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Article

Bioremediation of Saline-Alkali Soil Using a Waste Biomass-Functional Microorganism Composite Amendment and Preliminary Multi-Crop Field Validation

1
College of Biological and Pharmaceutical Engineering, Lanzhou Jiaotong University, Lanzhou 730000, China
2
Key Laboratory of Extreme Environmental Microbial Resources and Engineering of Gansu Province, Northwest Institute of Eco–Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
*
Author to whom correspondence should be addressed.
Microorganisms 2026, 14(2), 304; https://doi.org/10.3390/microorganisms14020304
Submission received: 17 December 2025 / Revised: 23 January 2026 / Accepted: 25 January 2026 / Published: 28 January 2026

Abstract

Soil salinization threatens crop production; however, in multi-crop field systems, evidence for the effectiveness of waste biomass-functional microorganism composite amendments remains limited. Here, we developed a composite microbial soil conditioner (F2) using pine needles and crushed corn cobs as carriers combined with salt-tolerant strains Bacillus subtilis (K1), Azotobacter chroococcum (Y1), and Bacillus gelatinus (J3) to remediate moderately saline-alkali soil from central Gansu (pH 8.36 ± 0.18; EC 1658 ± 55.24 μS·cm−1). Saturation screening identified an optimal carrier ratio of pine needles:corn cobs = 1:2 and an inoculum ratio of K1:Y1:J3 = 1:2:1. In pot experiments, F2 increased soil organic matter and water-holding capacity, enhanced alkaline phosphatase, urease, and sucrase activities, and significantly reduced soil pH and EC. Maize seedling height and chlorophyll content increased by 53.87% and 38.88%, respectively. Amplicon-based microbiome profiling indicated enrichment of beneficial microbial taxa and strengthened primary metabolic functions under F2. Field validation across five crops (flax, potato, edible sunflower, sorghum, and maize) showed consistent growth and yield-related improvements. Overall, these results demonstrate that the biomass–microbe composite amendment effectively alleviates saline-alkali constraints by jointly improving soil properties, microbial functions, and crop performance.

Graphical Abstract

1. Introduction

The quality of soil resources is a fundamental determinant of crop productivity and food security. With the continuous growth of the global population, agricultural systems are facing increasing pressure to sustain stable yields under constrained land and water resources [1]. However, unsustainable management practices, including excessive tillage, improper irrigation, intensive fertilizer application, and shallow ground-water rise—have accelerated the accumulation of soluble salts and exchangeable sodium in soils, resulting in widespread soil salinization and alkalization worldwide [2].
Recent global assessments indicate that salt-affected soils already occupy a substantial proportion of agricultural land. It is estimated that more than 20% of irrigated cropland is currently affected by salinity, and projections suggest that up to half of the world’s arable land may face salinization risks by the middle of this century if no effective interventions are implemented [3,4,5]. This degradation imposes severe constraints on crop establishment, nutrient uptake, and yield formation, leading to considerable economic losses in agricultural production [3,6]. In irrigated arid and semi-arid regions, secondary salinization is particularly prevalent, where excessive irrigation combined with strong evaporation promotes upward salt transport and surface accumulation, further intensifying soil degradation [2,4].
At the mechanistic level, saline–alkali stress disrupts soil structure and biogeochemical processes. Elevated Na+ concentrations displace Ca2+ and Mg2+ from soil colloids, inducing colloidal dispersion, reduced aggregate stability, and impaired water infiltration [7]. Meanwhile, carbonate and bicarbonate accumulation promote soil alkalization through hydrolysis reactions that release OH, leading to elevated soil pH and reduced nutrient availability [8]. These physicochemical constraints strongly inhibit seed germination, root development, and photosynthetic efficiency, ultimately reducing crop growth and productivity [5]. Such adverse effects have been widely reported across major crops, including maize, rice, and wheat, particularly in salt-affected irrigated systems [9,10].
In response to these challenges, the development of sustainable and environmentally compatible bioremediation strategies has attracted increasing attention. Among them, plant growth promoting rhizobacteria (PGPR), halotolerant microbial inoculants, and organic soil amendments have been extensively explored due to their potential to alleviate salt stress while maintaining ecological integrity [10,11,12]. Functional microorganisms can mitigate salinity stress through multiple pathways, including the production of extracellular polysaccharides, synthesis of osmoprotectants, secretion of phytohormones such as indole-3-acetic acid, and regulation of rhizosphere nutrient cycling [10,11]. Concurrently, organic materials derived from agricultural wastes provide valuable carbon sources, improve soil structure, and create favorable microhabitats for microbial colonization and activity [13,14,15,16,17].
Despite these advances, existing studies remain limited in two key aspects. First, most research has focused on the direct application of microbial inoculants or organic amendments individually, whereas systematic investigations into specific agricultural wastes functioning as microbial carriers and their synergistic enhancement effects are still scarce [4,16]. Second, the majority of available evidence is derived from short-term laboratory or pot experiments, with limited validation under multi-crop field conditions, where complex soil–plant–microbe interactions determine the long-term stability and effectiveness of remediation strategies [2,3].
Based on the identified research gaps, this study proposes the use of pine needles and crushed corn cobs as composite carriers for functional microorganisms to develop a biomass–microorganism amendment suitable for moderately saline–alkali soils. Rather than focusing solely on improvements in soil physicochemical properties, this study evaluates the overall effectiveness of the amendment through pot experiments and multi-crop field trials, and explores how interactions among the carrier, microorganisms, and plants under saline–alkali conditions influence soil remediation outcomes and crop growth performance.
Accordingly, we tested the following hypotheses: (i) pine needles and crushed corn cobs can optimize the rhizosphere microenvironment, thereby enhancing microbial colonization and metabolic activity; (ii) the biomass–microbe composite system can synergistically alleviate saline–alkali stress by improving soil structure, nutrient cycling, and rhizosphere microbial community composition; and (iii) the soil remediation and crop-promoting effects of this composite amendment exhibit stability and universality across different crop species. To test these hypotheses, systematic pot experiments and multi-crop field trials were conducted to evaluate changes in soil physicochemical properties, microbial community structure, and crop growth performance, providing a technically feasible and ecologically sustainable solution for saline–alkali land restoration.

2. Materials and Methods

2.1. Experimental Design

Based on literature reports and strain characteristics, this study preliminarily screened nine functional microorganisms [Bacillus subtilis (K1), Lactobacillus plantarum (Z1), Azotobacter chroococcum (Y1), Bacillus lateralis (E1), Bacillus giganteum (J1), Bacillus amylolyticus (J2), Bacillus gelatinus (J3), Saccharomyces (J4), and Rhizopus viridis (L1)] as candidate strains. Their symbiotic properties, growth-promoting capabilities, and salt-alkali tolerance were evaluated to identify superior strains. Simultaneously, to alleviate mild soil compaction in Lanzhou New Area’s cultivated soils and ensure microbial agent stability, two waste biomass sources: pine needles (particle size: 0.80–1.00 mm) and crushed corn cobs (particle size: 0.38–0.40 mm)—were selected as organic substrates for the amendment. This aims to enrich nutrient sources for soil microorganisms and enhance soil aeration. Recognizing that the microbial-to-organic-substrate ratio is critical for soil improvement efficacy, 19 soil saturation experiments were designed for screening and optimization. To validate the selected formulation’s ameliorative effect on saline-alkali soils, pot experiments were conducted using maize as an indicator plant. Finally, field verification trials were conducted using five locally cultivated cash crops: flax, potato, edible sunflower, sorghum, and maize. Experimental groups included an amended treatment group (EG) and an untreated control group (CG). The experimental design is illustrated in Figure S1.

2.2. Saturation Experiment and Potted Plant Experiment Design

Soil samples for this experiment were collected from the Zhongchuan Town experimental area within the Zhongchuan Industrial Park of Lanzhou New Area, Gansu Province. The basic characteristics of the soil samples are presented in Table S2. The soil saturation experiment lasted 60 days with three replicates per group. Soil physicochemical properties were measured every 10 days. Soil samples were air-dried, sieved (2 mm), and placed in bottom-perforated pots (pot diameter 14 cm, height 12 cm). Add microorganisms and waste biomass at application rates of 2 g·kg−1 soil and 6 g·kg−1 soil, respectively, and mix them into the 0–5 cm topsoil layer (microorganisms in wet fungal state) [18,19,20,21]. Detailed group configurations are provided in Table S1. The pot experiment lasted 60 days with three replicates per group. Soil physicochemical properties and plant growth physiological indicators were measured every 10 days. Soil samples were air-dried, sieved (2 mm), and placed into bottom-perforated pots (upper diameter 50 × 18.8 cm, lower diameter 40 × 11.5 cm, height 15 cm). Microorganism and waste biomass application rates were consistent with the saturation experiment. Group configurations are detailed in Table 1. Om refers to bio-organic fertilizer purchased from Zhonglin Gaoke Biotechnology Co., Ltd. (Zhoukou, China), and Em denotes microbial preparations sourced from Jining Xiannong Biotechnology Co., Ltd. (Jining, China), both applied according to manufacturer instructions. The maize variety used was Kenyu 147 (Ningxia Jinsanyuan Agricultural Science and Technology Co., Ltd., Yinchuan, China). Before sowing, seeds were disinfected with a 5% iodophenol solution for 15 min, then rinsed with deionized water. The disinfected seeds were soaked in a microbial suspension (106 CFU·mL−1) for 8 h before planting. Pots were placed in a constant-temperature incubator (12/12 h light/dark cycle, 25 °C), with uniform irrigation conditions maintained throughout.

2.3. Soil and Plant Sampling

Pot experiment: Rhizosphere soil was collected 48 h after irrigation by gently shaking the roots and brushing off the soil tightly adhering to the root surface. Coarse debris and visible root residues were removed, and subsamples were allocated for physicochemical analyses. At the end of the pot experiment, rhizosphere-attached soil was additionally collected for microbial community sequencing.
Field experiment: In each plot, five 1 m2 subplots were established (one at the center and four at the corners). Composite soil samples were obtained from the 0–20 cm layer using a five-point sampling approach. Soil samples were air-dried, sieved (2 mm), and used for subsequent physicochemical measurements. To standardize moisture conditions prior to indicator determination, sieved soil was rewetted to saturation until free drainage occurred and then equilibrated for 48 h before analysis.
Plant sampling: For the pot experiment, three maize plants per treatment were randomly selected. Plant height, root length, and stem diameter were measured after uprooting and gently washing the roots. Functional leaves were collected simultaneously for chlorophyll, malondialdehyde, and soluble sugar analyses. For the field experiment, three representative plants showing normal growth were collected at each sampling point using the five-point method. Whole plants were excavated, adhering soil was removed, and samples were photographed for record. Functional leaves were stored at low temperature and analyzed within 24 h.

2.4. Research Methods

2.4.1. Single-Colony Purification and Inoculum Preparation

All bacterial strains used in this study were purified by repeated streaking on LB agar plates. Each strain was streaked at least three consecutive times to obtain morphologically uniform and well-isolated single colonies. A single colony was then picked and inoculated into LB liquid medium, followed by incubation at 37 °C with shaking at 120 rpm for 10 h. The resulting cultures were adjusted to a final optical density of OD600 = 1.4 and used as standardized inocula for subsequent functional assays.

2.4.2. Qualitative Screening of Phosphorus Solubilization, Nitrogen Fixation, and Potassium Solubilization

The abilities of bacterial strains to solubilize organic and inorganic phosphorus were qualitatively evaluated on Mongina organic phosphorus agar and PKO inorganic phosphorus agar, respectively [22]. Standardized inocula were point-inoculated onto the agar surfaces and incubated at 37 °C for 3–7 days. Phosphorus solubilization was determined based on the formation of clear halo zones surrounding the colonies.
Nitrogen fixation potential was assessed on Ashby nitrogen-free medium, where visible colony growth after incubation indicated nitrogen-fixing ability [23]. Potassium solubilization capacity was evaluated using potassium-solubilizing agar medium following the same incubation conditions. All qualitative assays were conducted in triplicate (n = 3) for each strain, with uninoculated plates serving as negative controls.

2.4.3. Determination of Indole-3-Acetic Acid (IAA) Production

Qualitative detection of IAA production was performed using the Salkowski colorimetric method [24]. Briefly, bacterial cultures were centrifuged, and the supernatant was mixed with Salkowski reagent and incubated in the dark. Absorbance was measured at 530 nm using a spectrophotometer (Qingdao Juchuangshiji Environmental Protection Co., Ltd., Qingdao, China).
Quantitative analysis of IAA was conducted using high-performance liquid chromatography (HPLC) [25]. Separation was achieved on a C18 reversed-phase column, with a methanol–water mobile phase. IAA was detected at a wavelength of 280 nm, and quantification was performed using an external standard calibration curve. All measurements were performed in triplicate (n = 3).

2.4.4. Soil Physicochemical Properties and Enzyme Activities

Soil pH and electrical conductivity (EC) were measured in soil–water suspensions at ratios of 1:2.5 (pH) and 1:5 (EC), respectively, after shaking for 15 min. Measurements were conducted using a calibrated pH meter (PHS-3C, INESA Scientific Instrument Co., Ltd., Shanghai, China) and conductivity meter (DDS-11A, Leici, Shanghai, China).
Soil organic carbon (SOC) was determined using the potassium dichromate colorimetric method [26], and SOC was converted to soil organic matter (SOM) using the Van Bemmelen factor (SOM = SOC × 1.724). Soil bulk density (ρb) was measured using the ring knife (core) method [27]. Total porosity was calculated as Porosity (%) = (1 − ρb/ρs) × 100, where particle density (ρs) was assumed to be 2.65 g·cm−3 for mineral soils. Soil field water capacity (field water capacity) was determined following saturation and free drainage for 48 h, and the retained water content was quantified by the oven-drying method [28].
Activities of alkaline phosphatase, urease, sucrase, and catalase were determined using the sodium phosphate colorimetric method, sodium phenolate–sodium hypochlorite colorimetric method, 3,5-dinitrosalicylic acid colorimetric method, and potassium permanganate titration method, respectively [29,30]. Enzymatic reactions were completed and measured within 30 min after reagent addition under ambient temperature conditions. All soil analyses were conducted with three biological replicates (n = 3).

2.4.5. Soil Nutrient Determination and Plant Physiological Measurements

Soil samples were air-dried and sieved through a 2 mm mesh prior to analysis. Total nitrogen (TN) was determined using the Kjeldahl digestion method, while total phosphorus (TP) and total potassium (TK) were measured following acid digestion procedures. For inorganic and available nutrient fractions, nitrate nitrogen (NO3-N) was extracted with deionized water, available phosphorus (A-P) was extracted using sodium bicarbonate solution (Olsen method), and available potassium (A-K) was extracted using ammonium acetate solution. All digests and extracts were quantified using a nutrient analyzer (FP-LIBS, Felles Photonic, Shanghai, China) based on external standard calibration, with blanks and standards used for quality control. All measurements were conducted with three biological replicates (n = 3).
Plant chlorophyll content was determined by extracting finely ground leaf tissue with 95% ethanol, and absorbance was measured at 665 nm and 649 nm using a spectrophotometer [31]. Malondialdehyde (MDA) content was determined using the thiobarbituric acid method [32]. Soluble sugar content was quantified using the anthrone colorimetric method: leaf samples were finely cut and ground, extracted in boiling water, reacted with anthrone reagent, heated in a boiling water bath for 10 min, and absorbance was measured at 620 nm [33]. All plant physiological measurements were conducted with three independent replicates (n = 3).

2.5. High-Throughput Sequencing of Rhizosphere Soil

Microbial community analysis was performed using Illumina MiSeq (Illumina, Inc., San Diego, CA, USA) high-throughput sequencing targeting bacterial 16S rRNA and fungal ITS rRNA genes [34]. The 16S rRNA using primers 341F-CCTAYGGGRBGCASCAG and 806R-GGACTACNNGGGTWTCTAAT, ITS1F-CTTGGTCATTTAGAGGAAGTAA, and ITS2R-GCTGCGTTCTTCATCGATGC. The OTU table was generated using the Usearch software (v10), with an OTU identity of 97%. Taxonomic analysis was performed using the Uclust Algorithm software (v1.2.22q) with a confidence threshold of 0.8. Bacterial and fungal taxonomic annotation was conducted using the Silva and Unite databases, respectively, and bacterial functional prediction was performed using the Tax4Fun software (v1.1.5). The data source was supported by the cloud platform of Ling’en Biotechnology Co., Ltd. (Shanghai, China) (http://www.cloud.biomicroclass.com/CloudPlatform, accessed on 17 February 2025).

2.6. Field Experiment Locations and Methods

Field The field experiment for this study was conducted in Zhongchuan Town, Zhongchuan Industrial Park, Lanzhou New Area, Gansu Province (36°32′ N, 103°36′ E). This region exhibits a typical temperate continental semi-arid climate, with an annual average temperature of 10.3 ± 1.8 °C, average annual precipitation of 327 ± 24.8 mm, and annual evaporation exceeding 1500 mm. The area’s soil is moderately saline-alkali, making it a key region for saline-alkali land remediation and high-efficiency agricultural development in central Gansu Province.

2.6.1. Field Experiment Design

The experiment employed a randomized block design with a control group (CG) and an experimental group (EG). Ten plots were established, each measuring 660 m2 (22 m × 30 m). Crops were arranged in rectangular grid patterns with repeated blocks at varying plant spacings within each plot. The crop seed varieties used were: Longya 15 flax, Longshu 10 potato, Hefeng 593 edible sunflower, grain sorghum, and Kenyu 147 maize (Ningxia Jinsanyuan Agricultural Science and Technology Co., Ltd., Yinchuan, China). The seeding rate and spacing for each crop are as follows: flax (5 kg per plot, row spacing 15 cm), potato (100 kg per plot, two rows per ridge, inner row spacing 15 cm, plant spacing 20 cm, ridge spacing 40 cm), edible sunflower (1 kg of seeds per plot, two rows per ridge, 25 cm between inner rows, 30 cm between plants, 50 cm between ridges), sorghum (1.5 kg per plot, two rows per ridge, 20 cm between inner rows, 25 cm between plants, 40 cm between ridges), maize (2 kg per plot, two rows per ridge, inner row spacing 20 cm, plant spacing 25 cm, ridge spacing 40 cm). Except for the control group, which did not receive any microbial agents or waste biomass, all experimental plots were managed using uniform agronomic practices, including irrigation and weed control, in accordance with local agricultural planting standards.

2.6.2. Field Management Measures

Basal fertilizer: The control group and experimental group received 150 kg/plot and 120 kg/plot of organic fertilizer, respectively. The primary components of the organic fertilizer were livestock manure and straw compost.
Microbial amendments: One week after basal fertilizer application, the topsoil layer (0–15 cm) was tilled. The experimental group received 6 kg/plot of microbial inoculant (effective viable bacteria count ≥ 2.5 × 109 CFU·mL−1) mixed with 30 kg/plot of pine needles and crushed corn cobs mixture.
Seed treatment: Before sowing, crop seeds were treated with microbial inoculant (effective viable bacteria count ≥ 2.5 × 109 CFU·mL−1). The inoculant solution (20 mL/2.5 kg seeds) was diluted 10-fold and uniformly sprayed onto seeds. Seeds were air-dried in shade before sowing.
Top-dressing: Microbial inoculant top dressing was administered via drip irrigation on a monthly schedule during the field experiment. Flax received two applications due to its shorter growing period, whereas potato, sorghum, edible sunflower, and maize each received four applications.

2.7. Statistical Analysis

One-way analysis of variance (ANOVA) and Duncan’s multiple range test were performed using IBM SPSS Statistics 26 software to evaluate significant differences between treatment groups, with a significance level of 0.05. The experimental data for the characteristics of functional microorganisms, soil physicochemical properties, and plant physiological indicators were visualized using Origin 2024. The community composition analysis of rhizosphere microorganisms was conducted using the cloud platform of Ling’en Biotechnology Co., Ltd. (Shanghai, China) and Origin 2024. The correlations between microorganisms, soil, and soil were analyzed using redundant analysis (RDA) with Canoco 5.0.

3. Results

3.1. Screening and Characterization of Functional Microorganisms

Based on the physicochemical characteristics of the experimental soil, its taxonomic position was clarified following the World Reference Base for Soil Resources (WRB 2022). The newly reclaimed soil from the Zhongchuan Industrial Park of Lanzhou New Area exhibited an alkaline reaction (pH 8.36 ± 0.18) and elevated electrical conductivity (1658.33 ± 55.24 μS·cm−1; 1:5 soil–water suspension), indicating clear salinity–alkalinity constraints. According to agronomic classification commonly applied in arid regions, soils with alkaline pH and intermediate salinity levels are described as moderately saline–alkali soils, which is consistent with the background condition of the experimental site. Soil texture analysis classified the soil as loam, indicating a mineral soil prone to salt accumulation under arid conditions (Table S1).
The soil organic matter content was 14.38 ± 1.46 mg·g−1, and bulk density was relatively high (1.94 ± 0.08 g·cm−3), resulting in low total porosity (24.42 ± 1.08%). Exchangeable Na+ (5.25 cmol·kg−1) was markedly higher than Ca2+ (2.24 cmol·kg−1) and Mg2+ (1.83 cmol·kg−1), with a cation exchange capacity (CEC) of 14.15 cmol·kg−1. The calculated SAR was 5.08, and ESP reached 37.10%, far exceeding the WRB diagnostic threshold for sodicity (Table S1).
Overall, the elevated EC, high ESP, and unfavorable physical indicators demonstrate that, while the soil represents a moderately saline–alkali background in agronomic terms, it should be classified as a saline soil affected by sodicity constraints under the WRB 2022 framework.
L1 was excluded due to antagonistic interactions with K1, J1, and Z1 (Figure 1a). J1, J2, and J3 possessed potassium-solubilizing capabilities, with J3 exhibiting the strongest activity (Figure 1b); Y1 demonstrated nitrogen-fixing capacity (Figure 1c); J1 and J3 could solubilize both organic and inorganic phosphorus, with J3 showing superior solubilization ability (Figure 1d). K1, J3, Y1, Z1, and E1 produced indole-3-acetic acid-like compounds, with K1 exhibiting the highest yield (20.48 ± 0.64 μg·kg−1, Figure 1e). Additionally, E1, K1, Y1, Z1, and J3 exhibited good tolerance to NaCl concentrations (2–10% mass fraction) and alkaline conditions (pH 8.0–10.0) (Figure 1f,g).
After a comprehensive analysis, K1, Y1, and J3 were selected to formulate a saline-alkali soil conditioner. The growth curves of the three strains were similar, facilitating co-culture (Figure 1h). K1 and Y1 exhibited a partially beneficial symbiosis (Figure 1i), Y1 and J3 showed a neutral relationship (Figure 1j), while K1 and J3 formed a mutualistic symbiosis (Figure 1k), indicating stable coexistence under the same environmental conditions.

3.2. Saturated Experimental Soil Physicochemical Properties

Compared with the CK group, soil pH significantly decreased in all experimental treatments (p < 0.05), with the greatest reduction observed in the F2 group. At 60 days, soil pH in the F2 treatment decreased to 7.64 ± 0.15, corresponding to an 8.28% reduction relative to CK (Figure 2a). Soil electrical conductivity (EC) also declined significantly across all treatments (p < 0.05), with the most pronounced decreases recorded in the F2 and F6 groups (50.19% and 49.28%, respectively; Figure 2b). Notably, soil in the F2 group shifted toward a slightly saline–alkali classification.
Soil organic matter content increased significantly in all experimental groups (p < 0.05), reaching 42.60 ± 2.12 mg·g−1 in the F2 group at 60 days (Figure 2c). Soil porosity in the F1 and F2 groups increased significantly by 39.26% and 29.34%, respectively, compared with other treatments (p < 0.05; Figure 2d). Among all treatments, the F2 group exhibited the largest enhancement in soil water capacity, with an increase of 63.34% relative to CK at 60 days (Figure 2e).
Soil enzyme activities were significantly affected by all treatments (p < 0.05). The F2 group showed the greatest increases in alkaline phosphatase and sucrase activities (Figure 2f,h), while catalase activity decreased most markedly in this group (Figure 2i). Urease activity reached its highest value in the F3 group (Figure 2g); however, no significant difference was observed between the F3 and F2 treatments (p > 0.05).
To provide an integrated evaluation of soil improvement performance, a Composite Soil Improvement Index (CSII) was calculated based on normalized changes in soil pH, EC, organic matter, water-holding capacity, and composite enzyme activity. The CSII values ranked the treatments as F2 (1.000) > F3 (0.929) > F6 (0.884) > F1 (0.860). Accordingly, the CSII of the F2 treatment exceeded those of F1, F3, and F6 by 16.28%, 7.63%, and 13.11%, respectively (Table S2). This integrated assessment quantitatively confirms that the microorganism–waste biomass mixed ratio used in the F2 treatment provided the most balanced and robust overall improvement in soil physicochemical properties and biochemical functions among the tested formulations.

3.3. Physicochemical Properties of Potted Experimental Soil and Physiological Indicators of Plant Growth

Results showed that within 60 days, soil porosity, water-holding capacity, organic matter content, and alkaline phosphatase, urease, and sucrase activities in all treatment groups were significantly higher than in the CK (p < 0.05, Figure 3a–d). The CFP group exhibited the most pronounced improvement, with its porosity, water-holding capacity, and organic matter content reaching 0.28, 0.69, and 1.85 times those of the CK at 60 days. Simultaneously, soil electrical conductivity, pH, and bulk density significantly decreased in the CFP, CMP, CEM, and COM groups (p < 0.05). Catalase activity showed an initial increase followed by a decrease, while the CSP and CP groups exhibited smaller changes in these indicators. The CFP group showed the greatest reduction, with decreases of 86.36%, 12.85%, and 34.86% compared to the CK at 60 days (Figure 3b,e). All treatments promoted the accumulation of TN, TP, TK, NO3-N, A-P, and A-K, with CFP showing the highest increase (Figure 3f, Table S3).
Significant differences (p < 0.05) were observed among treatments for plant height, root length, stem diameter, chlorophyll content, malondialdehyde levels, and soluble sugar content. In the CFP group, plant height, root length, stem diameter, and chlorophyll content significantly increased with restoration time, showing an overall pattern of CFP > CMP > CEM > COM > CSP > CP (Figure 4a–d). Malondialdehyde and soluble sugar levels exhibited a decreasing trend, with values at 60 days showing CFP < CMP < CEM < COM < CSP < CP (Figure 4e,f).
In summary, the F2 amendment effectively reduced soil salinity and alkalinity, improved soil physicochemical properties and soil physical structure-related indicators (e.g., bulk density/porosity and soil water capacity), and significantly promoted plant growth and physiological performance.

3.4. Prediction of Rhizosphere Bacterial Community Composition and Function (Pot Experiment)

16S rRNA sequencing results indicated that the Chao1 and Shannon indices in the CFP group were significantly higher than those in other groups (p < 0.05) (Table S4). At the phylum level, Pseudomonadota (31.51 ± 1.94%) and Bacteroidota (12.84 ± 2.33%) dominated across all treatment groups, indicating their strong adaptability to saline-alkali soils. Compared to CK, Actinomycetota abundance significantly increased in the CFP group (24.85%), indicating that the F2 amendment promotes enrichment of this functional group. Chloroflexota and Bacillota increased in the COM and CEM groups, but to a lesser extent than in the CMP group, suggesting that microorganisms in F2 exhibit greater advantages in optimizing soil environments and promoting beneficial microbial growth (Figure 5a,b).
At the genus level, Pontibacter, Endomicrobium, and Zeaxanthinibacter were significantly enriched in the CFP group (p < 0.05); while potentially beneficial groups like Nitrolancea and Luteitalea also showed significant increases (p < 0.05). The microbial compositions of CSP and CEM groups were relatively similar, but Curvibacter was higher in CSP than in CEM and also higher in CMP than in COM (Figure 5c,d).
Core OTUs analysis revealed the following group-specific OTUs counts: CK (57), CP (64), CSP (71), CEM (79), COM (83), CMP (206), and CFP (304). All groups shared 27 species, with the CFP group harboring the highest species richness (90 species) and the greatest number of unique species (11 species) (Figure 5e).
Functional prediction based on the SILVA database indicated that bacterial communities primarily engaged in metabolism, cellular processes, genetic information processing, environmental information processing, and organismal systems (Figure 5f). Among these, CEM, COM, CMP, and CFP exhibited similar functional distributions, all dominated by metabolism—including energy metabolism, carbohydrate metabolism, amino acid metabolism, cofactor and vitamin metabolism, polysaccharide metabolism, and heterotrophic degradation—while also involving signal transduction, cell motility, membrane transport, replication and repair, and environmental adaptation (Figure 5f). The CFP group showed significantly higher representation than other groups (p < 0.05) in all major metabolic pathways except amino acid metabolism. Regarding cellular processes, CFP exhibited the highest abundance in membrane transport and cell growth and death functions. In genetic information processing, it also demonstrated the highest abundance in replication and repair, folding, classification, and degradation (Figure 5f).

3.5. Rhizosphere Fungal Community Composition (Pot Experiment)

ITS sequencing results revealed that the fungal communities in the CFP group exhibited significantly higher Chao1 and Shannon indices compared to other groups (p < 0.05) (Table S4). At the phylum level, Ascomycota dominated across all experimental groups (average proportion: 77.06 ± 6.25%), with the highest relative abundance observed in the CMP group (86.38%). Concurrently, Basidiomycota exhibited higher abundance in the CFP and CMP groups, while microbial abundance differences were minor in the COM and CEM groups (p > 0.05). Overall microbial abundance was superior to that in the CSP, CP, and CK groups (Figure 6a,b).
At the genus level, Podospora and Rhizophagus were significantly enriched in the CFP group, while potential pathogens such as Fusarium and Alternaria were significantly reduced. Additionally, functional fungi like Botryotrichum and Preussia exhibited higher abundances in the CFP group. In contrast, CK, CP, and CSP groups exhibited lower fungal diversity and higher proportions of pathogens. COM and CEM groups showed increases in certain fungal genera, but dominant genera fluctuated considerably. The CMP group had lower dominant genus abundances than the CFP group and performed less favorably, indicating that synergistic interactions between microorganisms and waste substrates hold greater potential for optimizing fungal community structure (Figure 6c,d).
Core OTUs analysis revealed the following fungal core OTUs counts across groups: CK (19), CP (21), CSP (25), CEM (48), COM (51), CMP (71), and CFP (90). The CFP group harbored 180 fungal species, including 51 unique species, significantly higher than other treatments (p < 0.05) (Figure 6e).

3.6. Correlation Analysis

Spearman correlation analysis was performed to quantify the relationships among rhizosphere microbial communities (top 10 bacterial and fungal genera by relative abundance), soil physicochemical properties, enzyme activities, and plant physiological parameters (Figure 7).
For bacterial communities, soil pH and EC showed consistent negative correlations with the relative abundance of most dominant genera. In contrast, nutrient-related variables exhibited strong positive associations. For example, Nitrolancea was positively correlated with NO3-N (r = 0.958, p < 0.001), A-P (r = 0.941, p < 0.001), and A-K; (r = 0.926, p < 0.001). Zeaxanthinibacter and Endomicrobium also showed strong positive correlations with OM (r = 0.932 and 0.918, respectively; both p < 0.001) and S-ALP (r = 0.964 and 0.905, respectively; both p < 0.001). In contrast, pH and EC were negatively correlated with these genera (|r| = 0.71–0.89, p < 0.05).
Associations between bacterial communities and plant physiological parameters revealed that stress-related indicators, including WSS and MDA, were negatively correlated with Nitrolancea, Pontibacter, and Zeaxanthinibacter (e.g., MDA and Zeaxanthinibacter: r = −0.934, p < 0.001). Conversely, growth-related parameters such as He, RL, SD, and CHL were positively correlated with Lutetiella, Ohtaekwangia, Acidobacterium, and Curvibacter (r = 0.88–0.97, p < 0.01).
For fungal communities, soil pH and EC were negatively correlated with the abundance of beneficial fungi. Podospora and Rhizophagus exhibited strong positive correlations with NO3-N (r = 0.974 and 0.948, respectively; p < 0.001), A-P (r = 0.957 and 0.936; p < 0.001), and OM (r = 0.962 and 0.944; p < 0.001). In contrast, potential pathogenic genera such as Fusarium and Alternaria were positively correlated with pH and EC (r = 0.81–0.93, p < 0.01) and negatively correlated with enzyme activities and CHL.
Correlation analysis between soil properties and plant parameters further showed that WSS and MDA were positively correlated with pH and EC (r = 0.79–0.91, p < 0.05), whereas He, RL, SD, and CHL exhibited strong positive correlations with nutrient availability (NO3-N, A-P, A-K, OM) and enzyme activities (S-ALP, S-Urea, S-SC) (r = 0.90–0.98, p < 0.001).

3.7. Plant Growth Physiology and Soil Physicochemical Properties (Field Experiment)

Results indicate that the F2 soil conditioner significantly improved the physicochemical properties of field soils (Figure S2). Compared to the control field, both soil pH and electrical conductivity decreased extremely significantly (p < 0.0001) in the experimental fields. Among them, the edible sunflower experimental field showed the largest pH decrease (5.86%), reaching 7.69 ± 0.05, with a Cohen’s d value of 11.02 between the two groups; while the sorghum experimental field exhibited the highest decrease in electrical conductivity (40.35%), reaching 662.76 ± 32.63 μs·cm−1, with a Cohen’s d value of 13.59. Total soil porosity increased extremely significantly (p < 0.001) in all experimental fields, with the edible sunflower experimental field showing the largest increase (28.67%). Organic matter content also increased significantly (p < 0.0001), with the most pronounced increase in the potato experimental field (80.60%), reaching 48.64 ± 2.71 mg·g−1, with a Cohen’s d value of 6.52. Concurrently, F2 significantly enhanced alkaline phosphatase, urease, and sucrase activities (p < 0.0001). with increases of 48.11% and 38.52% in the flax experimental field, reaching 6.66 ± 0.35 mg·g−1 (Cohen’s d = 6.73) and 4.87 ± 0.25 mg·g−1 (Cohen’s d = 5.64), respectively; Sucrase activity showed the most significant increase in the sunflower experimental field (73.77%), reaching 21.85 ± 1.11 mg·g−1 with a Cohen’s d value of 7.55. In contrast, catalase activity decreased significantly across all experimental fields (p < 0.0001), with the largest reduction (39.53%) observed in the edible sunflower experimental field, reaching 2.15 ± 0.15 mL·g−1 with a Cohen’s d value of 8.29.
Plant growth indicators also showed significant improvement (Figure 8 and Figure S3). Plant height, root length, and stem diameter in all five experimental plots exceeded those of the control (p < 0.01). Flax exhibited the greatest increases in plant height and root length (13.96%, 21.56%), reaching 85.48 ± 5.26 cm and Cohen’s d value 2.12, and 13.59 ± 1.28 cm, Cohen’s d value 1.73, respectively. Potato exhibited the highest increase in stem thickness (37.12%), reaching 15.28 ± 1.51 mm, with a Cohen’s d value of 3.02. Above-ground and below-ground fresh weights of crops in all experimental fields significantly increased (p < 0.05), with potatoes showing the most pronounced increase. Chlorophyll content extremely significantly increased in all experimental fields (p < 0.0001), peaking in potatoes at 5.14 ± 0.29 mg·g−1 (Cohen’s d = 3.23). Concurrently, malondialdehyde and soluble sugar contents both decreased significantly (p < 0.001), with the greatest reductions observed in flax: 10.05 ± 0.91 μmol·g−1 (Cohen’s d = 4.85) and 9.01 ± 0.72 mmol·g−1 (Cohen’s d = 3.89), respectively.
To facilitate agronomic interpretation and cross-study comparison, crop yield data were standardized to area-based metrics (Table S5). Across all five field trials, the F2 treatment resulted in consistent yield enhancement relative to the corresponding control plots. When expressed on an area basis, yields in the F2-treated plots ranged from 2.76 × 103 to 6.42 × 104 kg·ha−1, depending on crop type, and were consistently higher than those of the controls. Yield increases varied among crops but remained positive in all cases. Flax exhibited a yield increase of 26.85 ± 1.24%, while maize showed the most pronounced response, with a yield increase of 32.37 ± 1.36%. Sorghum, edible sunflower, and potato also displayed clear yield advantages under F2 treatment, with yield increases ranging between 20% and 30%. These results demonstrate that the growth-promoting effects of F2 observed at the physiological level translated effectively into harvestable yield gains under field conditions.
Importantly, yield enhancement was observed even under the lowest cumulative F2 input, which corresponded to crops with shorter growth cycles and fewer top-dressing events. Based on the standardized dataset (Table S5), the lowest cumulative F2 application rate that still resulted in statistically significant improvements in yield and soil quality indicators was identified as the minimum effective dose within the tested experimental range, is 727.2 kg·ha−1.

4. Discussion

4.1. Soil Physicochemical Improvement and Functional Activation Under F2 Amendment

Soil salinization and alkalization pose a global agricultural challenge by degrading soil structure, nutrient availability, and overall productivity. In the present study, application of the F2 amendment (CFP-treated group) resulted in systematic and statistically significant improvements in the physicochemical properties of moderately saline–alkali soils. Specifically, soil EC and pH were markedly reduced, while field water capacity, organic matter content, aggregate stability, and nutrient pools were significantly enhanced. These outcomes provide direct evidence that the combined carrier–microorganism system effectively alleviated salinity- and alkalinity-related constraints at the soil level.
Quantitatively, the reductions in EC and pH indicate a weakened osmotic and ionic stress environment for plant roots, which is a prerequisite for restoring soil functionality. Concurrent increases in organic matter and water-holding capacity further suggest improved soil structure and moisture regulation, both of which are critical for root growth and microbial activity in saline–alkali soils. These improvements are consistent with the observation that soil fertility indicators, including TN, TP, TK, NO3-N, A-P, and A-K, were significantly elevated under F2 treatment, confirming a comprehensive enhancement of soil nutrient status [35].
Mechanistically, these changes can be attributed to the synergistic effects of the composite carrier and the functional microbial consortium. Organic acids and phenolic compounds released during the gradual decomposition of pine needle components likely neutralized alkaline ions and promoted humus formation, thereby improving soil colloidal stability and cation exchange capacity [36]. At the same time, the porous structure and cellulose- and hemicellulose-rich composition of crushed corn cobs provided continuous carbon inputs and stable physical habitats for microorganisms, enhancing soil aeration and aggregate formation [37]. The diversity of carbon substrates supplied by the composite carrier is also known to stimulate microbial metabolic activity and functional diversity in saline–alkali soils [38].
Beyond carrier-driven effects, the inoculated salt-tolerant strains (K1, Y1, and J3) directly contributed to soil biochemical regulation. Through the secretion of organic acids and extracellular polymeric substances, these microorganisms participated in Na+ adsorption, Ca2+–Na+ exchange, and aggregate cementation, reinforcing soil structural recovery at the biochemical level [39]. This microbial contribution is further reflected in the pronounced activation of soil enzymes involved in nutrient cycling.
Soil enzyme analyses showed that activities of S-Urea, S-ALP, and S-SC were significantly higher in the CFP group than in the control, indicating enhanced turnover and availability of C, N, and P elements [35]. Although S-CAT activity decreased under F2 treatment, catalase primarily functions to detoxify reactive oxygen species in stressed soils [40]. Therefore, its reduction is more plausibly interpreted as a consequence of alleviated oxidative stress rather than impaired antioxidant capacity [41]. Taken together, these results confirm that F2 amendment improves soil physicochemical conditions and activates soil biochemical functions through coordinated carrier and microbial effects.

4.2. Microbial Community Restructuring and Functional Enhancement

The improvements observed in soil physicochemical properties were accompanied by pronounced restructuring of soil microbial communities. The rational combination of multifunctional strains provided the biological foundation for this regulation. Previous studies have shown that functionally diverse microorganisms can promote soil health and plant performance through complementary mechanisms, including hormone production, nutrient mobilization, organic matter decomposition, and soil aggregation [42,43,44,45,46,47,48]. However, microbial antagonism and competition can destabilize artificial consortia and compromise functional expression [49,50].
In the present study, antagonistic interactions between strain L1 and strains K1, J1, and Z1 were identified, leading to their exclusion from the final formulation. In contrast, co-culture experiments demonstrated a clear symbiotic relationship among strains K1, Y1, and J3. The total biomass produced under co-culture conditions exceeded the sum of their individual biomasses, providing experimental evidence for positive interspecific interactions and functional complementarity [51]. This confirmed that the selected consortium possesses the intrinsic stability required for effective colonization and persistence in saline–alkali soil environments.
High-throughput sequencing further revealed that the F2 amendment significantly enhanced microbial diversity and community complexity. Compared with the CK and CP treatments, which exhibited low bacterial and fungal diversity under severe saline–alkali stress, the CFP group showed marked increases in community richness, evenness, and structural complexity. Treatments such as CSP, CEM, COM, and CMP partially altered dominant taxa but failed to restore overall community complexity to the level observed in the CFP group. These results indicate that the composite carrier–microorganism system effectively reduced environmental filtering pressure while simultaneously providing diverse ecological niches and carbon resources for microbial proliferation.
At the taxonomic level, F2 treatment promoted the enrichment of stress-resistant and functionally important microbial groups. At the phylum level, Actinomycetota, Chloroflexota, and Basidiomycota were significantly enriched, taxa known for their metabolic versatility and tolerance to adverse environmental conditions [52,53]. At the genus level, the increased abundance of Endomicrobium, Zeaxanthinibacter, Nitrolancea, and Luteitalea indicates enhanced capacities for cellulose degradation, humus formation, nitrification, and nutrient transformation [54,55,56,57]. This selective enrichment of beneficial taxa demonstrates that F2 does not merely increase microbial abundance but actively steers community composition toward functionally advantageous assemblages, consistent with synergistic regulation theory [58].
Fungal community responses further supported this conclusion. The enrichment of saprotrophic and symbiotic fungi such as Podospora and Rhizophagus suggests accelerated organic matter turnover and improved plant nutrient acquisition, while the reduced abundance of potential pathogens (Fusarium and Alternaria) implies a healthier rhizosphere environment [59,60,61]. Functional prediction analysis revealed increased representation of pathways related to carbohydrate metabolism, amino acid metabolism, and energy metabolism, reflecting enhanced metabolic flexibility and ecological stability of the microbial community [62,63].

4.3. Plant Physiological Responses and Soil–Microbe–Plant Coupling

The coordinated improvements in soil properties and microbial community structure were directly translated into enhanced plant growth and physiological performance. In the pot experiment, maize plants treated with the F2 amendment exhibited significantly greater aboveground biomass accumulation, more developed root systems, and increased plant height compared with other treatments. These growth responses were accompanied by a pronounced increase in leaf chlorophyll content, indicating enhanced photosynthetic capacity and nutrient uptake efficiency [64,65].
Physiological stress indicators further confirmed the stress-alleviating effects of F2. Malondialdehyde (MDA) content in CFP-treated plants was significantly lower than in other treatments, reflecting reduced membrane lipid peroxidation and improved cellular membrane stability under saline–alkali conditions [66]. In parallel, water-soluble sugar (WSS) accumulation was lowest in the CFP group, suggesting that plants experienced reduced osmotic stress and therefore required less synthesis of compatible solutes to maintain cellular homeostasis [67,68]. These results collectively demonstrate that F2 effectively mitigated salt-induced physiological stress at the plant level.
Comparative analysis among treatments highlights the integrative advantage of the F2 strategy. Compost-only treatment (COM) primarily relied on organic matter inputs and lacked the driving force of functional microbial communities, resulting in limited and unstable effects. Single microbial agent treatment (CEM) showed insufficient persistence due to the absence of carrier protection and continuous carbon supply. Treatments relying on a single carrier or lacking sustained carbon input (CSP and CMP) provided partial benefits but failed to achieve consistent improvements across multiple indicators. In contrast, F2 successfully integrated a multifunctional microbial consortium with a composite carrier system, establishing a stable soil–microbe–plant interaction network.
Importantly, the superiority of F2 was not limited to controlled pot conditions. Field trials across multiple crop systems further confirmed its ability to enhance crop growth, physiological status, and stress tolerance under saline–alkali conditions. These results demonstrate that the benefits of F2 arise from a coupled mechanism in which improved soil structure and fertility support microbial activity, enhanced microbial functions promote nutrient cycling, and improved nutrient availability and reduced stress jointly drive crop performance. Together, these findings provide strong evidence that the F2 amendment establishes a robust and efficient soil–microbe–plant coupling system capable of sustaining crop productivity in saline–alkali environments.

4.4. Cross-Regional Comparison and Scalability Potential of the F2 Strategy

Multi-crop field trials demonstrated that the positive effects of the F2 soil conditioner were consistent across different crop systems, indicating that its remediation and growth-promoting functions were not crop-specific. Similar organic–microbial composite strategies have been widely investigated in saline–alkali soils in different regions, providing a useful basis for cross-regional comparison.
In China, studies conducted in inland saline–alkali regions, particularly in northern and northwestern agricultural systems, have reported that organic amendments or bio-based conditioners significantly reduce soil EC and pH while improving soil organic matter, nutrient availability, and crop performance [9,10,13]. These results are generally consistent with our findings, suggesting that carbon-rich materials combined with biological regulation are effective in arid and semi-arid saline–alkali soils dominated by coarse texture and strong evaporative salt accumulation. By contrast, studies in southern or coastal saline–alkali soils—characterized by higher clay content, distinct ion compositions, and stronger hydrological influences—have shown that organic amendments primarily regulate nutrient retention and nitrogen transformation processes rather than structural amelioration alone [69,70]. These regional differences highlight that soil texture and hydrological conditions strongly influence the dominant remediation pathways, although the overall effectiveness of organic–microbial composites remain evident.
Internationally, similar trends have been observed across diverse saline–alkali environments. Studies combining organic carriers or carbonaceous materials with beneficial microorganisms have consistently reported improvements in soil quality, microbial diversity, and plant growth under saline stress [15,71]. These findings suggest that synergistic carrier–microorganism systems represent a broadly applicable remediation approach, although the magnitude of response may vary depending on climate, soil properties, and crop species.
From a scalability perspective, the F2 strategy exhibits several practical advantages. The carrier materials—pine needles and crushed corn cobs are abundant agricultural and forestry residues, supporting low-cost and sustainable large-scale production. Moreover, the composite microbial agent meets the Chinese “Composite Microbial Fertilizer (NY/T 798-2015)” standard for effective viable cell counts and strain composition [72], providing a technical foundation for standardized manufacturing and quality control. The solid carrier-based formulation further enhances microbial survival during storage and transport, facilitating field application and long-term effectiveness.
Overall, the consistency of F2 effects across multiple crops, its alignment with outcomes reported in other saline–alkali regions, and its favorable material and formulation characteristics collectively indicate strong potential for regional expansion and industrial-scale application. While site-specific optimization may be required to account for differences in soil texture and hydrological regimes, the F2 strategy represents a promising, scalable solution for sustainable saline–alkali land remediation.

5. Conclusions

This study developed the F2 soil amendment through steps such as strain screening, co-culture verification, and ratio optimization, which consists of a synergistic microbial consortium (K1, Y1, J3) and a composite carrier composed of pine needles and ground corn husks. Based on pot experiments and multi-crop field trials, the main conclusions are as follows: (i) F2 application significantly reduced soil pH and electrical conductivity, increased soil nutrient availability, and enhanced key enzyme activities involved in C, N, and P cycling. Improvements in soil physical structure-related indicators, including bulk density, porosity, and field water capacity, indicate more favorable soil conditions under saline–alkali stress. (ii) High-throughput sequencing showed that the F2 application was associated with clear shifts in rhizosphere microbial community composition and enrichment of taxa related to nutrient cycling and organic matter turnover. Correlation analyses further demonstrated significant associations between soil nutrients, enzyme activities, and the abundance of these functional microbial groups. (iii) Across pot and field experiments, F2-treated crops exhibited improved growth and physiological status, including higher chlorophyll content and reduced oxidative stress indicators, consistent with enhanced stress tolerance. Overall, compared with the single application of organic amendments or microbial agents, F2 showed more stable and integrated benefits across soil, microbial, and plant indicators, supporting its potential as a bio-based approach for the green management of saline–alkali-affected farmland.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microorganisms14020304/s1, Figure S1: Schematic diagram of experimental design; Figure S2: Soil physicochemical properties at plant maturity stage (field experiment); Figure S3: Plant growth and physiological indicators at plant maturity stage (field experiment); Table S1: Physicochemical properties, texture fractions, and salinity–sodicity characteristics of the experimental soil; Table S2: Composite Soil Improvement Index (CSII) based on normalized changes in soil physicochemical properties and enzyme activities at 60 days; Table S3: Soil nutrient parameters across different treatments; Table S4: Alpha diversity index of microorganisms in rhizosphere soil; Table S5: Standardized yield metrics and F2 application rate in multi-crop field trials.

Author Contributions

Conceptualization, M.Z. and X.C.; methodology, W.L. (Wei Liu); software, Z.L. (Ziting Li); validation, W.L. (Wangrun Li); formal analysis, Z.L. (Zhaoyu Li) and Y.T.; investigation, F.Y.; resources, W.Z., G.Z. and T.C.; data curation, Z.G.; writing—original draft preparation, X.C.; writing—review and editing, X.C.; visualization, X.C.; supervision, M.Z.; project administration, M.Z.; funding acquisition, M.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by (1) Open Fund of the Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province (EEMRE202601); (2) Major Project of Gansu Province (26ZDNA010); (3) Natural Science Foundation of Gansu Province Project (25JRRA173); (4) National Key R&D Program of China (2025YFD1700600); (5) Undergraduate Key Teaching Reform Project of Lanzhou Jiaotong University (2024); (6) Graduate Students Key Teaching Reform Project for Graduate Students at Lanzhou Jiaotong University (2024).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw sequencing reads were deposited in the NCBI Sequence Read Archive (SRA) database (Accession Number: SRP606161). Further inquiries can be directed to the corresponding authors upon reasonable request.

Acknowledgments

We would like to thank all the reviewers who participated in the review.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ECElectrical conductivity
SARSodium adsorption ratio
ESPExchangeable sodium percentage
S-ALPSoil alkaline phosphatase
S-UreaSoil urease
S-SCSoil sucrase
S-CATSoil catalase
TNTotal nitrogen
TPTotal phosphorus
TKTotal potassium
NO3-NNitrate nitrogen
A-PAvailable phosphorus
A-KAvailable potassium
STPSoil total porosity
OMOrganic matter
HePlant height
RLRoot length
SDStem diameter
CHLChlorophyll
MDAMalondialdehyde
WSSSoluble sugar

References

  1. Daszkiewicz, T. Food Production in the Context of Global Developmental Challenges. Agriculture 2022, 12, 832. [Google Scholar] [CrossRef]
  2. Tarolli, P.; Luo, J.; Park, E.; Barcaccia, G.; Masin, R. Soil salinization in agriculture: Mitigation and adaptation strategies combining nature-based solutions and bioengineering. iScience 2024, 27, 108830. [Google Scholar] [CrossRef]
  3. Daba, A.W. Rehabilitation of soil salinity and sodicity using diverse amendments and plants: A critical review. Discov. Environ. 2025, 3, 53. [Google Scholar] [CrossRef]
  4. Li, Z.; Kekeli, M.A.; Jiang, Y.; Rui, Y. Progress and Prospect of Saline-Alkaline Soil Management Technology: A Review. Appl. Sci. 2025, 15, 4567. [Google Scholar] [CrossRef]
  5. Akimbekov, N.; Digel, I.; Kamenov, B.; Altynbay, N.; Tastambek, K.; Zha, J.; Tepecik, A.; Sakhanova, S.K. Screening halotolerant bacteria for their potential as plant growth-promoting and coal-solubilizing agents. Sci. Rep. 2025, 15, 13138. [Google Scholar] [CrossRef] [PubMed]
  6. Zhang, G.; Bai, J.; Zhai, Y.; Jia, J.; Zhao, Q.; Wang, W.; Hu, X. Microbial diversity and functions in saline soils: A review from a biogeochemical perspective. J. Adv. Res. 2024, 59, 129–140. [Google Scholar] [CrossRef] [PubMed]
  7. Mokrani, S.; Nabti, E.-h.; Cruz, C. Recent Trends in Microbial Approaches for Soil Desalination. Appl. Sci. 2022, 12, 3586. [Google Scholar] [CrossRef]
  8. Liu, Z.; Li, J.; Zhang, Y.; Gong, H.; Hou, R.; Sun, Z.; Ouyang, Z. Soil Microbes from Saline–Alkali Farmland Can Form Carbonate Precipitates. Agronomy 2023, 13, 372. [Google Scholar] [CrossRef]
  9. Wang, Y.; Gao, M.; Chen, H.; Chen, Y.; Wang, L.; Wang, R. Organic Amendments promote saline-alkali soil desalinization and enhance maize growth. Front. Plant Sci. 2023, 14, 1177209. [Google Scholar] [CrossRef]
  10. Shabaan, M.; Asghar, H.N.; Zahir, Z.A.; Zhang, X.; Sardar, M.F.; Li, H. Salt-Tolerant PGPR Confer Salt Tolerance to Maize Through Enhanced Soil Biological Health, Enzymatic Activities, Nutrient Uptake and Antioxidant Defense. Front. Microbiol. 2022, 13, 901865. [Google Scholar] [CrossRef]
  11. Kumawat, K.C.; Sharma, B.; Nagpal, S.; Kumar, A.; Tiwari, S.; Nair, R.M. Plant growth-promoting rhizobacteria: Salt stress alleviators to improve crop productivity for sustainable agriculture development. Front. Plant Sci. 2023, 13, 1101862. [Google Scholar] [CrossRef] [PubMed]
  12. Li, H.-P.; Ma, H.-B.; Zhang, J.-L. Halo-tolerant plant growth-promoting bacteria-mediated plant salt resistance and microbiome-based solutions for sustainable agriculture in saline soils. FEMS Microbiol. Ecol. 2025, 101, fiaf037. [Google Scholar] [CrossRef] [PubMed]
  13. Chen, M.; Zhang, S.; Liu, L.; Wu, L.; Ding, X. Combined organic amendments and mineral fertilizer application increase rice yield by improving soil structure, P availability and root growth in saline-alkaline soil. Soil Tillage Res. 2021, 212, 105060. [Google Scholar] [CrossRef]
  14. Chen, L.; Du, H.; Liu, Q.; Gao, W.; Cui, J.; Chen, Y. Organic waste recycling application increases N availability and mitigates N2O emission without crop yield penalty in the North China Plain. Front. Plant Sci. 2024, 15, 1446277. [Google Scholar] [CrossRef]
  15. Riddech, N.; Theerakulpisut, P.; Ma, Y.N.; Sarin, P. Bioorganic fertilizers from agricultural waste enhance rice growth under saline soil conditions. Sci. Rep. 2025, 15, 8979. [Google Scholar] [CrossRef]
  16. Hoque, M.N.; Imran, S.; Hannan, A.; Paul, N.C.; Mahamud, M.A.; Chakrobortty, J.; Sarker, P.; Irin, I.J.; Brestic, M.; Rhaman, M.S. Organic Amendments for Mitigation of Salinity Stress in Plants: A Review. Life 2022, 12, 1632. [Google Scholar] [CrossRef]
  17. Meena, M.D.; Yadav, R.K.; Narjary, B.; Yadav, G.; Jat, H.S.; Sheoran, P.; Meena, M.K.; Antil, R.S.; Meena, B.L.; Singh, H.V.; et al. Municipal solid waste (MSW): Strategies to improve salt affected soil sustainability: A review. Waste Manag. 2019, 84, 38–53. [Google Scholar] [CrossRef]
  18. Luo, S.; Wang, S.; Tian, L.; Shi, S.; Xu, S.; Yang, F.; Li, X.; Wang, Z.; Tian, C. Aggregate-related changes in soil microbial communities under different ameliorant applications in saline-sodic soils. Geoderma 2018, 329, 108–117. [Google Scholar] [CrossRef]
  19. Marcińczyk, M.; Oleszczuk, P. Biochar and engineered biochar as slow-and controlled-release fertilizers. J. Clean. Prod. 2022, 339, 130685. [Google Scholar] [CrossRef]
  20. Kraut-Cohen, J.; Zolti, A.; Rotbart, N.; Bar-Tal, A.; Laor, Y.; Medina, S.; Shawahna, R.; Saadi, I.; Raviv, M.; Green, S.; et al. Short-and long-term effects of continuous compost conditioner on soil microbiome community. Comput. Struct. Biotechnol. 2023, 21, 3280–3292. [Google Scholar] [CrossRef]
  21. Zhou, T.; Wang, Z.; Lv, Q.; Zhang, Y.; Tao, S.; Ren, X.; Gao, H.; Gao, Z.; Hu, S. Sulfur dynamics in saline sodic soils: The role of paddy cultivation and organic amendments. Ecol. Indic. 2024, 162, 112014. [Google Scholar] [CrossRef]
  22. Ma, X.; Huang, C.; Zhang, J.; Pan, J.; Guo, Q.; Yang, H.; Xue, X. Comparative Analysis of Plant Growth-Promoting Rhizobacteria’s Effects on Alfalfa Growth at the Seedling and Flowering Stages under Salt Stress. Microorganisms 2024, 12, 616. [Google Scholar] [CrossRef] [PubMed]
  23. Zhang, Y.; Zhang, N.; Bi, X.; Bi, T.; Baloch, F.B.; Miao, J.; Zeng, N.; Li, B.; An, Y. Growth promotion on maize and whole-genome sequence analysis of Bacillus velezensis D103. Microbiol. Spectr. 2024, 12, e01147-24. [Google Scholar] [CrossRef] [PubMed]
  24. Ganesh, J.; Hewitt, K.; Devkota, A.R.; Wilson, T.; Kaundal, A. IAA-producing plant growth promoting rhizobacteria from Ceanothus velutinus enhance cutting propagation efficiency and Arabidopsis biomass. Front. Plant Sci. 2024, 15, 1374877. [Google Scholar] [CrossRef]
  25. Chen, W.; Niu, T.; Lian, W.; Ye, T.; Sun, Q.; Zhang, J. Involvement of endogenous IAA and ABA in the regulation of arbuscular mycorrhizal fungus on rooting of tea plant (Camellia sinensis L.) cuttings. BMC Plant Biol. 2024, 24, 1266. [Google Scholar] [CrossRef]
  26. Yang, J.; Wang, T.; Que, S.; Li, Z.; Liang, Y.; Wei, Y.; Li, N.; Xu, Z. Effect of colour calibration on the prediction of soil organic matter content based on original soil images obtained from smartphones under different lighting conditions. Soil Tillage Res. 2024, 238, 106018. [Google Scholar] [CrossRef]
  27. Guo, J.; Fan, Y.; Li, Y.; Bi, Y.; Wang, S.; Hu, Y.; Zhang, L.; Song, W. Topography Dominates the Spatial and Temporal Variability of Soil Bulk Density in Typical Arid Zones. Sustainability 2024, 16, 9670. [Google Scholar] [CrossRef]
  28. Almaz, C.; Miháliková, M.; Báťková, K.; Vopravil, J.; Matula, S.; Khel, T.; Kara, R.S. Simple and Cost-Effective Method for Reliable Indirect Determination of Field Capacity. Hydrology 2023, 10, 202. [Google Scholar] [CrossRef]
  29. Baćmaga, M.; Kucharski, J.; Wyszkowska, J. Microbial and enzymatic activity of soil contaminated with azoxystrobin. Environ. Monit. Assess 2015, 187, 615. [Google Scholar] [CrossRef]
  30. Huang, M.; Fu, H.; Kong, X.; Ma, L.; Liu, C.; Fang, Y.; Zhang, Z.; Song, F.; Yang, F. Effects of Fertilization Methods on Chemical Properties, Enzyme Activity, and Fungal Community Structure of Black Soil in Northeast China. Diversity 2020, 12, 476. [Google Scholar] [CrossRef]
  31. Luo, Q.; Xie, H.; Chen, Z.; Ma, Y.; Yang, H.; Yang, B.; Ma, Y. Morphology, photosynthetic physiology and biochemistry of nine herbaceous plants under water stress. Front. Plant Sci. 2023, 14, 1147208. [Google Scholar] [CrossRef] [PubMed]
  32. Huang, X.J.; Jian, S.F.; Chen, D.L.; Zhong, C.; Miao, J.H. Concentration-dependent dual effects of exogenous sucrose on nitrogen metabolism in Andrographis paniculata. Sci. Rep. 2022, 12, 4906. [Google Scholar] [CrossRef] [PubMed]
  33. El-Badri, A.M.; Batool, M.; AA Mohamed, I.; Wang, Z.; Khatab, A.; Sherif, A.; Ahmad, H.; Khan, M.N.; Hassan, H.M.; Elrewainy, I.M.; et al. Antioxidative and Metabolic Contribution to Salinity Stress Responses in Two Rapeseed Cultivars during the Early Seedling Stage. Antioxidants 2021, 10, 1227. [Google Scholar] [CrossRef] [PubMed]
  34. Bukin, Y.S.; Galachyants, Y.P.; Morozov, I.V.; Bukin, S.V.; Zakharenko, A.S.; Zemskaya, T.I. The effect of 16S rRNA region choice on bacterial community metabarcoding results. Sci. Data 2019, 6, 190007, Erratum in Sci. Data 2022, 9, 94.. [Google Scholar] [CrossRef]
  35. Shaaban, M.; Wu, Y.; Núñez-Delgado, A.; Kuzyakov, Y.; Peng, Q.A.; Lin, S.; Hu, R. Enzyme activities and organic matter mineralization in response to application of gypsum, manure and rice straw in saline and sodic soils. Environ. Res. 2023, 224, 115393. [Google Scholar] [CrossRef]
  36. Yang, R.; Sun, Z.; Liu, X.; Long, X.; Gao, L.; Shen, Y. Biomass composite with exogenous organic acid addition supports the growth of sweet sorghum (Sorghum bicolor ‘Dochna’) by reducing salinity and increasing nutrient levels in coastal saline-alkaline soil. Front. Plant Sci. 2023, 14, 1163195. [Google Scholar] [CrossRef]
  37. Haddad, S.A.; Lemanowicz, J. Benefits of Corn-Cob Biochar to the Microbial and Enzymatic Activity of Soybean Plants Grown in Soils Contaminated with Heavy Metals. Energies 2021, 14, 5763. [Google Scholar] [CrossRef]
  38. Hu, W.; Zhang, Y.; Rong, X.; Zhou, X.; Fei, J.; Peng, J.; Luo, G. Biochar and organic fertilizer applications enhance soil functional microbial abundance and agroecosystem multifunctionality. Biochar 2024, 6, 3. [Google Scholar] [CrossRef]
  39. Zhang, M.; Wu, Y.; Qu, C.; Huang, Q.; Cai, P. Microbial extracellular polymeric substances (EPS) in soil: From interfacial behaviour to ecological multifunctionality. Geo-Bio Interfaces 2024, 1, e4. [Google Scholar] [CrossRef]
  40. Abdel Latef, A.A.H.; Kordrostami, M.; Zakir, A.; Zaki, H.; Saleh, O.M. Eustress with H2O2 Facilitates Plant Growth by Improving Tolerance to Salt Stress in Two Wheat Cultivars. Plants 2019, 8, 303. [Google Scholar] [CrossRef]
  41. Li, W.; Zhong, M.; Wang, H.; Shi, X.; Song, J.; Wang, J.; Zhang, W. Exogenous carbon inputs alleviated salt-induced oxidative stress to cotton in salinized field by improving soil aggregate structure and microbial community. Front. Plant Sci. 2025, 16, 1522534. [Google Scholar] [CrossRef] [PubMed]
  42. Hashem, A.; Tabassum, B.; Fathi Abd_Allah, E. Bacillus subtilis: A plant-growth promoting rhizobacterium that also impacts biotic stress. Saudi J. Biol. Sci. 2019, 26, 1291–1297. [Google Scholar] [CrossRef] [PubMed]
  43. Feng, Y.; Tian, B.; Xiong, J.; Lin, G.; Cheng, L.; Zhang, T.; Lin, B.; Ke, Z.; Li, X. Exploring IAA biosynthesis and plant growth promotion mechanism for tomato root endophytes with incomplete IAA synthesis pathways. Chem. Biol. Technol. Agric. 2024, 11, 187. [Google Scholar] [CrossRef]
  44. Chandrasekaran, M.; Chun, S.C.; Oh, J.W.; Paramasivan, M.; Saini, R.K.; Sahayarayan, J.J. Bacillus subtilis CBR05 for Tomato (Solanum lycopersicum) Fruits in South Korea as a Novel Plant Probiotic Bacterium (PPB): Implications from Total Phenolics, Flavonoids, and Carotenoids Content for Fruit Quality. Agronomy 2019, 9, 838. [Google Scholar] [CrossRef]
  45. Chauhan, P.; Sharma, N.; Tapwal, A.; Kumar, A.; Verma, G.S.; Meena, M.; Seth, C.S.; Swapnil, P. Soil Microbiome: Diversity, Benefits and Interactions with Plants. Sustainability 2023, 15, 14643. [Google Scholar] [CrossRef]
  46. Bellenger, J.P.; Darnajoux, R.; Zhang, X.; Kraepiel, A.M.L. Biological nitrogen fixation by alternative nitrogenases in terrestrial ecosystems: A review. Biogeochemistry 2020, 149, 53–73. [Google Scholar] [CrossRef]
  47. Botha, A. The importance and ecology of yeasts in soil. Soil Biol. Biochem. 2011, 43, 1–8. [Google Scholar] [CrossRef]
  48. Hernández-Melchor, D.J.; Guerrero-Chávez, A.C.; Ferrera-Rodríguez, M.R.; Ferrera-Cerrato, R.; Larsen, J.; Alarcón, A. Cellulase and chitinase activities and antagonism against Fusarium oxysporum f.sp. cubense race 1 of six Trichoderma strains isolated from Mexican maize cropping. Biotechnol. Lett. 2023, 45, 387–400. [Google Scholar] [CrossRef]
  49. Wang, C.; Kuzyakov, Y. Mechanisms and implications of bacterial-fungal competition for soil resources. ISME J. 2024, 18, wrae073. [Google Scholar] [CrossRef]
  50. Yim, S.S.; Wang, H.H. Exploiting interbacterial antagonism for microbiome engineering. Curr. Opin. Biomed. Eng. 2021, 19, 100307. [Google Scholar] [CrossRef]
  51. Foster, K.R.; Bell, T. Competition, Not Cooperation, Dominates Interactions among Culturable Microbial Species. Curr. Biol. 2012, 22, 1845–1850. [Google Scholar] [CrossRef]
  52. Borsodi, A.K. Taxonomic diversity of extremophilic prokaryotes adapted to special environmental parameters in Hungary: A review. Biol. Futur. 2024, 75, 183–192. [Google Scholar] [CrossRef]
  53. Williams Timothy, J.; Allen Michelle, A.; Ray Angelique, E.; Benaud, N.; Chelliah Devan, S.; Albanese, D.; Donati, C.; Selbmann, L.; Coleine, C.; Ferrari Belinda, C. Novel endolithic bacteria of phylum Chloroflexota reveal a myriad of potential survival strategies in the Antarctic desert. Appl. Environ. Microbiol. 2024, 90, e02264-23. [Google Scholar] [CrossRef]
  54. Li, Y.; Kuramae, E.E.; Nasir, F.; Wang, E.; Zhang, Z.; Li, J.; Yao, Z.; Tian, L.; Sun, Y.; Luo, S.; et al. Addition of cellulose degrading bacterial agents promoting keystone fungal-mediated cellulose degradation during aerobic composting: Construction the complex co-degradation system. Bioresour. Technol. 2023, 381, 129132. [Google Scholar] [CrossRef] [PubMed]
  55. Zhao, X.; Miao, R.; Guo, M.; Shang, X.; Zhou, Y.; Zhu, J. Biochar enhanced polycyclic aromatic hydrocarbons degradation in soil planted with ryegrass: Bacterial community and degradation gene expression mechanisms. Sci. Total Environ. 2022, 838, 156076. [Google Scholar] [CrossRef] [PubMed]
  56. Boddicker, A.M.; Mosier, A.C. Genomic profiling of four cultivated Candidatus nitrotoga spp. predicts broad metabolic potential and environmental distribution. ISME J. 2018, 12, 2864–2882. [Google Scholar] [CrossRef] [PubMed]
  57. Vieira, S.; Luckner, M.; Wanner, G.; Overmann, J. Luteitalea pratensis gen. nov.; sp. nov. a new member of subdivision 6 Acidobacteria isolated from temperate grassland soil. Int. J. Syst. Evol. Microbiol. 2017, 67, 1408–1414. [Google Scholar] [CrossRef]
  58. Peng, Y.; Zhang, H.; Lian, J.; Zhang, W.; Li, G.; Zhang, J. Combined Application of Organic Fertilizer with Microbial Inoculum Improved Aggregate Formation and Salt Leaching in a Secondary Salinized Soil. Plants 2023, 12, 2945. [Google Scholar] [CrossRef]
  59. Dicko, M.; Ferrari, R.; Tangthirasunun, N.; Gautier, V.; Lalanne, C.; Lamari, F.; Silar, P. Lignin Degradation and Its Use in Signaling Development by the Coprophilous Ascomycete Podospora anserina. J. Fungi. 2020, 6, 278. [Google Scholar] [CrossRef]
  60. Roussis, I.; Beslemes, D.; Kosma, C.; Triantafyllidis, V.; Zotos, A.; Tigka, E.; Mavroeidis, A.; Karydogianni, S.; Kouneli, V.; Travlos, I.; et al. The Influence of Arbuscular Mycorrhizal Fungus Rhizophagus irregularis on the Growth and Quality of Processing Tomato (Lycopersicon esculentum Mill.) Seedlings. Sustainability 2022, 14, 9001. [Google Scholar] [CrossRef]
  61. Andreo-Jimenez, B.; Schilder, M.T.; Nijhuis, E.H.; Te Beest, D.E.; Bloem, J.; Visser, J.H.M.; van Os, G.; Brolsma, K.; de Boer, W.; Postma, J. Chitin- and Keratin-Rich Soil Amendments Suppress Rhizoctonia solani Disease via Changes to the Soil Microbial Community. Appl. Environ. Microb. 2021, 87, e00318-21. [Google Scholar] [CrossRef] [PubMed]
  62. Chen, H.; Ma, K.; Huang, Y.; Yao, Z.; Chu, C. Stable Soil Microbial Functional Structure Responding to Biodiversity Loss Based on Metagenomic Evidences. Front. Microbiol. 2021, 12, 716764. [Google Scholar] [CrossRef] [PubMed]
  63. Liang, M.; Wu, Y.; Jiang, Y.; Zhao, Z.; Yang, J.; Liu, G.; Xue, S. Microbial functional genes play crucial roles in enhancing soil nutrient availability of halophyte rhizospheres in salinized grasslands. Sci. Total Environ. 2025, 958, 178160. [Google Scholar] [CrossRef] [PubMed]
  64. Kelbessa, B.G.; Dubey, M.; Catara, V.; Ghadamgahi, F.; Ortiz, R.; Vetukuri, R.R. Potential of plant growth-promoting rhizobacteria to improve crop productivity and adaptation to a changing climate. CABI Rev. 2023. [Google Scholar] [CrossRef]
  65. Chen, X.; Jiang, Y.; Cong, Y.; Liu, X.; Yang, Q.; Xing, J.; Liu, H. Ascorbic Acid Mitigates Salt Stress in Tomato Seedlings by Enhancing Chlorophyll Synthesis Pathways. Agronomy 2024, 14, 1810. [Google Scholar] [CrossRef]
  66. Hnilickova, H.; Kraus, K.; Vachova, P.; Hnilicka, F. Salinity Stress Affects Photosynthesis, Malondialdehyde Formation, and Proline Content in Portulaca oleracea L. Plants 2021, 10, 845. [Google Scholar] [CrossRef]
  67. Xiao, N.; Ma, H.; Wang, W.; Sun, Z.; Li, P.; Xia, T. Overexpression of ZmSUS1 increased drought resistance of maize (Zea mays L.) by regulating sucrose metabolism and soluble sugar content. Planta 2024, 259, 43. [Google Scholar] [CrossRef]
  68. Afzal, S.; Chaudhary, N.; Singh, N.K. Role of Soluble Sugars in Metabolism and Sensing Under Abiotic Stress. In Plant Growth Regulators; Aftab, T., Hakeem, K.R., Eds.; Springer: Cham, Switzerland, 2021; pp. 305–334. [Google Scholar]
  69. Zhang, H.; Xu, Z.; Guo, K.; Huo, Y.; He, G.; Sun, H. Organic amendments improve nitrogen retention and reduce nitrogen loss in coastal saline soil of eastern China. Agr. Ecosyst. Environ. 2019, 272, 1–10. [Google Scholar]
  70. Zhao, Y.; Wang, S.; Li, Y.; Liu, J.; Zhuo, Y.; Zhang, X. Responses of nitrogen transformation processes to organic amendments in a coastal saline soil with high clay content. Geoderma 2020, 366, 114237. [Google Scholar]
  71. Wang, X.; Li, Z.; Xing, Y. Biochar–microbial interactions in saline soils: Implications for soil quality improvement and plant growth promotion. Sci. Total Environ. 2021, 763, 142965. [Google Scholar]
  72. NY/T 798-2015; Compound Microbial Fertilizer. China Agriculture Press: Beijing, China, 2015.
Figure 1. Screening and performance identification of functional microorganisms. (a) microbial antagonistic experiment; (b) potassium resolving property; (c) nitrogen fixation characteristic; (d) solubility of organic phosphorus and inorganic phosphorus; (e) indole-3-acetic acid production characteristics; (f) salt tolerance of microorganisms; (g) alkaline tolerance of microorganisms; (h) curve growth of microorganisms; (i) commensalism relationship between K1 and Y1; (j) neutralism relationship between Y1 and J3; (k) mutualism relationship between K1 and J3, green and blue columns are the biomass of individual culture, gray column is the total biomass of co-culture, dotted line is the sum of the biomass of individual. CK, K1, Z1, Y1, E1, J1, J2, J3, J4 and L1, respectively, represent blank control, Bacillus subtilis, Lactobacillus plantarum, Azotobacter chroococcum, Bacillus lateralis, Bacillus giganteum, Bacillus amylolyticus, Bacillus gelatinus, Saccharomyces and Richoderma viridis. Data are means ± SD (n = 3).
Figure 1. Screening and performance identification of functional microorganisms. (a) microbial antagonistic experiment; (b) potassium resolving property; (c) nitrogen fixation characteristic; (d) solubility of organic phosphorus and inorganic phosphorus; (e) indole-3-acetic acid production characteristics; (f) salt tolerance of microorganisms; (g) alkaline tolerance of microorganisms; (h) curve growth of microorganisms; (i) commensalism relationship between K1 and Y1; (j) neutralism relationship between Y1 and J3; (k) mutualism relationship between K1 and J3, green and blue columns are the biomass of individual culture, gray column is the total biomass of co-culture, dotted line is the sum of the biomass of individual. CK, K1, Z1, Y1, E1, J1, J2, J3, J4 and L1, respectively, represent blank control, Bacillus subtilis, Lactobacillus plantarum, Azotobacter chroococcum, Bacillus lateralis, Bacillus giganteum, Bacillus amylolyticus, Bacillus gelatinus, Saccharomyces and Richoderma viridis. Data are means ± SD (n = 3).
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Figure 2. Soil physicochemical properties at 30 and 60 days (soil saturation experiment). (a) pH; (b) electric conductivity; (c) organic matter; (d) total porosity; (e) water holdup; (f) alkaline phosphatase activity; (g) urease activity; (h) sucrase activity; (i) catalase activity. See Table S1 for a description of the different groups, data are means ± SD (n = 3), a, b, c, d, e, f and g show that there is a significant difference between different treatment groups (p < 0.05).
Figure 2. Soil physicochemical properties at 30 and 60 days (soil saturation experiment). (a) pH; (b) electric conductivity; (c) organic matter; (d) total porosity; (e) water holdup; (f) alkaline phosphatase activity; (g) urease activity; (h) sucrase activity; (i) catalase activity. See Table S1 for a description of the different groups, data are means ± SD (n = 3), a, b, c, d, e, f and g show that there is a significant difference between different treatment groups (p < 0.05).
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Figure 3. Soil physicochemical properties at 20, 40, and 60 days (pot experiment). (a) total porosity and water holdup; (b) organic matter and electric conductivity; (c) urease activity and alkaline phosphatase activity; (d) catalase activity and sucrase activity; (e) pH and soil bulk density; (f) soil nitrogen, phosphorus, and potassium content. See Table S1 for a description of the different groups and abbreviations, data are means ± SD (n = 3), from (ae), a, b and c represent the same treatment with significant differences at different times, while t, u, v, w, x, y and z represent the same time with significant differences at different treatments; in (f), a, b, c, d, e, f and g show that there is a significant difference between different treatment groups (p < 0.05).
Figure 3. Soil physicochemical properties at 20, 40, and 60 days (pot experiment). (a) total porosity and water holdup; (b) organic matter and electric conductivity; (c) urease activity and alkaline phosphatase activity; (d) catalase activity and sucrase activity; (e) pH and soil bulk density; (f) soil nitrogen, phosphorus, and potassium content. See Table S1 for a description of the different groups and abbreviations, data are means ± SD (n = 3), from (ae), a, b and c represent the same treatment with significant differences at different times, while t, u, v, w, x, y and z represent the same time with significant differences at different treatments; in (f), a, b, c, d, e, f and g show that there is a significant difference between different treatment groups (p < 0.05).
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Figure 4. Plant growth and physiological indicators at 20, 40, and 60 days (pot experiment). (a) plant height; (b) root length; (c) stem diameter; (d) chlorophyll content; (e) malondialdehyde content; (f) soluble sugar content. See Table S1 for a description of the different groups, data are means ± SD (n = 3), a, b and c represent the same treatment with significant differences at different times, while u, v, w, x, y and z represent the same time with significant differences at different treatments (p < 0.05).
Figure 4. Plant growth and physiological indicators at 20, 40, and 60 days (pot experiment). (a) plant height; (b) root length; (c) stem diameter; (d) chlorophyll content; (e) malondialdehyde content; (f) soluble sugar content. See Table S1 for a description of the different groups, data are means ± SD (n = 3), a, b and c represent the same treatment with significant differences at different times, while u, v, w, x, y and z represent the same time with significant differences at different treatments (p < 0.05).
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Figure 5. Differences in bacterial communities among different treatment groups (pot experiment). (a) differences in the relative abundance of bacterial communities at the phylum level; (b) relative abundance of bacterial communities at the phylum level, only the top 10 phyla in relative abundance are displayed; (c) differences in the relative abundance of bacterial communities at the genus level; (d) relative abundance of bacterial communities at the genus level, only the top 10 genera in relative abundance are displayed; (e) the petal diagram represents the core OTU level, while the UpSet plot is constructed at the species level; (f) heatmap of the relative abundance of predicted bacterial functional genes between different groups of samples. (* p < 0.05, ** p < 0.01).
Figure 5. Differences in bacterial communities among different treatment groups (pot experiment). (a) differences in the relative abundance of bacterial communities at the phylum level; (b) relative abundance of bacterial communities at the phylum level, only the top 10 phyla in relative abundance are displayed; (c) differences in the relative abundance of bacterial communities at the genus level; (d) relative abundance of bacterial communities at the genus level, only the top 10 genera in relative abundance are displayed; (e) the petal diagram represents the core OTU level, while the UpSet plot is constructed at the species level; (f) heatmap of the relative abundance of predicted bacterial functional genes between different groups of samples. (* p < 0.05, ** p < 0.01).
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Figure 6. Differences in fungal communities among different treatment groups (pot experiment). (a) differences in the relative abundance of fungal communities at the phylum level; (b) relative abundance of fungal communities at the phylum level, only the top 8 phyla in relative abundance are displayed; (c) differences in the relative abundance of fungal communities at the genus level; (d) relative abundance of fungal communities at the genus level, only the top 10 genera in relative abundance are displayed; (e) the petal diagram represents the core OTU level, while the UpSet plot is constructed at the species level.
Figure 6. Differences in fungal communities among different treatment groups (pot experiment). (a) differences in the relative abundance of fungal communities at the phylum level; (b) relative abundance of fungal communities at the phylum level, only the top 8 phyla in relative abundance are displayed; (c) differences in the relative abundance of fungal communities at the genus level; (d) relative abundance of fungal communities at the genus level, only the top 10 genera in relative abundance are displayed; (e) the petal diagram represents the core OTU level, while the UpSet plot is constructed at the species level.
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Figure 7. Redundancy analysis (RDA). (a) correlation between bacteria and soil environmental factors; (b) correlation between bacteria and plant physicochemical indicators; (c) correlation between fungi and soil environmental factors; (d) correlation between fungi and plant physicochemical indicators; (e) correlation between soil environmental factors and plant physicochemical indicators. Black arrows indicate explanatory variables, while orange arrows indicate response variables. Only the top 10 genera in relative abundance are shown.
Figure 7. Redundancy analysis (RDA). (a) correlation between bacteria and soil environmental factors; (b) correlation between bacteria and plant physicochemical indicators; (c) correlation between fungi and soil environmental factors; (d) correlation between fungi and plant physicochemical indicators; (e) correlation between soil environmental factors and plant physicochemical indicators. Black arrows indicate explanatory variables, while orange arrows indicate response variables. Only the top 10 genera in relative abundance are shown.
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Figure 8. Growth status of different crops at the field and individual levels during fruiting stage. (a) flax; (b) potato; (c) edible sunflower; (d) sorghum; (e) maize. EG–experimental group, CG–control group, the yellow dashed line represents the boundary between the aboveground and underground parts of the crop, the data in the figure show the aboveground height of different crops.
Figure 8. Growth status of different crops at the field and individual levels during fruiting stage. (a) flax; (b) potato; (c) edible sunflower; (d) sorghum; (e) maize. EG–experimental group, CG–control group, the yellow dashed line represents the boundary between the aboveground and underground parts of the crop, the data in the figure show the aboveground height of different crops.
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Table 1. Description of treatment for different groups.
Table 1. Description of treatment for different groups.
GroupTreatment
Pine needles: crushed corn cobsK1: Y1: J3
G11:11:1:1
G21:11:2:1
G31:11:1:2
G41:12:1:1
G51:12:1:2
G61:12:2:1
F11:21:1:1
F21:21:2:1
F31:21:1:2
F41:22:1:1
F51:22:1:2
F61:22:2:1
E12:11:1:1
E22:11:2:1
E32:11:1:2
E42:12:1:1
E52:12:1:2
E62:12:2:1
CMPSaline-alkali soil + F2 (microbial only) + maize
CEMSaline-alkali soil + Em + maize
COMSaline-alkali soil + Om + maize
CSPSaline-alkali soil + F2 (waste biomass only) + maize
CFPSaline-alkali soil + F2 + maize
CPSaline-alkali soil + maize
CKControl check
(Note) The ratios in the G, F, and E series are mass ratios.
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MDPI and ACS Style

Zhao, M.; Chen, X.; Liu, W.; Li, Z.; Li, W.; Yang, F.; Guo, Z.; Li, Z.; Tian, Y.; Zhang, W.; et al. Bioremediation of Saline-Alkali Soil Using a Waste Biomass-Functional Microorganism Composite Amendment and Preliminary Multi-Crop Field Validation. Microorganisms 2026, 14, 304. https://doi.org/10.3390/microorganisms14020304

AMA Style

Zhao M, Chen X, Liu W, Li Z, Li W, Yang F, Guo Z, Li Z, Tian Y, Zhang W, et al. Bioremediation of Saline-Alkali Soil Using a Waste Biomass-Functional Microorganism Composite Amendment and Preliminary Multi-Crop Field Validation. Microorganisms. 2026; 14(2):304. https://doi.org/10.3390/microorganisms14020304

Chicago/Turabian Style

Zhao, Mengmeng, Xiong Chen, Wei Liu, Ziting Li, Wangrun Li, Fanfan Yang, Zixuan Guo, Zhaoyu Li, Yongqiang Tian, Wei Zhang, and et al. 2026. "Bioremediation of Saline-Alkali Soil Using a Waste Biomass-Functional Microorganism Composite Amendment and Preliminary Multi-Crop Field Validation" Microorganisms 14, no. 2: 304. https://doi.org/10.3390/microorganisms14020304

APA Style

Zhao, M., Chen, X., Liu, W., Li, Z., Li, W., Yang, F., Guo, Z., Li, Z., Tian, Y., Zhang, W., Zhang, G., & Chen, T. (2026). Bioremediation of Saline-Alkali Soil Using a Waste Biomass-Functional Microorganism Composite Amendment and Preliminary Multi-Crop Field Validation. Microorganisms, 14(2), 304. https://doi.org/10.3390/microorganisms14020304

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