of unique OTUs under CK, T1, T2, T3, and T4 treatments was 459, 610, 456, 405, and 413, accounting for 10.45, 12.02, 9.65, 9.08, and 8.75% of the total bacterial genera, respectively. It indicated that there were certain differences in microbial community structure among the samples. There were approximately 2,493 common core OTUs, which accounted for 49.11–56.73% of the total OTUs, indicating that they had similar microbial compositions.

Figure 2 Venn diagram of OTUs associated with different processes.
Figure 2

Venn diagram of OTUs associated with different processes.

3.3 Analysis of community composition

The species distribution of the bacterial community structure in the samples from the different treatments at the phylum and genus levels is shown in Figure 4, which reveals that the composition of the bacterial community in each treatment was relatively similar.

As shown in Figure 3a, at the phylum level, the 15 Bacteroidetes with the most significant differences in relative abundance were Proteobacteria (39.98–61.62%), Actinobacteria (11.03–19.21%), Firmicutes (4.10–23.19%), Gemmatimonadetes (5.34–10.43%), Acidobacteria (1.27–2.8%), Nitrospirae (0.17–0.83%), Cyanobacteria (0.05–0.40%), Chloroflexi (0.08–0.19%), Epsilonbacteraeota (0.03–0.33%), Patescibacteria (0.02–0.12%), Verrucomicrobia (0.03–0.10%), Rokubacteria (0.02–0.13%), Latescibacteria (0.02–0.11%), and Tenericutes (0–0.40%). Proteobacteria accounted for the greatest proportion of bacteria in all the treatments. Compared with fresh water irrigation (CK), mixed irrigation with brackish water and reclaimed water increased the relative abundance of Proteobacteria, Gemmatimonadetes, and Latescibacteria and decreased the relative abundance of Firmicutes, Nitrospirae, Verrucomicrobia, and Rokubacteria. After treatment with a 1:2 mixture of brackish water and reclaimed water, the relative abundance of Actinobacteria and Chloroflexi was the greatest. Firmicutes, Nitrospirae, Epsilonbacteraeota, Patescibacteria, and Tenericutes had the lowest relative abundance. The relative abundance of Actinobacteria, Acidobacteria, Chloroflexi, and Rokubacteria was the lowest under the 1:1 mixed irrigation with brackish-reclaimed water treatment.

Figure 3 Variations in the relative abundance of major microbes. (a) Phylum and (b) genus.
Figure 3

Variations in the relative abundance of major microbes. (a) Phylum and (b) genus.

As shown in Figure 3b, at the genus level, the 15 most common microbial genera under the different treatments were Sphingomonas (3.51–8.86%), Lysobacter (2.18–8.6%), Algoriphagus (0.49–10.83%), Bacteroides (1.04–5.97%), Hydrogenophaga (0.24–5.84%), Faecalibacterium (0.8–7.77%), Bifidobacterium (0.7–6.47%), Arenimonas (0.52–3.98%), Massilia (0.5–2.96%), Pseudomonas (0.04–3.1%), Escherichia-Shigella (0.57–4.35%), MND1 (0.83–2.06%), Ellin6055 (0.51–1.71%), Nocardioides (0.36–1.83%), and Bacillus (0.36–2.59%), while Sphingosphingomonas accounted for the greatest proportion of all the treatments. Compared to fresh water irrigation, mixed irrigation with brackish water and reclaimed water improved the relative abundance of Sphingomonas, Lysobacter, Hydrogenophaga, Massilia, Pseudomonas, and Ellin6055. The relative abundance of Bacteroides, Faecalibacterium, Bifidobacterium, and Escherichia-Shigella decreased. The relative abundance of Arenimonas, Nocardioides, and Bacillus was the highest, while the relative abundance of Bacteroides, Faecalibacterium, Bifidobacterium, Escherichia-Shigella, and MND1 was the lowest under 1:2 mixed irrigation with brackish-reclaimed water. Under mixed irrigation with brackish water and reclaimed water at 1:1 ratio, the relative abundance of Hydrogenophaga and Ellin6055 was the highest.

3.4 Beta-diversity analysis

A PCoA is an analysis based on a variety of distance matrices through which the differences between individuals or groups can be observed. Each point in the figure represents a sample, and the same color represents the same group. The closer the samples are to the same group, the greater the distance between them and the other groups, and the greater the grouping effect [27]. PCoA based on unweighted UniFrac distance was used to evaluate the similarities and differences in microbial community composition among the different irrigation methods (Figure 4). The interpretations of the results by the PC1 and PC2 axes are 10.79 and 9.24%, respectively. The intergroup distance between the T3 and T4 treatments was relatively small, and there was some overlap, indicating that the species compositions of the two treatments were similar. That is, the species compositions of the two treatment groups were similar. The group spacing between the CK treatment and the other treatments was large, and there were significant differences in microbial community composition. Therefore, different irrigation water sources significantly affect the soil microbial community composition.

Figure 4 PCOAs in different processes.
Figure 4

PCOAs in different processes.

3.5 Correlation analysis of environmental factors

RDA revealed the correlation between bacterial communities and soil physicochemical properties at the genus level under different treatments. Figure 5 shows that there was an obvious correlation between the bacterial community structure and the environmental factors. Points of different colors or shapes in the figure represent sample groups of different treatments, and the strength of the influence of environmental factors on the microbial community structure is reflected by the arrow length [21]. Lysobacter and Hydrogenophaga were positively correlated with S-UE, while Faecalibacterium and Bifidobacterium were negatively correlated with S-UE. Sphingomonas and Massilia were positively correlated with S-SC and WDPT, while Algoriphagus and Nocardioides were negatively correlated with S-SC and WDPT. Sphingomonas and Pseudomonas were negatively correlated with S-AKP/ALP.

Figure 5 RDA for different processing and environmental factors.
Figure 5

RDA for different processing and environmental factors.

3.6 Evolutionary analysis

A heatmap can use color changes to reflect data information in a two-dimensional matrix or table. A heatmap can intuitively represent the size of the data values in defined color shades. Correlation heatmap analysis was performed by calculating the correlation between species or between environmental factors and species (Spearman coefficient, etc.). The obtained numerical matrices are visually displayed in the heatmap [28]. The abundance of each OTU was calculated, and the 50 OTUs with the most tags (the greatest abundance) were selected. An evolutionary tree was constructed, and the abundance of OTUs [29] in different samples is displayed with a heatmap.

As shown in Figure 6, Proteobacteria had the highest abundance in the microbial community, followed by Firmicutes and Gemmatimonadetes, which had the lowest abundance. The analysis revealed that the functions of Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, and Gemmatimonadetes, which are five types of bacteria, significantly differed from those of most other bacteria. The correlation between these parameters and the metabolic function of soil bacteria showed a potential coupling relationship.

Figure 6 Combinations of phylogenetic evolutionary trees and species abundance for different treatments.
Figure 6

Combinations of phylogenetic evolutionary trees and species abundance for different treatments.

4 Discussion

The salt in brackish water may cause the accumulation of soil salt, thus posing a stress hazard to the soil, preventing crop roots from absorbing water from the soil, and selectively killing or inhibiting some microbes, ultimately inhibiting the growth and activities of microbial communities [29]. Reclaimed water contains some organic matter and nutrients, such as nitrogen and phosphorus, which promote certain microbial communities. The mixed use of brackish water and reclaimed water increases the nutrient content of the soil, promotes the growth and activity of certain microbial communities, and can also effectively reduce the proportion of salt in the soil. There is a mutual relationship between the soil environment and the microbial community; changes in the soil environment affect microbial community structure, and microbes also react to soil via biological processes [30]. The relative abundance of soil microbes is an important index reflecting microbial activity and soil quality [31].

The results of this study showed that the dominant bacteria in the soil under the different treatments were mainly Proteobacteria, Actinobacteria, and Bacteroidetes at the phylum level, which is consistent with the findings of Han et al. [32]. In addition, it was found in the present study that under different treatments, the dominant bacteria in the soil mainly included Sphingomonas, Arenimonas, and Bacillus at the genus level, which is consistent with the findings of Sanka et al. [33]. Proteobacteria are the main group of salinized soil; Actinobacteria can mainly inhibit the activity of some pathogenic fungi and can promote the decomposition of plant residues, seed germination, and root development. Moreover, Bacteroidetes can promote the conversion and utilization of phosphorus through phosphorus dissolution and promote the uptake of nutrients in roots, playing a key role in the stability and function of soil ecosystems [31]. The three phyla, as the main phyla, all affect the ecological environment and community structure of soil microbes, effectively promoting the growth of crops and increasing yield.

At present, most studies have focused on the effects of mixed irrigation with reclaimed water and brackish water on soil physicochemical properties and crop growth physiological characteristics, but there has been no further exploration of soil microbial diversity. Irrigation with pure reclaimed water, irrigation with pure brackish water, and mixed irrigation with reclaimed water and brackish water had effects on the composition, relative abundance, and evenness of the microbial communities. The alpha diversity index can well reflect the abundance and diversity of microbial communities [34]. Han et al. [35] noted that reclaimed water irrigation can promote the metabolic reproduction of soil microbes and significantly increase the number and activity of soil microbes. Guo et al. [36] suggested that the nitrogen and organic matter contained in reclaimed water irrigation promoted an increase in the abundance of related microbes in soil, which was consistent with the conclusions of this study; that is, purely reclaimed water irrigation increased the diversity of the microbial community. However, Metcalfe et al. [37] reported that reclaimed water irrigation inhibited the propagation of soil Proteobacteria. This phenomenon may be caused by the difference between soil properties and reclaimed water quality and competition among the bacteria contained in the reclaimed water [36], thus reducing species diversity. Previous studies [38] have shown that, compared with those under pure reclaimed water drip irrigation, the Shannon index increased and the Simpson index decreased under brackish water irrigation, indicating that brackish water irrigation increased the species abundance, community diversity, and species composition uniformity of soil microbes. On the basis of the findings of Bouras et al. [39], the Shannon index of the microbial community increases with increasing irrigation water salinity. Guo [40] reported that the abundance of microbes increased with increasing irrigation water salinity. Chen et al. [41] reported that the abundance and diversity of soil microbes increased while the number of microbes categories decreased with increasing salinity in irrigation water. In this study, the results under brackish water irrigation were consistent with the above results, but mixed irrigation with brackish water and reclaimed water increased the diversity of the community structure compared with that under brackish water irrigation and decreased the diversity of the community structure compared with that under fresh water and reclaimed water irrigation; however, the difference was not significant. The PCoA revealed that the intergroup distance under the different mixed irrigation treatments was small, and there was a certain overlap. It means that their species compositions were similar, while the microbial community composition was significantly different as the group distance between CK and the other treatments was large.

Regulating soil environmental factors is an important way to increase microbial activity, promote crop growth, and increase yield [31]. Changes in the soil environment will change the nutrient supply pattern and further affect the survival of microbes. This study revealed that the S-UE, S-SC, and S-AKP/ALP were important factors affecting the composition and function of the soil microbial communities. Since the content of organic matter in soil significantly increases under fertilization conditions, organic matter is the main factor affecting microbial community structure [42], indicating that changes in soil properties are the leading factor influencing changes in microbial community structure. Although brackish water irrigation adds a large amount of salt ions to the soil, which greatly reduces soil permeability and weakens microbial activity [43], the addition of reclaimed water neutralizes salt ions [44], which reduces soil salinity and increases microbial activity.

The decrease in soil pH and an increase in salinity are two important factors affecting soil and crop growth under mixed irrigation. Sarfraz et al. [45] suggested that acidic soil affects the activity and ecological functions of soil microbes, as most microbes are sensitive to changes in soil pH. Greses et al. [46] proposed that pH reduction may lead to a decrease in certain beneficial microbes in the soil, which are crucial for crop growth and nutrient absorption. Fang et al. [47] argued that acidic soil may also lead to increased toxicity of certain important elements (such as aluminum, manganese, and iron) in the soil, thereby affecting root growth and nutrient absorption in crops. Golchoobi et al. [48] suggested that increased salinity affects the physical structure of soil and the availability of soil moisture. High salinity can enhance soil particle cohesion, reduce soil permeability, and increase soil susceptibility to cracking and clumping. Xu et al. [49] indicated that excessive salinity can inhibit crop growth and development because high-salinity environments make it difficult for crop roots to absorb water while increasing the plant’s demand for water. Khatei et al. [50] reported that the salt content affects the types and quantities of microbes in the soil. Some microbes exhibit strong salt tolerance, while others may be inhibited or die, impacting soil ecosystem stability and crop health. Therefore, close monitoring of soil pH and salinity is necessary during mixed irrigation, along with appropriate soil improvement measures such as lime application to adjust soil pH and proper saline drainage measures to ensure soil environment stability and healthy crop growth.

The impact of different irrigation water sources on soil microbial communities is complex and diverse and potentially influenced by multiple interacting factors. Hadi et al. [51] suggested that different irrigation water sources may have varying salinity and pH levels; high salinity and low pH water sources may adversely affect soil microbes, inhibiting the growth and reproduction of certain microbes, while low salinity and neutral to alkaline water sources may promote the reproduction of certain microbes in the soil. Sagar et al. [52] proposed that recycled water may contain nutrients such as nitrogen, phosphorus, and kalium, which can serve as nutritional sources necessary for the growth and metabolism of microbes, thereby promoting the reproduction of certain microbes. Sanka et al. [53] suggested that irrigation water sources with high water use efficiency may promote the reproduction of certain moisture-dependent microbes in the soil, while irrigation water sources with low water use efficiency may inhibit the growth of these microbes. Kanjana et al. [54] argued that different types and structures of soil may have different effects on the growth and reproduction of microbes; some irrigation water sources may be more compatible with specific types of soil, thereby promoting the growth and reproduction of certain microbes. The promotion or inhibition of microbial communities under different irrigation water resources may be the result of the combined effects of multiple factors. Therefore, when studying the response of microbial communities to different irrigation water resources, it is necessary to consider the comprehensive effects of these factors to more fully understand the interactions between microbial and irrigation water resources.

5 Conclusions

(1) Mixed irrigation with reclaimed water and brackish water had greater significant effects on soil microbial microbes than fresh water irrigation did. In mixed irrigation treatments, the relative abundance of soil microbes decreased gradually with increasing proportions of brackish water.

(2) Under mixed irrigation with brackish water and reclaimed water, the dominant bacteria in the soil mainly included Proteobacteria, Actinobacteria, and Chloroflexi at the phylum level. At the genus level, there were Arenimonas, Nocardioides, Bacillus, and Hydrogenophaga. The S-UE, S-SC, and S-AKP/ALP were important factors affecting the composition and function of soil microbial communities.

In addition, there are some limitations to this study. First, this study only conducted pot experiments focusing on a single crop and soil type; thus, further validation is needed for broader application in practical settings. Second, the study did not consider the effects of different water source mixing ratios on crop yield and quality. Future research could expand the sample range, consider more factors, and combine field experiments for validation to comprehensively assess the impact of mixed irrigation on soil ecosystems and agricultural production.

# Jieru Zhao, Juan Wang and Bingjian Cui contributed equally to this study.

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Acknowledgments

The authors thank the microbial diversity analysis results provided by Ouyi Biology; the project contract number is HT2020-13212, the sequencing type is bacterial 16SrDNA, and the region is V3V4 region.

  1. Funding information: This research was funded by “the Scientific and Technological Project of Henan Province (232102110014),” the “Central Public-interest Scientific Institution Basal Research Fund (IFI2023-25),” “the Natural Science Foundation of Henan Province of China (242300420061),” and “the Agricultural Science and Technology Innovation Program (ASTIP) of Chinese Academy of Agricultural Sciences.”

  2. Author contributions: J.Z.: writing (lead); conceptualization (equal); methodology (equal). J.W.: writing – review and editing (equal); conceptualization (equal); methodology (equal). B.C.: conceptualization (lead); supervision (equal); writing – review and editing (equal). B.Z.: data curation (equal); methodology (supporting); C.H.: data curation (equal); supervision (lead). Y.L.: data curation (equal); investigation (lead). Z.L.: conceptualization (lead); methodology (equal); funding acquisition (equal). C.L.: conceptualization (lead); project administration (supporting); supervision (equal); funding acquisition (equal). All authors have read and agreed to the published version of the manuscript.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Data availability Statement: The raw data supporting the conclusions of this article will be made available by the authors on request.

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Received: 2024-02-26
Revised: 2024-06-13
Accepted: 2024-06-19
Published Online: 2024-07-11

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  147. GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)
  148. Geospatial modeling of wildfire susceptibility on a national scale in Montenegro: A comparative evaluation of F-AHP and FR methodologies
  149. Geosite assessment as the first step for the development of canyoning activities in North Montenegro
  150. Urban geoheritage and degradation risk assessment of the Sokograd fortress (Sokobanja, Eastern Serbia)
  151. Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia
  152. Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities
  153. Forest soil CO2 emission in Quercus robur level II monitoring site
  154. Characterization of glomalin proteins in soil: A potential indicator of erosion intensity
  155. Power of Terroir: Case study of Grašac at the Fruška Gora wine region (North Serbia)
  156. Special Issue: Geospatial and Environmental Dynamics - Part I
  157. Qualitative insights into cultural heritage protection in Serbia: Addressing legal and institutional gaps for disaster risk resilience
https://doi.org/10.1515/geo-2022-0659
Keywords for this article
brackish water; reclaimed water; mixed irrigation; microbial diversity
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  147. GIS-based spatial modeling of landslide susceptibility using BWM-LSI: A case study – city of Smederevo (Serbia)
  148. Geospatial modeling of wildfire susceptibility on a national scale in Montenegro: A comparative evaluation of F-AHP and FR methodologies
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  150. Urban geoheritage and degradation risk assessment of the Sokograd fortress (Sokobanja, Eastern Serbia)
  151. Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia
  152. Understanding seismic hazard resilience in Montenegro: A qualitative analysis of community preparedness and response capabilities
  153. Forest soil CO2 emission in Quercus robur level II monitoring site
  154. Characterization of glomalin proteins in soil: A potential indicator of erosion intensity
  155. Power of Terroir: Case study of Grašac at the Fruška Gora wine region (North Serbia)
  156. Special Issue: Geospatial and Environmental Dynamics - Part I
  157. Qualitative insights into cultural heritage protection in Serbia: Addressing legal and institutional gaps for disaster risk resilience
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