Next Article in Journal
Effects of Climatic Conditions and Agronomic Practices on Health, Tuber Yield, and Mineral Composition of Two Contrasting Potato Varieties Developed for High and Low Input Production Systems
Previous Article in Journal
Multispectral Inversion of Starch Content in Rice Grains from Yingjiang County Based on Feature Band Selection Algorithms
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 15
Issue 1
10.3390/agronomy15010087
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Effects of Salt Field Waste-Generated Bio-Organic Fertilizer Application on Bacterial Community Structure in Tea Plantations Rhizosphere Soil

by
Chengran Yu
1,2,†,
Liuting Zhou
1,2,†,
Xiaoyun Huang
1,2,
Xiaofeng You
1,2,
Jiali Lin
1,2,
Haidong Han
1,2 and
Xiusheng Huang
1,2,*
1
Institute of Resources, Environment and Soil Fertilizer, Fujian Academy of Agricultural Sciences, No. 100 Pudang, Jinan District, Fuzhou 350013, China
2
Fujian Engineering and Technology Research Center for Recycling Agriculture in Hilly Areas, Fuzhou 350013, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(1), 87; https://doi.org/10.3390/agronomy15010087
Submission received: 26 November 2024 / Revised: 25 December 2024 / Accepted: 27 December 2024 / Published: 31 December 2024
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Versions Notes

Abstract

:
This study aims to investigate the impact of salt field waste-generated bio-organic fertilizer application on the bacterial community structure within the rhizosphere soil of tea plants. After the administration of salt field waste-generated bio-organic fertilizer, the content of tea polyphenols in tea decreased, while the content of caffeine and free amino acids increased. The results showed that the dominant bacterial species in the rhizosphere soil of tea plants were Chloroflexi, Acidobacteriota, and Proteobacteria. The most dominant genus were k__Bacteria__p__Proteobacteria__c__uncultured__o__uncultured__f__uncultured__g__uncultured, k__Bacteria__p__Acidobacteriota__c__Acidobacteriae__o__Subgroup_2__f__Subgroup_2__g__Subgroup_2, k__Bacteria__p__Chloroflexi__c__AD3__o__AD3__f__AD3__g__AD3, k__Bacteria__p__Chloroflexi__c__Ktedonobacteria__o__Ktedonobacterales__f__Ktedonobacteraceae__g__HSB_OF53-F07, and g__Acidothermus. Following the application of bio-organic fertilizer, g__AD3, g__Subgroup_2, and g__HSB_OF53_F07 in the rhizosphere soil of the tea plants exhibited a decreasing trend compared to the control group. p_Proteobacteria was significantly increased, and p_Chloroflexi was considerably decreased in soils treated with bioorganic fertilizers, indicating that bio-organic fertilizers might influence the soil microbial structure in the rhizosphere soil of tea plants. Network association analyses showed a strong positive correlation between g_Candidatus_Solibacter and g_Bryobacter and a significant negative correlation between g_AD3 and g_ADurb.Bin063_1. Applying salt field waste-generated bio-organic fertilizers might effectively adjust the bacterial community structure in tea plants’ rhizosphere soil, improving the quality of tea. This study provides valuable insights into the potential benefits of utilizing bio-organic fertilizer from salt field waste in tea plantations.

1. Introduction

The tea plant (Camellia sinensis (L.) O. Kuntze) is a member of the family Theaceae and is one of the most popular beverage crops worldwide. It is a perennial woody crop with important economic value and is widely distributed in tropical and subtropical regions such as China, India, Kenya, and Sri Lanka [1]. The most used part of tea plants is their leaves, which have tea polyphenols and are extensively used in food processing [2]. Tea plantations often rely on synthetic fertilizers to enhance economic returns, leading to various environmental issues, including soil acidification, leaching risks, and loss of soil microbial diversity [3,4,5]. In recent years, environmentally friendly bio-organic fertilizers (BOF) containing a large number of beneficial microorganisms and soil-friendly organic matter have attracted attention [6,7]. Hu et al. have reported that applying BOF in tea plantations can increase the biomass of tea plants by improving soil fertility and influencing the soil bacterial function groups [8]. BOF contains a variety of non-pathogenic microflora that can increase the number and composition of beneficial microorganisms in the soil and reduce and inhibit harmful pathogens [9], which helps improve the resilience of tea trees and control plant diseases [10]. In addition to tea, BOF can also improve the soil biome structure of other crops, thereby increasing plant growth or yield. For instance, BOF primarily influences pear yields by enhancing soil chemical properties that support a beneficial plant microbiome [11]. The application of organic fertilizers, microbial fertilizers, or a combination of both can influence bacterial composition and soil metabolic processes, leading to improved growth of Dendrocalamus farinosus [12].
The increase in edible sea salt production has led to the generation of a significant amount of salt field waste, including seaweed peel, seaweed mud, calcium, magnesium, and sulfur. Research has shown that seaweed species contain essential compounds like polyphenols, polysaccharides, carotenoids, fibers, and minerals [13]. Seaweed is known for its phytostimulant properties that can improve crop growth and yields. Moreover, seaweed extracts have been found to boost plant defense mechanisms, helping plants resist pests, diseases, and environmental stresses such as drought, salinity, and cold [14]. For example, polysaccharides obtained from algae can trigger defense responses in plants and increase resistance to viral, fungal, and bacterial pathogens [15]. Extracts from Ascophyllum nodosum seaweed have been shown to enhance foliar resistance in cucumber plants against various pathogens [16]. The use of seaweed fertilizers in crop production systems is gaining popularity as an eco-friendly option. Seaweed may serve as a high-quality organic fertilizer, either applied alone or in combination with other fertilizers [17,18]. Seaweed extract positively impacts plant germination, root growth, leaf size, and soil nutrient uptake [14,19]. The application of extracts from Ascophyllum nodosum in agronomy has led to a reduction in nitrogen fertilizer usage while maintaining or improving crop productivity [20]. Collectively, salt field waste offers numerous potential applications as a biofertilizer. It not only provides essential nutrients to plants and improves the soil environment but also enhances plant stress resistance and increases crop yields. Moreover, it serves as an environmentally friendly and cost-effective agricultural resource. Therefore, salt pan waste may potentially serve as an effective BOF in tea plants.
Therefore, this study aimed to explore the effect of applying different concentrations of salt field waste-generated BOF on the bacterial community structure in tea tree root nodule soil. This work broadens the ways to utilize salt pan waste resources.

2. Materials and Methods

2.1. Study Area

The experimental area of this study is located at Mountain Tea Garden of Fuyan Tea Industry Co., LTD. in Jianyang District, Nanping City, Fujian Province (118°0′6″ E, 27°21′35″ N). The base is located in the humid subtropical monsoon climate zone with an average altitude of 279 m. The experimental tea tree variety is Qidan Tea, five years old. The experimental area has a sandy loam soil texture. Physico-chemical properties were as follows: pH 5.60, organic matter: 35.70 g·kg−1, total nitrogen: 1.75 g·kg−1, total phosphorus: 0.95 g·kg−1, total potassium: 7.23 g·kg−1, alkali dissolved nitrogen (ADN): 174.06 mg·kg−1, quick-acting phosphorus (QAP): 76.30 mg·kg−1, and quick-acting potassium (K): 266.01 mg·kg−1.
Four different fertilization methods were carried out in the plantations: No fertilizer control (CK), 0.15 kg/m2 bio-organic fertilizer treatment (BOF1), 0.30 kg/m2 bio-organic fertilizer treatment (BOF2), and 0.45 kg/m2 bio-organic fertilizer treatment (BOF3). Soil and tea samples were collected approximately three months after the fertilization treatments. The pH of the salt field waste-generated BOF was 8.7, and the composition of the salt field waste-generated BOF was organic matter (18%), total N (0.49%), total P (0.18%), total K (1.18%), total nutrients (1.85%), elemental calcium (7.14%), elemental magnesium (2.36%), elemental sulfur (0.73%), chloride ion (1.51%), and protein (4%).

2.2. Determination of Total Polyphenols Content in Tea

The tea sample was ground into a fine powder, and 0.2 g was weighed and placed in a test tube. Subsequently, 5 mL of a 70% methanol aqueous solution was added. The mixture was stirred thoroughly and placed in a water bath at 70 °C for 10 min for extraction. Following this, centrifugation was performed at 3500 rpm for 10 min to collect the supernatant. The residue was then treated with an additional 10 mL of the extraction solution and subjected to extraction in the 70 °C water bath for another 10 min. After centrifugation, the supernatant was collected and combined with the previously obtained supernatant, which was then diluted to a final volume of 10 mL. The extract was filtered using a 0.45 μm membrane and prepared for high-performance liquid chromatography (HPLC) analysis. For this study, a high-performance liquid chromatograph equipped with a C8 column (5 μm, 250 mm × 4.6 mm) was utilized. The HPLC conditions were established as follows: mobile phase A consisted of 9% acetonitrile and 2% acetic acid in aqueous solution, while mobile phase B comprised 80% acetonitrile and 2% acetic acid in aqueous solution. The mobile phase flow rate was set to 1 mL/min, and the column temperature was maintained at 35 °C.

2.3. Determination of Water Extract Content in Tea

Weigh 2.00 g (to the nearest 0.001 g) of tea powder into a 500 mL conical flask, add 300 mL of boiling distilled water, and steep for 45 min in a boiling water bath (shaking every 10 min). Then filter under reduced pressure while hot and wash the tea residue several times with 150 mL of boiling distilled water, transfer the tea residue with a known mass of filter paper to a baking dish and then dry in a thermostatic drying oven at 120 °C ± 2 °C for 1 h. Remove the lid, cool for 1 h, and then bake for another 1 h. Then, immediately transfer to a desiccator, cool to room temperature, and then weigh. The content of the water extract was calculated using the following formula:
W a t e r   e x t r a c t % = ( 1 − m 1 m 0 × W )   ×   100 %
  • m0—mass of specimen (g).
  • m1—Mass of tea residue after drying (g).
  • w—Content of dry matter of specimen (%).

2.4. Determination of Caffeine Content in Tea

Weigh 1.00 g (accurate to 0.0001 g) of tea powder into a 500 mL flask, add 4.5 g of magnesium oxide and 300 mL of boiling water, and leach in a boiling water bath for 20 min (shaking every 5 min). Then, filter under reduced pressure, transfer the filtrate to a 500 mL volumetric flask, and cool and mix well with water. A portion of the test solution was filtered through a 0.45 μm membrane filter and prepared for high-HPLC analysis. For this study, a high-performance liquid chromatograph equipped with a C18 column (5 μm, 250 mm × 4.6 mm) was utilized. The HPLC conditions were established as follows: mobile phase: 30% aqueous methanol solution, flow rate: 0.5 mL/min~1.5 mL/min, column temperature: 40 °C, sample volume: 10 μL, and UV wavelength: 280 nm.

2.5. Determination of Free Amino Acid Content in Tea

Weigh 3.00 g of tea powder into a 500 mL Erlenmeyer flask. Add 450 mL of boiling distilled water and extract in a boiling water bath for 45 min, shaking every 10 min. Then, filter the mixture under reduced pressure and wash the residue 2 to 3 times with a small volume of hot distilled water. Transfer the filtrate into a 500 mL volumetric flask, allow it to cool, and dilute to 500 mL with water, ensuring thorough mixing.
Accurately pipette 1 mL of the test solution into a 25 mL colorimetric tube. Then, add 0.5 mL of pH 8.0 phosphate buffer and 0.5 mL of a 2% ninhydrin solution. Heat the mixture in a boiling water bath for 15 min. After cooling, dilute the solution with water to a final volume of 25 mL. Allow the solution to stand for 10 min before measuring the absorbance at 570 nm using a 5 mm cuvette, with the reagent blank solution serving as a reference.

2.6. Soil Sampling and Analysis

All soil samples were randomly collected from 15 tea plants in each experimental area. Tea tree root soil was collected from a depth of 20 cm in a sterile 50 mL tube using a disinfected spade and spoon. Next, the surface covering soil was removed layer by layer, fine root branches of the tea plants were cut, and the soil around the roots (1–2 cm) was collected using an aseptic spoon. Rhizosphere soil from tea plants close to the surface of fine roots was collected into sterile bags and quickly frozen in liquid nitrogen. Five samples were randomly selected from the 15 rhizosphere soils obtained in each experimental area and mixed to obtain three replicate soil samples. Finally, we obtained a total of 12 soil samples from the four experimental areas, and at least 15 inter-root soil samples of tea plants were collected from each treatment group. Soil samples are passed through a 2 mm sieve to remove fine roots, gravel, and contaminants, then divided into two parts and stored in sterile bags. A portion of the sample was freeze-dried to measure soil properties, and the remainder was stored at −80 °C and shipped in dry ice to the laboratory, where the high-throughput sequencing analysis was performed.

2.7. DNA Extraction and Library Construction

Genomic DNA was extracted from soil samples using the EZNA Soil DNA Kit (Omega Bio-tek, Inc., Norcross, GA, USA) following the manufacturer’s instructions. The quality and concentration of DNA were assessed with a Nanodrop 2000 (ThermoFisher Scientific, Inc., Waltham, MA, USA), and the DNA samples were stored at −20 °C for future experiments. The V3-V4 region of the bacterial 16S rRNA gene was amplified using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). An 8 bp barcode sequence was added to the 5′ ends of both primers to differentiate between samples. Universal primers with barcode sequences were amplified on an ABI 9700 PCR machine (Applied Biosystems, Inc., Framingham, MA, USA) with the following program: Pre-denaturation at 95 °C for 5 min, 28 cycles of denaturation at 95 °C for 45 s, annealing at 55 °C for 50 s, and extension at 72 °C for 45 s. A final extension was done at 72 °C for 10 min, followed by storage at 4 °C. Amplicon quality was checked using 1% agarose gel electrophoresis and purified with the Agencourt AMPure XP (Beckman Coulter, Inc., Chaska, MN, USA). For library construction, amplicon libraries were prepared with the NEB Next Ultra II DNA Library Prep Kit (New England Biolabs, Inc., Beverly, MA, USA) according to the manufacturer’s instructions and further purified with the Agencourt AMPure XP kit (Beckman Coulter, Inc., Chaska, MN, USA). Library concentration was determined using Nanodrop 2000 (ThermoFisher Scientific, Inc., USA), and library fragment size was determined using an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA). In addition, the library concentration was determined using the ABI StepOnePlus real-time PCR system (Applied Biosystems, Inc., Framingham, MA, USA). Finally, DNA samples were sequenced using the Illumina PE300 high-throughput sequencing platform at Beijing Allwegene Technology Co., Ltd (Beijing, China).

2.8. Data Analysis

Use barcode sequences to split sequence data into different samples. Data were filtered and combined using Pear Software [21] (v0.9.6) to remove sequences with ambiguous N bases or quality scores less than 20. The minimum overlap during splicing was set to 10 bp, with a p-value of 0.0001. The Vsearch software (v2.7.1) [22] was utilized to eliminate sequences with a length of less than 230 bp, and the uchime method [23] was employed to align and remove chimeric sequences based on the Gold Database.
Sequences were grouped into operational taxonomic units (OTUs) using the Uparse algorithm [24] of VSEARCH software (v2.7.1) [22]. The threshold for sequence similarity is 97%. The representative OTU sequences were then compared with the Silva138 database through the BLAST algorithm [25,26]. The α diversity index was computed based on the OTUs and their abundance results using QIIME (v1.8.0) [27] software.

2.9. Linear Discriminant Analysis Effect Size (LEfSe) Analysis

LEfSe analysis was performed on the BOF1, BOF2, BOF3, and CK groups, with a threshold for the LDA score set at 3 to identify species exhibiting significant differences in abundance among the groups, utilizing Python (v2.7) software [28].

2.10. Statistical Analysis

The R language (version 4.0.2) was used to conduct principal coordinates analysis (PCoA). PCoA analysis is a non-binding data dimensionality reduction analysis method that can be used to study the similarities or differences in sample community composition. The Wilcoxon rank sum test was employed to compare differences in various indicators across different groups. The limma function package (version 3.56.2) was applied to identify differential species between the two groups based on the p < 0.05 [29]. The igraph and psych function packages were used to calculate the Spearman correlation coefficient; the correlation network diagram was filtered and plotted based on the adjusted p < 0.05 after the Benjamini-Hochberg correction. All statistical analysis was performed using the R language.

3. Results

3.1. Effect of Salt Field Waste-Generated-BOF Treatment on the Quality of Tea Leaves

First, we analyzed the content of tea polyphenols, water extract (water-soluble substances in tea leaves), caffeine, and free amino acids in tea leaves after three months of applying BOF. We found that after administration of BOF3, the tea polyphenol content in tea decreased by 1.30%, while the caffeine and free amino acid content increased by 1% and 0.2%, respectively, compared with the CK group (Figure 1).

3.2. The α Diversity Analysis of Soil Bacterial Communities

The α diversity index was utilized to assess the diversity of soil bacterial communities in BOF1, BOF2, BOF3, and CK groups. The α diversity measures species diversity within a particular area or ecosystem as a holistic indicator of species richness and evenness. As shown in Figure 2A, soil bacterial alpha diversity, indicated by Shannon, was not significantly different among the BOF1, BOF2, BOF3, and CK groups. The Good’s coverage index was significantly decreased in the BOF3 group compared to the CK group (Figure 2B).

3.3. Compositional Analysis of Soil Bacterial Communities

At the phylum level (Figure 3), the top five dominant bacterial species of all samples were p__Chloroflexi (26.1~42.0%), p__Acidobacteriota (19.2~26.1%), p__Proteobacteria (16.7~23.9%), p__Actinobacteriota (8.5~9.3%), and p__Verrucomicrobiota (1.7~4.4%). p__Chloroflexi was the most abundant species, followed by p__Acidobacteriota and p__Proteobacteria. Compared to the CK group, the relative abundances of p__Chloroflexi in the BOF1, BOF2, and BOF3 groups were observably reduced by 16.6%, 14%, and 15.7%, respectively.
At the genus level (Figure 4), the top five dominant bacteria genera in all rhizospheric soils of all samples were g__uncultured (19.8~29.7%), g__Subgroup_2 (4.9~11.1%), g__AD3 (5.5~11.8%), g__HSB_OF53_F07 (4.2~10.5%), and g__Acidothermus (4.0~6.5%). Other major genera were g__1921-2 (2.7~4.0%), g__Candidatus__Solibacter (2.2~3.9%), and g__FCPS473 (1.7~6.1%). Furthermore, a higher proportion of Bradyrhizobium was found in the BOF1 (2.2%), BOF2 (2.2%), and BOF3 (2.2%) groups. Compared with the CK group, the application of BOF1, BOF2, and BOF3 led to an increase in the number of uncultured bacteria in the rhizosphere soil of the tea plants. The increase was observed to be 9%, 8.6%, and 6%, respectively. Following the application of BOF, g__AD3, g__Subgroup_2, and g__HSB_OF53_F07 in the rhizosphere soil of tea plants exhibited a decreasing trend compared to the CK group. Specifically, after the application of 0.15 kg/m2, 0.30 kg/m2, and 0.45 kg/m2 of BOF, the relative abundance of g__AD3 decreased by 6.3%, 5.9%, and 3.5%, respectively. Similarly, the relative abundance of g__Subgroup_2 decreased by 4.2%, 2.2%, and 6.2%, respectively, while the relative abundance of g__HSB_OF53_F07 decreased by 6.1%, 5.8%, and 6.3%, respectively.

3.4. Heatmap, Clustering, and PCoA of Soil Bacteria in the Rhizosphere of Tea Tree

The heatmap and clustering analysis of the top 20 species at the phylum and genus levels were depicted in Figure 5A and Figure 5B, respectively. The results demonstrated the variations in bacterial composition in the soil at the rhizosphere soil of tea plants following the application of BOF. Through OTU annotation and subsequent PCoA analysis, it was observed that the distance between the CK group and the BOF was farther, indicating that the microbial composition difference between the CK group and the BOF group was greater (Figure 5C), indicating a discernible clustering of microbiota composition between CK and BOF groups. The ordination axis accounted for approximately 56.38% of the variability. These results indicated that BOF might influence the soil microbial structure in the rhizosphere soil of tea plants.

3.5. Comparison of Bacterial Community Composition Among the Different Treatments

The analysis utilized Linear Discriminant Analysis (LDA) to examine variations in bacterial makeup across various fertilization scenarios. According to Figure 6, over 95 bacterial populations displayed LDA scores surpassing 3 in the four groups. Significant phylogenetic variances in bacterial communities were observed across various taxonomic hierarchies. Notably, 42 communities were derived from soil samples exposed to 0.45 kg/m2 BOF treatment. Moreover, at the family level, f__Subgroup 2 in the CK group, f__Microscillaceae in the BOF3 group, and f__Xanthobacteraceae in the BOF2 group exhibited LDA scores exceeding 4. At the order level, o__Subgroup 2 in the CK group, o__Cytophagales in the BOF3 group, and o__Rhizobiales in the BOF2 group had LDA scores exceeding 4. At the genus level, the LDA score of g__FCPS473 and g__Subgroup 2 in the CK group was greater than 4. Moreover, p Chloroflexi in the CK group and c__Gammaproteobacteria, p__Bacteroidota, and c__Bacteroidia in the BOF3 group exhibited LDA scores exceeding 4.

3.6. Taxonomic Biomarkers

To further investigate which taxa served as biomarkers among the groups, we applied LEfSe to explore the bacterial community’s significant changes and relative richness. The enrichment characteristics of some bacterial community groups in the taxonomic hierarchy from domain to species were substantial. There were 4 biomarkers (2 orders and 2 families), 14 biomarkers (3 classes, 5 orders, and 6 families), 13 biomarkers (1 class, 5 orders, and 7 families), and 24 biomarkers (3 Class 11, order 10 families) in the soil treated with 0 kg/m2, 0.15 kg/m2, 0.30 kg/m2, and 0.45 kg/m2 BOF, respectively (Figure 7).
In addition, there were significant differences in biomarkers between the CK group and the BOF1, BOF2, and BOF3 groups (Table S1). Compared to the CK group, 220 bacterial genera decreased in the BOF1 group while 40 bacterial genera increased (Figure 8A). The BOF2 group saw a significant increase in 186 bacterial genera and a decrease in 36 bacterial genera (Figure 8B, BOF2 vs. CK). Additionally, 399 bacterial genera were significantly increased in the T3 group, while 48 were significantly reduced (Figure 8C, BOF3 vs. CK). Noteworthy, p_Proteobacteria was significantly increased, and p_Chloroflexi was considerably decreased in the BOF1, BOF2, and BOF3 groups compared to the CK group.

3.7. Network Associations Among Bacterial Communities

The top 30 bacterial genera with absolute abundance in all samples were used to construct a network (Figure 9). The network comprised 54 important associations (edges) connecting 29 nodes, with 38 positive links and 16 negative links. The size of each node was directly proportional to its abundance. The top 10 taxa with a high number of interactions were g_HSB_OF53_F07 (8 links), g_FCPS473 (7 links), g_Subgroup_2 (7 links), g_BacC_u_018 (6 links), g_Pedosphaeraceae (6 links), g_Acidothermus (5 links), g_ADurb.Bin063_1 (5 links), g_Burkholderi_Caballeronia_Paraburkholderia (5 links), g_Candidatus Udaeobacter (5 links), and g_Pajaroellobacter (5 links). The results also revealed a strong positive correlation between g_Candidatus_Solibacter and g_Bryobacter (r = 0.902097902, p < 0.05, Table S2) and a significant negative correlation between g_AD3 and g_ADurb.Bin063_1 (r = −0.839160839, p < 0.05, Table S2).

4. Discussion

Soil microorganisms decompose soil organic matter, regulate carbon storage and nutrient cycling, and play a crucial role in ecosystem functions such as enhancing plant nutrient uptake [30,31]. As a result, soil microorganisms have become commonly utilized indicators in assessing soil quality. This study discovered that after the administration of BOF, the content of tea polyphenols in tea decreased, while the content of caffeine and free amino acids increased. Moreover, BOF treatment enhanced the diversity of microorganisms in the rhizosphere soil of tea plants. These results indicated that BOF may affect the diversity of tea rhizosphere soil microorganisms and improve tea quality. Our results also showed that the goods coverage index was observably decreased in BOF3 treatment compared to CK treatment. The goods coverage index reflects the sequencing coverage of microbial communities; the notable decrease in the goods coverage index following BOF treatment suggested that applying BOF might have led to a reduction or disappearance of certain microbial communities or the emergence of new, undetected ones. Organic amendments enhance soil microbial biomass and activity by boosting organic matter and nutrient availability; however, certain components within organic amendments might exert inhibitory effects on particular microbial populations [32,33,34]. Organic fertilizers are rich in beneficial microorganisms. These microorganisms compete with pathogenic microorganisms for habitat and resources, thereby playing an antagonistic role. Additionally, they can produce substances that inhibit the growth of pathogenic microorganisms [35]. Research indicates that the application of BOF supplies microorganisms with essential carbon sources, nitrogen sources, and other nutrients, which fosters their growth and reproduction while optimizing the structure and function of soil microbial communities [35]. Salt field waste-generated BOF contains minerals such as nitrogen, phosphorus, potassium, calcium, magnesium, and sulfur. Thus, the application of salt field waste-generated BOF has the potential to enhance the nutrient content in the rhizosphere soil of tea trees, improve the structure and function of soil microbial communities, improve the soil environment, and ultimately enhance the quality of tea.
The dominant bacterial phyla in CK and BOF rhizospheric soil were p__Chloroflexi, p__Acidobacteriota, and p__Proteobacteria, which were consistent with published reports [36,37,38]. It has been reported that Proteobacteria, Actinobacteria, Chloroflexi, Acidobacteriota, and Firmicutes accounted for approximately 96.00% of the bacterial phyla in the bulk soil of a tea garden [39]. Chen et al. have reported that tea rhizosphere bacterial communities are often enriched in members of Proteobacteria, Firmicutes, and Acidobacteria [40]. Moreover, previous studies have shown that Chloroflexi and Proteobacteria were significantly enriched or increased in acidified soil [41]. Chloroflexi plays a nitrification or denitrification function in soil N-cycle [41,42]. The prevalence of Acidobacteria in tea garden soil increases with the age of the tea trees [43], highlighting the significance of Acidobacteria in crucial ecological processes like regulating biogeochemical cycles and promoting growth in tea gardens [44]. Proteobacteria play a key role in ammonia oxidation and nitrification processes [45,46] and actively participate in nitrogen transformation within the soil [47]. Therefore, the dominance of Proteobacteria in tea plantation soils might be related to their functions in carbon and nitrogen cycles.
BOF may supply a variety of essential nutrients for tea trees while enhancing the soil environment, which may indirectly influence the production of plant hormones. For instance, the organic matter and microbial activity present in BOF may stimulate the roots of tea trees to secrete increased levels of hormones such as auxin and cytokinin, thereby promoting their growth and development [48]. The application of BOF can elevate the organic matter content in the soil, potentially altering the composition and quantity of root exudates from tea trees, which in turn affects the interactions between tea trees and rhizosphere microorganisms [49]. An increase in organic matter may encourage tea tree roots to secrete additional organic compounds, thus providing more energy and nutrients for rhizosphere microorganisms. Furthermore, the use of BOF may indirectly influence root nodule microbiota by raising soil pH and enhancing nutrient availability, which promotes the uptake of nitrogen, potassium, and magnesium by tea trees, ultimately improving their photosynthetic efficiency [50]. Thus, we hypothesized that the salt field waste-generated BOF may stimulate the production of phytohormones by changing the soil environment and providing nutrients, thereby affecting tea tree root exudates and the root nodule microbial community structure. However, the specific extent and mechanism of the effects may require further experimental studies to clarify.
Seaweed extract is said to improve plant defense mechanisms, helping plants resist pests, disease, and environmental stresses such as drought, salinity, and cold [14]. For example, algae-derived polysaccharides can induce plant defense responses and enhance resistance to viral, fungal, and bacterial pathogens [15]. The application of bioorganic fertilizers may also enhance soil enzyme activities, including leucine aminopeptidase, β-glucosidase, β-N-acetylglucosaminidase, soil acid phosphatase, β-cellobiosidase, and β-xylanase [51]. The observed increase in the activity of these enzymes may be associated with alterations in the soil microbial community, as most of these enzymes are produced by microorganisms, and their activities can serve as indicators of the metabolic activities within the microbial community [51]. Therefore, the application of salt field waste-generated BOF may enhance the defense mechanism of tea plants by increasing soil enzyme activity and may affect the structure and function of the rhizosphere microbiota. However, the specific extent and mechanism of the effect may require further experimental studies to clarify.
Following the application of BOF, there was a significant decrease in the relative abundance of Chloroflexi. Chloroflexi, commonly known as heterotrophic oligotrophs and facultative anaerobic bacteria, are sensitive to soil pH and thrive best at neutral pH [52]. Research indicates that alkaline substances, such as biochar, can neutralize H+ ions in the soil, increase soil cation exchange capacity (CEC), and enhance the content of salt-based substances. These effects contribute to improved soil buffering against acidity, thereby raising the pH value of acidified soils [53]. Additionally, salt field waste-generated BOF has a high pH and might improve acidic soil that could exert similar effects. The application of salt field waste may impact the living environment and metabolic activities of microorganisms, such as Chloroflexi, by altering the pH of tea tree soil and introducing new carbon sources, thereby leading to changes in their population numbers. Furthermore, the heatmap, cluster analysis, and PCoA analysis showed that BOF might influence the soil microbial structure in the rhizosphere soil of tea plants. LDA showed a difference in bacterial composition under different fertilization conditions. LEfSe analysis revealed that there were significant differences in biomarkers between the CK group and the BOF1, BOF2, and BOF3 groups, and the biomarker P. Proteobacteria was significantly increased, and P. Chloroflexi was considerably decreased in the BOF groups compared to the CK group. Proteobacteria is frequently associated with nitrogen transformations, particularly nitrogen fixation and nitrification processes [54,55]. An increase in Proteobacteria may enhance nitrogen availability in the soil, thereby promoting the growth and yield of tea plants. Strains within the phylum Proteobacteria may also facilitate the release of other essential nutrients, such as phosphorus and potassium, which support the uptake by tea trees [56]. Additionally, Proteobacteria can decompose organic matter and enhance the mineralization of carbon, resulting in the release of carbon dioxide [57]. This process may influence the soil’s capacity to sequester carbon and provide the energy and nutrients necessary for plant growth. Furthermore, research indicates that Proteobacteria may possess the ability to degrade carbohydrates and proteins, thereby participating in carbon and energy cycles [58]. Salt field waste-generated BOF application in tea plants might increase P. proteobacteria to impact the carbon and nutrient cycling of tea trees. Further research into the mechanisms and consequences of these changes will aid in optimizing the cultivation and management of tea trees.
The results of the network association analysis revealed a strong positive correlation between g_Candidatus_Solibacter and g_Bryobacter. The g_Bryobacter and g_Candidatus_Solibacter belong to the phylum Acidobacteria and can decompose organic matter and promote the carbon cycle [59]. The relative abundance of Candidatus_Solibacter and Bryobacter increased significantly overall in soils with higher nitrogen deposition [60]. The increase in Candidatus_Solibacter and Bryobacter observed may promote the complete decomposition of organic carbon, thereby reducing the organic carbon content in the soil [60]. The relative abundance of Candidatus Solibacter and Bryobacter decreased with the increase in soil erosion depths [61]. Severe soil erosion changes soil organic carbon and nutrient content through raindrops, soil leaching, and related sediment transport and deposition processes, indirectly affecting soil nutrient cycling and plant fertility [62,63]. In addition, the elevated CO2 was correlated with increased relative abundances of the genera Bryobacter and Candidatus_Solibacter in soil [64]. Wang et al. investigated the alterations in dominant bacterial genera in soil resulting from acid rain and exogenous nitrogen input and discovered that the genera Bryobacter and Candidatus_Solibacter exhibited a trend of initially increasing followed by a subsequent decrease [65]. Thus, we hypothesized that BOF treatment may regulate the relative abundances of cyanobacteria and silver-green algae in the rhizosphere soil of tea trees, thereby promoting soil nutrient cycling. This hypothesis necessitates further research.

5. Conclusions

The application of salt field waste-generated BOF significantly impacts the tea plant’s rhizosphere soil microbial community and the quality of tea produced. This study revealed that the use of this fertilizer led to a decrease in tea polyphenols and an increase in caffeine and free amino acids in tea leaves. The dominant bacterial phyla in the rhizosphere soil were identified as Chloroflexi, Acidobacteriota, and Proteobacteria, with uncultured genera being the most prevalent. Post-application of the BOF, there was a notable decrease in the abundance of AD3, Subgroup_2, and HSB_OF53_F07 compared to the control group, suggesting a shift in the microbial community structure. Additionally, the phylum Proteobacteria increased significantly, while Chloroflexi decreased considerably in the treated soils, indicating that BOF may alter the soil microbial composition in the rhizosphere of tea plants. In conclusion, this study examines the impact of BOF on the soil microbial community structure of tea tree root nodules, offering valuable insights into the growth conditions of tea trees and providing insights into the potential benefits of utilizing BOF from salt field waste in tea plantations. However, the specific mechanism of salt field waste-generated BOF in regulating the microbial structure of tea tree inter-root soil remains unclear. Future studies could also investigate the potential mechanisms of these changes in the microbial structure of tea tree soils due to BOF application in order to improve soil management practices and tea tree cultivation strategies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15010087/s1, Table S1: The differences in biomarkers between the CK group and the BOF1, BOF2, and BOF3 groups; Table S2: The results of the network association analysis.

Author Contributions

C.Y.: Conceptualization, data curation, formal analysis, investigation, methodology, validation, visualization, and writing—original draft; L.Z.: Conceptualization, data curation, formal analysis, investigation, methodology, validation, and visualization; X.H. (Xiaoyun Huang): Data curation, formal analysis, investigation, validation, and visualization; X.Y.: Data curation, formal analysis, validation, and visualization; J.L.: Data curation, formal analysis, validation, and visualization; H.H.: Resources, supervision, and writing—review and editing; X.H. (Xiusheng Huang): Project administration, resources, and supervision. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Special Fund for Scientific Research on Public Causes of Fujian Province (2023R1019002, 2020R1021004), and “5511” Collaborative Innovation Project of People’s Government of Fujian Province and Chinese Academy of Agricultural Sciences (XTCXGC2021010).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data supporting the conclusion of this study are openly available from the SRA database with the reference number (PRJNA1137571) in the following link [https://www.ncbi.nlm.nih.gov/sra/PRJNA1137571].

Conflicts of Interest

The authors report no conflicts of interest.

References

  1. Mukhopadhyay, M.; Mondal, T.K.; Chand, P.K. Biotechnological advances in tea (Camellia sinensis [L.] O. Kuntze): A review. Plant Cell Rep. 2016, 35, 255–287. [Google Scholar] [CrossRef] [PubMed]
  2. Xue, H.; Tu, Y.; Zhang, G.; Xin, X.; Hu, H.; Qiu, W.; Ruan, D.; Zhao, Y. Mechanism of ultrasound and tea polyphenol assisted ultrasound modification of egg white protein gel. Ultrason. Sonochem. 2021, 81, 105857. [Google Scholar] [CrossRef] [PubMed]
  3. Ni, K.; Shi, Y.; Yi, X.; Zhang, Q.; Fang, L.; Ma, L.; Ruan, J. Effects of long-term nitrogen application on soil acidification and solution chemistry of a tea plantation in China. Agric. Ecosyst. Environ. 2018, 252, 74–82. [Google Scholar] [CrossRef]
  4. Yan, P.; Wu, L.; Wang, D.; Fu, J.; Shen, C.; Li, X.; Zhang, L.; Zhang, L.; Fan, L.; Wenyan, H. Soil acidification in Chinese tea plantations. Sci. Total Environ. 2020, 715, 136963. [Google Scholar] [CrossRef]
  5. Ji, L.; Wu, Z.; You, Z.; Yi, X.; Ni, K.; Guo, S.; Ruan, J. Effects of organic substitution for synthetic N fertilizer on soil bacterial diversity and community composition: A 10-year field trial in a tea plantation. Agric. Ecosyst. Environ. 2018, 268, 124–132. [Google Scholar] [CrossRef]
  6. Liu, T.; Wang, S.; Chen, Y.; Luo, J.; Hao, B.; Zhang, Z.; Yang, B.; Guo, W. Bio-organic fertilizer promoted phytoremediation using native plant leymus chinensis in heavy Metal(loid)s contaminated saline soil. Environ. Pollut. 2023, 327, 121599. [Google Scholar] [CrossRef] [PubMed]
  7. Sun, L.; Wang, Y.; Ma, D.; Wang, L.; Zhang, X.; Ding, Y.; Fan, K.; Xu, Z.; Yuan, C.; Jia, H.; et al. Differential responses of the rhizosphere microbiome structure and soil metabolites in tea (Camellia sinensis) upon application of cow manure. BMC Microbiol. 2022, 22, 55. [Google Scholar] [CrossRef]
  8. Hu, Z.; Ji, L.; Wan, Q.; Li, H.; Li, R.; Yang, Y. Short-Term Effects of Bio-Organic Fertilizer on Soil Fertility and Bacterial Community Composition in Tea Plantation Soils. Agronomy 2022, 12, 2168. [Google Scholar] [CrossRef]
  9. Tao, C.; Li, R.; Xiong, W.; Shen, Z.; Liu, S.; Wang, B.; Ruan, Y.; Geisen, S.; Shen, Q.; Kowalchuk, G.A. Bio-organic fertilizers stimulate indigenous soil Pseudomonas populations to enhance plant disease suppression. Microbiome 2020, 8, 137. [Google Scholar] [CrossRef]
  10. Huang, Y.; Fang, X.; Sui, M.; Jiang, G.; Xiao, J.; Wang, W.; Ning, Y. Situation and prospect of studying tea microorganisms. J. Huazhong Agric. Univ. 2022, 41, 24–32. [Google Scholar]
  11. Wang, Z.; Yang, T.; Mei, X.; Wang, N.; Li, X.; Yang, Q.; Dong, C.; Jiang, G.; Lin, J.; Xu, Y.; et al. Bio-Organic Fertilizer Promotes Pear Yield by Shaping the Rhizosphere Microbiome Composition and Functions. Microbiol. Spectr. 2022, 10, e0357222. [Google Scholar] [CrossRef]
  12. Li, S.; Fan, W.; Xu, G.; Cao, Y.; Zhao, X.; Hao, S.; Deng, B.; Ren, S.; Hu, S. Bio-organic fertilizers improve Dendrocalamus farinosus growth by remolding the soil microbiome and metabolome. Front. Microbiol. 2023, 14, 1117355. [Google Scholar] [CrossRef]
  13. Ummat, V.; Tiwari, B.K.; Jaiswal, A.K.; Condon, K.; Garcia-Vaquero, M.; O’Doherty, J.; O’Donnell, C.; Rajauria, G. Optimisation of Ultrasound Frequency, Extraction Time and Solvent for the Recovery of Polyphenols, Phlorotannins and Associated Antioxidant Activity from Brown Seaweeds. Mar. Drugs 2020, 18, 250. [Google Scholar] [CrossRef]
  14. Ali, O.; Ramsubhag, A.; Jayaraman, J. Biostimulant Properties of Seaweed Extracts in Plants: Implications towards Sustainable Crop Production. Plants 2021, 10, 531. [Google Scholar] [CrossRef] [PubMed]
  15. Hernández-Herrera, R.M.; Virgen-Calleros, G.; Ruiz-López, M.; Zañudo-Hernández, J.; Délano-Frier, J.P.; Sánchez-Hernández, C. Extracts from green and brown seaweeds protect tomato (Solanum lycopersicum) against the necrotrophic fungus Alternaria solani. J. Appl. Phycol. 2014, 26, 1607–1614. [Google Scholar] [CrossRef]
  16. Jayaraman, J.; Norrie, J.; Punja, Z.K. Commercial extract from the brown seaweed Ascophyllum nodosum reduces fungal diseases in greenhouse cucumber. J. Appl. Phycol. 2011, 23, 353–361. [Google Scholar] [CrossRef]
  17. Najafi Vafa, Z.; Sohrabi, Y.; Mirzaghaderi, G.; Heidari, G. Soil Microorganisms and Seaweed Application With Supplementary Irrigation Improved Physiological Traits and Yield of Two Dryland Wheat Cultivars. Front. Plant Sci. 2022, 13, 855090. [Google Scholar] [CrossRef]
  18. Tursun, A.O. Effect of foliar application of seaweed (organic fertilizer) on yield, essential oil and chemical composition of coriander. PLoS ONE 2022, 17, e0269067. [Google Scholar] [CrossRef] [PubMed]
  19. Ali, O.; Ramsubhag, A.; Jayaraman, J. Biostimulatory activities of Ascophyllum nodosum extract in tomato and sweet pepper crops in a tropical environment. PLoS ONE 2019, 14, e0216710. [Google Scholar] [CrossRef]
  20. Goni, O.; Langowski, L.; Feeney, E.; Quille, P.; O’Connell, S. Reducing Nitrogen Input in Barley Crops While Maintaining Yields Using an Engineered Biostimulant Derived From Ascophyllum nodosum to Enhance Nitrogen Use Efficiency. Front. Plant Sci. 2021, 12, 664682. [Google Scholar] [CrossRef]
  21. Zhang, J.; Kobert, K.; Flouri, T.; Stamatakis, A. PEAR: A fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 2014, 30, 614–620. [Google Scholar] [CrossRef] [PubMed]
  22. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahe, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 2016, 4, e2584. [Google Scholar] [CrossRef]
  23. Edgar, R.C.; Haas, B.J.; Clemente, J.C.; Quince, C.; Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011, 27, 2194–2200. [Google Scholar] [CrossRef] [PubMed]
  24. Edgar, R.C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 2013, 10, 996–998. [Google Scholar] [CrossRef] [PubMed]
  25. Pruesse, E.; Quast, C.; Knittel, K.; Fuchs, B.M.; Ludwig, W.; Peplies, J.; Glockner, F.O. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007, 35, 7188–7196. [Google Scholar] [CrossRef] [PubMed]
  26. Ye, J.; McGinnis, S.; Madden, T.L. BLAST: Improvements for better sequence analysis. Nucleic Acids Res. 2006, 34, W6–W9. [Google Scholar] [CrossRef] [PubMed]
  27. Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.D.; Costello, E.K.; Fierer, N.; Pena, A.G.; Goodrich, J.K.; Gordon, J.I.; et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 7, 335–336. [Google Scholar] [CrossRef]
  28. Segata, N.; Izard, J.; Waldron, L.; Gevers, D.; Miropolsky, L.; Garrett, W.S.; Huttenhower, C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011, 12, R60. [Google Scholar] [CrossRef]
  29. Ritchie, M.E.; Phipson, B.; Wu, D.; Hu, Y.; Law, C.W.; Shi, W.; Smyth, G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015, 43, e47. [Google Scholar] [CrossRef]
  30. Delgado-Baquerizo, M.; Reich, P.B.; Trivedi, C.; Eldridge, D.J.; Abades, S.; Alfaro, F.D.; Bastida, F.; Berhe, A.A.; Cutler, N.A.; Gallardo, A.; et al. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 2020, 4, 210–220. [Google Scholar] [CrossRef]
  31. van der Heijden, M.G.; Bardgett, R.D.; van Straalen, N.M. The unseen majority: Soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 2008, 11, 296–310. [Google Scholar] [CrossRef]
  32. Insam, H.; Gómez-Brandón, M.; Ascher, J. Manure-based biogas fermentation residues—Friend or foe of soil fertility? Soil Biol. Biochem. 2015, 84, 1–14. [Google Scholar] [CrossRef]
  33. Tang, Y.; Luo, L.; Carswell, A.; Misselbrook, T.; Shen, J.; Han, J. Changes in soil organic carbon status and microbial community structure following biogas slurry application in a wheat-rice rotation. Sci. Total Environ. 2021, 757, 143786. [Google Scholar] [CrossRef] [PubMed]
  34. Cao, Y.; Wang, J.; Wu, H.; Yan, S.; Guo, D.; Wang, G.; Ma, Y. Soil chemical and microbial responses to biogas slurry amendment and its effect on Fusarium wilt suppression. Appl. Soil Ecol. 2016, 107, 116–123. [Google Scholar] [CrossRef]
  35. Chao, Y.; Fu, G.; Yan, X.; Hang, Z.; Yang, Q.; Wang, H.; Pan, H.; Lou, Y.; Zhu, Y. Effects of Organic Fertilizer on Crop Quality, Soil Fertility and Environment: Research Progress. Chin. Agric. Sci. Bull. 2022, 38, 103–107. [Google Scholar] [CrossRef]
  36. Li, G.; Zhu, S.; Long, J.; Mao, H.; Dong, Y.; Hou, Y. Differences in microbial community structure and metabolic activity among tea plantation soils under different management strategies. Front. Microbiol. 2023, 14, 1219491. [Google Scholar] [CrossRef] [PubMed]
  37. Zhang, S.; Wang, Y.; Sun, L.; Qiu, C.; Ding, Y.; Gu, H.; Wang, L.; Wang, Z.; Ding, Z. Organic mulching positively regulates the soil microbial communities and ecosystem functions in tea plantation. BMC Microbiol. 2020, 20, 103. [Google Scholar] [CrossRef]
  38. Mengesha, W.K.; Powell, S.M.; Evans, K.J.; Barry, K.M. Diverse microbial communities in non-aerated compost teas suppress bacterial wilt. World J. Microbiol. Biotechnol. 2017, 33, 49. [Google Scholar] [CrossRef] [PubMed]
  39. Wei, S.; Liu, B.; Ni, K.; Ma, L.; Shi, Y.; Leng, Y.; Zheng, S.; Gao, S.; Yang, X.; Ruan, J. Rhizosphere Microbial Community Shows a Greater Response Than Soil Properties to Tea (Camellia sinensis L.) Cultivars. Agronomy 2023, 13, 221. [Google Scholar] [CrossRef]
  40. Chen, Y.; Fu, W.; Xiao, H.; Zhai, Y.; Luo, Y.; Wang, Y.; Liu, Z.; Li, Q.; Huang, J. A Review on Rhizosphere Microbiota of Tea Plant (Camellia sinensis L): Recent Insights and Future Perspectives. J. Agric. Food Chem. 2023, 71, 19165–19188. [Google Scholar] [CrossRef]
  41. Lin, S.; Liu, Z.; Wang, Y.; Li, J.; Wang, G.; Ye, J.; Wang, H.; He, H. Soil metagenomic analysis on changes of functional genes and microorganisms involved in nitrogen-cycle processes of acidified tea soils. Front. Plant Sci. 2022, 13, 998178. [Google Scholar] [CrossRef] [PubMed]
  42. Spieck, E.; Sass, K.; Keuter, S.; Hirschmann, S.; Spohn, M.; Indenbirken, D.; Kop, L.F.M.; Lucker, S.; Giaveno, A. Defining Culture Conditions for the Hidden Nitrite-Oxidizing Bacterium Nitrolancea. Front. Microbiol. 2020, 11, 1522. [Google Scholar] [CrossRef]
  43. Wang, S.; Li, T.; Zheng, Z.; Chen, H.Y.H. Soil aggregate-associated bacterial metabolic activity and community structure in different aged tea plantations. Sci. Total Environ. 2019, 654, 1023–1032. [Google Scholar] [CrossRef] [PubMed]
  44. Kalam, S.; Basu, A.; Ahmad, I.; Sayyed, R.Z.; El-Enshasy, H.A.; Dailin, D.J.; Suriani, N.L. Recent Understanding of Soil Acidobacteria and Their Ecological Significance: A Critical Review. Front. Microbiol. 2020, 11, 580024. [Google Scholar] [CrossRef]
  45. Zhang, Z.; Ge, S.; Fan, L.C.; Guo, S.; Hu, Q.; Ahammed, G.J.; Yan, P.; Zhang, L.P.; Li, Z.Z.; Zhang, J.Y.; et al. Diversity in rhizospheric microbial communities in tea varieties at different locations and tapping potential beneficial microorganisms. Front. Microbiol. 2022, 13, 1027444. [Google Scholar] [CrossRef]
  46. Wang, Z.; Xu, M.; Li, F.; Bai, Y.; Hou, J.; Li, X.; Cao, R.; Deng, Y.; Jiang, Y.; Wang, H.; et al. Changes in soil bacterial communities and functional groups beneath coarse woody debris across a subalpine forest successional series. Glob. Ecol. Conserv. 2023, 43, e02436. [Google Scholar] [CrossRef]
  47. Jibola-Shittu, M.Y.; Heng, Z.; Keyhani, N.O.; Dang, Y.; Chen, R.; Liu, S.; Lin, Y.; Lai, P.; Chen, J.; Yang, C.; et al. Understanding and exploring the diversity of soil microorganisms in tea (Camellia sinensis) gardens: Toward sustainable tea production. Front. Microbiol. 2024, 15, 1379879. [Google Scholar] [CrossRef]
  48. Zhang, N.; Tao, R.; Liu, P.; Hu, H.; Gao, L.; Guo, L.; Zhu, Z.; Ma, Y. Effects of organic fertilizer coupled with chemical fertilizer on growth and quality of tea and soil fertility. Acta Agric. Zhejiangensis 2023, 35, 1844–1852. [Google Scholar]
  49. Lin, S.; Zhuang, J.Q.; Chen, T.; Zhang, A.J.; Zhou, M.M.; Lin, W.X. Analysis of nutrient and microbial Biolog function diversity in teasoils with different planting years in Fujian Anxi. Chin. J. Eco-Agric. 2012, 20, 1471–1477. [Google Scholar] [CrossRef]
  50. Li, C.J.; Yang, W.H.; Zhou, B.Q.; Zhang, Y.; Lin, Y.; Xing, S.H. Effects of Biochar Based Fertilizer on Soil Nutrients, Tea Output and Quality in An Acidified Tea Field. Chin. J. Soil Sci. 2021, 52, 387–397. [Google Scholar] [CrossRef]
  51. Liu, W.; Cui, S.; Wu, L.; Qi, W.; Chen, J.; Ye, Z.; Ma, J.; Liu, D. Effects of Bio-organic Fertilizer on Soil Fertility, Yield, and Quality of Tea. J. Soil Sci. Plant Nutr. 2023, 23, 5109–5121. [Google Scholar] [CrossRef]
  52. Hug, L.A.; Castelle, C.J.; Wrighton, K.C.; Thomas, B.C.; Sharon, I.; Frischkorn, K.R.; Williams, K.H.; Tringe, S.G.; Banfield, J.F. Community genomic analyses constrain the distribution of metabolic traits across the Chloroflexi phylum and indicate roles in sediment carbon cycling. Microbiome 2013, 1, 22. [Google Scholar] [CrossRef]
  53. Wang, Y.; Huang, J.; Ye, J.; Li, Y.; Lin, Y.; Liu, C. Effects of different amount of biochar application on soil property and bacterial community structure in acidified tea garden. J. Plant Nutr. Fertil. 2020, 26, 1967–1977. [Google Scholar] [CrossRef]
  54. Chen, C.; Ai, J.; Chen, L.; Li, Y.; Tang, X.; Li, J. Nitrogen metabolism pathways and functional microorganisms in typical karst wetlands. Environ. Sci. Pollut. Res. Int. 2024, 31, 22494–22506. [Google Scholar] [CrossRef] [PubMed]
  55. Delmont, T.O.; Quince, C.; Shaiber, A.; Esen, O.C.; Lee, S.T.; Rappe, M.S.; McLellan, S.L.; Lucker, S.; Eren, A.M. Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes. Nat. Microbiol. 2018, 3, 804–813. [Google Scholar] [CrossRef] [PubMed]
  56. Wang, M.; Sun, H.; Dai, H.; Xu, Z. Characterization of Plant-Growth-Promoting Rhizobacteria for Tea Plant (Camellia sinensis) Development and Soil Nutrient Enrichment. Plants 2024, 13, 2659. [Google Scholar] [CrossRef]
  57. Whitman, T.; Pepe-Ranney, C.; Enders, A.; Koechli, C.; Campbell, A.; Buckley, D.H.; Lehmann, J. Dynamics of microbial community composition and soil organic carbon mineralization in soil following addition of pyrogenic and fresh organic matter. ISME J. 2016, 10, 2918–2930. [Google Scholar] [CrossRef]
  58. Zhou, Z.; Tran, P.Q.; Kieft, K.; Anantharaman, K. Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation. ISME J. 2020, 14, 2060–2077. [Google Scholar] [CrossRef] [PubMed]
  59. Yu, F.; Liang, J.; Shi, J.; Wang, S.; Lu, J. Effects of canopy damage on soil CO2 fixation bacterial community structure in Xiaokeng forest farm. Microbiol. China 2017, 44, 2297–2306. [Google Scholar]
  60. Zhang, R.; Fu, X.; Zhong, H.; Sui, X.; Liu, Y. Changes in Soil Bacterial Community and Function in Winter Following Long-Term Nitrogen (N) Deposition in Wetland Soil in Sanjiang Plain, China. Microorganisms 2023, 11, 2634. [Google Scholar] [CrossRef] [PubMed]
  61. Zhang, R.; Rong, L.; Zhang, L. Soil nutrient variability mediates the effects of erosion on soil microbial communities: Results from a modified topsoil removal method in an agricultural field in Yunnan plateau, China. Environ. Sci. Pollut. Res. Int. 2022, 29, 3659–3671. [Google Scholar] [CrossRef] [PubMed]
  62. Liu, G.; Hu, F.; Abd Elbasit, M.A.M.; Zheng, F.; Liu, P.; Xiao, H.; Zhang, Q.; Zhang, J. Holocene erosion triggered by climate change in the central Loess Plateau of China. CATENA 2018, 160, 103–111. [Google Scholar] [CrossRef]
  63. Hancock, G.R.; Kunkel, V.; Wells, T.; Martinez, C. Soil organic carbon and soil erosion—Understanding change at the large catchment scale. Geoderma 2019, 343, 60–71. [Google Scholar] [CrossRef]
  64. Wang, Y.; Yu, Z.; Li, Y.; Wang, G.; Liu, J.; Liu, J.; Liu, X.; Jin, J. Microbial association with the dynamics of particulate organic carbon in response to the amendment of elevated CO(2)-derived wheat residue into a Mollisol. Sci. Total Environ. 2017, 607–608, 972–981. [Google Scholar] [CrossRef] [PubMed]
  65. Wang, N.; Qian, S.Y.; Pan, X.C.; Chen, Y.L.; Bai, S.B.; Xu, F. Effects of Simulated Acid Rain and Nitrogen Deposition on Soil Bacterial Community Structure and Diversity in the Masson Pine Forest. Huan Jing Ke Xue=Huanjing Kexue 2023, 44, 2315–2324. [Google Scholar] [PubMed]
Agronomy 15 00087 g001
Figure 1. The content of tea polyphenols, water extract, caffeine, and free amino acids in tea leaves after administration of BOF.
Figure 1. The content of tea polyphenols, water extract, caffeine, and free amino acids in tea leaves after administration of BOF.
Agronomy 15 00087 g001
Agronomy 15 00087 g002
Figure 2. The Shannon (A) Good’s coverage (B) index in the BOF1, BOF2, BOF3, and CK groups. ns indicates no significant difference, * means p < 0.05. Alpha diversity analysis of soil bacterial communities, Soil bacterial community diversity under different treatments.
Figure 2. The Shannon (A) Good’s coverage (B) index in the BOF1, BOF2, BOF3, and CK groups. ns indicates no significant difference, * means p < 0.05. Alpha diversity analysis of soil bacterial communities, Soil bacterial community diversity under different treatments.
Agronomy 15 00087 g002
Agronomy 15 00087 g003
Figure 3. Relative abundance of soil bacterial phylum in the rhizosphere soil of tea plants.
Figure 3. Relative abundance of soil bacterial phylum in the rhizosphere soil of tea plants.
Agronomy 15 00087 g003
Agronomy 15 00087 g004
Figure 4. Relative abundance of soil bacterial genera in the rhizosphere soil of tea plants.
Figure 4. Relative abundance of soil bacterial genera in the rhizosphere soil of tea plants.
Agronomy 15 00087 g004
Agronomy 15 00087 g005
Figure 5. BOF might influence the soil microbial structure in the rhizosphere soil of tea plants. The heatmap and clustering analysis of the top 20 soil bacteria at the phylum (A) and genus (B) levels. (C) Microbial community principal coordinate analysis (PCoA) of different groups.
Figure 5. BOF might influence the soil microbial structure in the rhizosphere soil of tea plants. The heatmap and clustering analysis of the top 20 soil bacteria at the phylum (A) and genus (B) levels. (C) Microbial community principal coordinate analysis (PCoA) of different groups.
Agronomy 15 00087 g005
Agronomy 15 00087 g006
Figure 6. Linear discriminant analysis (LDA) distribution histogram is based on LEfSe analysis of classification information, and different colors represent different groups.
Figure 6. Linear discriminant analysis (LDA) distribution histogram is based on LEfSe analysis of classification information, and different colors represent different groups.
Agronomy 15 00087 g006
Agronomy 15 00087 g007
Figure 7. LEfSe biomarkers of the bacterial community in tea rhizosphere soil under different treatments.
Figure 7. LEfSe biomarkers of the bacterial community in tea rhizosphere soil under different treatments.
Agronomy 15 00087 g007
Agronomy 15 00087 g008
Figure 8. Significantly differential biomarkers between the CK group and the BOF1 (A), BOF2 (B), and BOF3 (C) groups were analyzed using LEFSe.
Figure 8. Significantly differential biomarkers between the CK group and the BOF1 (A), BOF2 (B), and BOF3 (C) groups were analyzed using LEFSe.
Agronomy 15 00087 g008
Agronomy 15 00087 g009
Figure 9. Network analysis was based on the top 30 bacterial genera, with absolute abundance in all samples. The size of the point represents the abundance, and the line’s thickness represents the correlation’s magnitude. Red and green lines represent significantly positive and negative correlations, respectively.
Figure 9. Network analysis was based on the top 30 bacterial genera, with absolute abundance in all samples. The size of the point represents the abundance, and the line’s thickness represents the correlation’s magnitude. Red and green lines represent significantly positive and negative correlations, respectively.
Agronomy 15 00087 g009
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yu, C.; Zhou, L.; Huang, X.; You, X.; Lin, J.; Han, H.; Huang, X. Effects of Salt Field Waste-Generated Bio-Organic Fertilizer Application on Bacterial Community Structure in Tea Plantations Rhizosphere Soil. Agronomy 2025, 15, 87. https://doi.org/10.3390/agronomy15010087

AMA Style

Yu C, Zhou L, Huang X, You X, Lin J, Han H, Huang X. Effects of Salt Field Waste-Generated Bio-Organic Fertilizer Application on Bacterial Community Structure in Tea Plantations Rhizosphere Soil. Agronomy. 2025; 15(1):87. https://doi.org/10.3390/agronomy15010087

Chicago/Turabian Style

Yu, Chengran, Liuting Zhou, Xiaoyun Huang, Xiaofeng You, Jiali Lin, Haidong Han, and Xiusheng Huang. 2025. "Effects of Salt Field Waste-Generated Bio-Organic Fertilizer Application on Bacterial Community Structure in Tea Plantations Rhizosphere Soil" Agronomy 15, no. 1: 87. https://doi.org/10.3390/agronomy15010087

APA Style

Yu, C., Zhou, L., Huang, X., You, X., Lin, J., Han, H., & Huang, X. (2025). Effects of Salt Field Waste-Generated Bio-Organic Fertilizer Application on Bacterial Community Structure in Tea Plantations Rhizosphere Soil. Agronomy, 15(1), 87. https://doi.org/10.3390/agronomy15010087

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop