Complex Microbial Fertilizer Promotes the Growth of Summer-Sown Short-Season-Cultivated Cotton and Increases Cotton Yield in the Yangtze River Basin by Changing the Soil Microbial Community Structure
by
Zhangshu Xie
1,†, 
Xiaorong Wang
1,†,
Xuefang Xie
2,†,
Dan Yang
3,
Zhonghua Zhou
1,
Qiming Wang
4,
Aiyu Liu
1,* and
Xiaoju Tu
1,* 1
Cotton Research Institute, Agronomy College, Hunan Agricultural University, Changsha 410128, China
2
Rubber Research Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
3
Jingzhou County Agriculture and Rural Bureau, Huaihua 418400, China
4
College of Biological Science and Technology, Hunan Agricultural University, Changsha 410128, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2025, 15(2), 404; https://doi.org/10.3390/agronomy15020404
Submission received: 3 January 2025
/
Revised: 29 January 2025
/
Accepted: 2 February 2025
/
Published: 4 February 2025
(This article belongs to the Special Issue Effect of Agricultural Management Practices on Soil Microbial Community Composition, Diversity and Function)
Abstract
:The summer-sowing short-season cotton cultivation model is an important method for simplified and mechanized cotton planting in the Yangtze River Basin. However, the effects of microbial fertilizers on cotton growth and soil under this model remain unclear. In 2023, we conducted a systematic analysis on the application of microbial fertilizers (compost) at varying levels (CK, MF1, MF2, and MF3) during different growth stages of cotton (bud, flowering, bolling, and boll opening). Results showed that appropriate microbial fertilizer application (MF2 and MF3) enhanced soil bacterial and fungal diversity, enriched beneficial microorganisms (e.g., Acidobacteriota and Candidatus Udaeobacter), improved soil nutrient availability, and increased antioxidant enzyme activity (POD, SOD), while reducing membrane lipid peroxidation (MDA). These effects led to significant improvements in yield traits, such as cotton plant height, number of fruiting branches and bolls, boll weight, and coat weight. The highest microbial fertilizer application level (MF3) resulted in a 54.35% increase in seed yield and a 75.37% increase in lint yield compared to CK. PLS-DA (Partial Least Squares Discriminant Analysis) and multivariate statistical analyses revealed that microbial fertilizer application fine-tuned soil microbial community composition, emphasizing the dynamic balance of the microbial ecosystem. This study provides scientific support for optimizing microbial fertilizer strategies to enhance the yield and quality of summer-sown short-season cotton and promote sustainable agriculture.
1. Introduction
Cotton (Gossypium spp.) is an important economic crop, and China’s cotton production ranks first in the world [1]. Based on differences in climate, soil, and environmental conditions across planting regions, cotton-growing areas are divided into the Yangtze River Basin, the Yellow River Basin, and the northwestern inland regions (mainly Xinjiang). The traditional planting method for cotton in the Yangtze River Basin primarily involves spring sowing, seedling raising, and transplanting. Sowing typically occurs from the end of March to mid-April each year, with boll opening starting in early August and generally concluding by the end of November. Some late-maturing cotton fields may continue to open bolls until December. The entire growth cycle usually exceeds 220 days, with the boll-opening period lasting over 100 days—a key factor limiting the mechanization of cotton production. Rising labor costs coupled with continuous increases in the prices of seeds, pesticides, and fertilizers have gradually made the traditional cotton planting model insufficient to meet the demands of modern agricultural development [2]. Additionally, the excessively long cotton production cycle exacerbates land competition with winter crops and increases the risk of natural and biological disasters affecting cotton during the growing season, subsequently impacting yield and fiber quality [3]. To address constraints on cotton production, a shift from spring sowing to summer sowing has been implemented, involving increasing the planting density, reducing fertilizer application, adopting water-saving irrigation methods, and using chemical regulation measures to achieve a concentrated boll setting. Furthermore, the use of defoliant ripening agents facilitates concentrated boll opening in the summer-sown short-season cultivation model. This approach allows for simplified and mechanized cotton planting, reduces cost inputs during the production process, and enhances the economic benefits of cotton, and it has recently become an important production and planting technology for cotton in the Yangtze River Basin [4].
Fertilization is an important aspect of cotton cultivation. There have been extensive studies on the effects of traditional fertilizers on cotton growth and development under the summer-sown short-season cultivation model in the Yangtze River Basin [5,6]. Microbial fertilizers, as a new type of organic fertilizer, primarily consist of beneficial microorganisms (including nitrogen-fixing bacteria, decomposing bacteria, disease-resistant bacteria, etc.). In addition, they contain essential nutrients like nitrogen (N), phosphorus (P), and potassium (K), along with plant growth regulators (such as auxins and gibberellins), sugars, amino acids, enzymes, and other supplementary compounds. Microbial fertilizers can persist in the plant roots for a prolonged period, and they promote plant growth by dissolving phosphorus, fixing nitrogen, producing beneficial microorganisms, protecting plants from potential pathogens and harsh environmental conditions, and increasing soil nutrient content [7,8]. In peanut cultivation, the application of microbial biofertilizers can alter the microbial community structure in rhizosphere soil, increase the abundance of beneficial bacteria (Bradyrhizobium, Rhizobium, and Burkholderia) and fungi (Trichoderma and Cladophialophora), reduce the abundance of pathogenic fungi (Penicillium and Fusarium), and significantly promote growth and yield [9]. Yang et al. [10] found that microbial biofertilizers not only increased the content of available phosphorus and potassium in the soil but also increased wheat plants’ height, spike number, and grains per spike, thereby enhancing yield. Similar results have been observed in indoor pot experiments. In tomato plants, Liu et al. [11] found that microbial biofertilizers could increase the photosynthetic rate, transpiration rate, and relative chlorophyll content of leaves, as well as the root surface area and root volume, thereby improving dry matter and nitrogen use efficiency. Therefore, microbial biofertilizers have shown excellent performance in promoting plant growth and development. Currently, in the field trial environment, especially in the planting areas of the Yangtze River Basin, exploring the effects of microbial fertilizers on the growth and development of summer-sown, short-season cotton cultivation holds significant practical relevance.
Therefore, we evaluated the feasibility of applying microbial biofertilizers in cotton production under the summer-sowing short-season cultivation model through field experiments in 2023. By measuring cotton plant height, branch number, leaf enzyme activity, soil biodiversity, and cotton yield at different growth stages, we aimed to elucidate how microbial biofertilizers affect cotton growth and development. Our research contributes to the development of fertilization techniques and methods for cotton cultivation in the summer-sowing short-season model in the Yangtze River Basin of China, providing a theoretical basis for optimizing simplified and mechanized cotton planting in this region.
2. Materials and Methods
2.1. Experimental Materials, Sites, and Design
The composite microbial fertilizer (Hunan Qinong Biotechnology Co., Ltd. Hengyang, China) contains organic matter ≥ 20% (including humic acid ≥ 15%, amino acids ≥ 10%), effective biocontrol bacteria ≥ 20 billion/kg, trace elements ≥ 5%, and N + P2O5 + K2O = 8%.
The experiment was conducted in Yanxi Town, Liuyang City, Hunan Province (28°18′19″ N, 113°49′26″ E), which has a subtropical monsoon humid climate, with an average annual temperature of 19.1 °C and annual precipitation of 1138.6 mm. The soil type is red soil, with a particle composition of clay. The pH of the tillage layer soil is 5.7, available phosphorus is 148.3 mg/kg, total nitrogen is 1.89 g/kg, available potassium is 178.4 mg/kg, and organic matter content is 29.7 g/kg. Sampling and measurements were performed in the Key Laboratory of Crop Physiology and Molecular Biology, Ministry of Education, China. The previous crop was cotton and the amount of fertilizer (N + P+K) applied in the previous year was 800 kg/ha.
Compound microbial fertilizers were applied as basal fertilizers, with four treatment levels: no microbial fertilizer (CK), 1125 kg/ha (MF1), 1875 kg/ha (MF2), and 2625 kg/ha (MF3). Direct sowing was carried out on May 26, 2023. The experiment was planted in a 2-plot-by-4-row layout, with each plot covering an area of 22.5 m2 (4.5 m × 5 m), and was replicated three times, totaling 12 plots. The planting density was set at 90,000 plants per hectare (plant spacing of 0.15 m and row spacing of 0.75 m). A randomized block design was employed for the experiment. The cotton variety used was the early-maturing LAT-69, provided by the Cotton Research Institute of Hunan Agricultural University, with a total growth period of approximately 140 days. Other summer-sown short-season cultivation management practices were implemented in accordance with DB43/T 2379-2022 [12].
2.2. Measurement Indicators and Methods
Prior to bud break, three cotton plants with similar growth and development were marked in each plot for sampling and investigation. Subsequently, the following indicators were investigated during the bud stage, flowering stage, bolling stage, and boll-opening stage.
2.2.1. Cotton Plant Height and Number of Fruit Branches
The height of each cotton plant was measured using a ruler, defined as the distance from the tip of the main stem to the soil surface. The number of fruit branches per cotton plant was observed and recorded.
2.2.2. Enzyme Activity
The fourth leaf from the bottom of the cotton main stem was placed in a plastic sealable bag, wrapped with aluminum foil, and then sealed and stored in a liquid nitrogen tank. Superoxide dismutase (SOD) [13], guaiacol peroxidase (POD) [14], and malondialdehyde (MDA) [15] levels were measured using a UV-Vis spectrophotometer (model UV1910, Shaoxing Kechi Instrument Co., Ltd., Zhejiang, China) according to the instructions provided in the reagent kits produced by Shenggong Biotech Co., Ltd. (Shanghai, China).
2.2.3. Measurement of Soil Biodiversity
Soil samples (0–20 cm) from each cotton plot were collected for bacterial 16S V4 region and fungal ITS1 region IlluminaPE250 sequencing and subsequent analysis. Genomic DNA was extracted from the soil samples using the E.Z.N.A. Soil DNA Kit (Omega Bio-tek, Inc., Norcross, GA, USA) according to the manufacturer’s protocol. DNA concentration and quality were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific Inc., Waltham, MA, USA), and the DNA samples were stored at −20 °C for later use.
The V3-4 hypervariable region of the bacterial 16S rRNA gene was amplified using the universal primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′). A unique 8-digit barcode sequence was appended to the 5′ ends of both the forward and reverse primers (synthesized by Allwegene Company, Beijing, China) for sample identification. PCR amplification was conducted with an ABI 9700 PCR machine (Applied Biosystems, Waltham, MA, USA) with a 25 μL reaction mix, containing 12.5 μL of 2× Taq PCR MasterMix (Vazyme Biotech Co., Ltd., Nanjing, China), 3 μL of BSA (2 ng/μL), 1 μL of each primer (5 μM), 2 μL of template DNA, and 5.5 μL of ddH2O. The amplification conditions were as follows: 95 °C for 5 min, followed by 28 cycles of 95 °C for 45 s, 55 °C for 50 s, and 72 °C for 45 s, with a final extension at 72 °C for 10 min. The resulting PCR products were purified using the Agencourt AMPure XP Kit (Beckman Coulter, Inc., Brea, CA, USA).
Sequencing libraries were prepared using the NEB Next Ultra II DNA Library Prep Kit (New England Biolabs, Inc., Ipswich, MA, USA) in accordance with the manufacturer’s instructions. The quality of the library was evaluated using a NanoDrop 2000 spectrophotometer (ThermoFisher Scientific, Inc., Carlsbad, CA, USA), an Agilent 2100 Bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA), and an ABI StepOnePlus Real-Time PCR System (Applied Biosystems, Inc., Waltham, MA, USA).
High-throughput sequencing was conducted using the Illumina Miseq, Nextseq 2000, and Novaseq 6000 platforms (Illumina, Inc., San Diego, CA, USA) at Beijing Allwegene Technology Co., Ltd. (Beijing, China). Image analysis, base calling, and error estimation were performed using Illumina Analysis Pipeline Version 2.6 (Illumina, Inc., San Diego, CA, USA).
2.3. Yield and Yield Components
The number of bolls per plant in each plot was counted during the boll-opening stage. Cotton bolls with fully opened lint from the lower parts of the plants were harvested. For each plot, 50 opened bolls were collected, dried, and weighed to obtain the average boll weight. Cotton was ginned using a gin machine (Model 110A, Xinxing Cotton Machinery Factory, Dongguang County, Hebei Province, China). The lint percentage is the percentage of cotton fiber (lint) to seed cotton (w/w). The seed cotton and lint yields were calculated by using Xie et al.’s method [16].
2.4. Data Processing and Analysis
Cotton growth and development metrics were organized utilizing Microsoft Excel 2010. Variance analysis was conducted with SPSS version 25.0, and Duncan’s test was applied to evaluate significant differences. Sequencing data for bacterial 16S and fungal ITS regions were processed and assembled using Pear (v0.9.6) software, which involved removing sequences containing ambiguous bases (N), discarding portions of sequences with quality scores below 20, and setting the minimum overlap to 10 bp with a p-value threshold of 0.0001 during assembly. Following the splicing, sequences shorter than 120 bp (with ITS2 sequences at 230 bp) were discarded using Vsearch (v2.7.1) software, and chimeric sequences were removed using the Uchime method based on the Unite Database.
High-quality sequences were clustered into Operational Taxonomic Units (OTUs) using the uparse algorithm in Vsearch (v2.7.1) software, employing a sequence similarity threshold of 97% [17,18]. Alpha- and beta-diversity analyses were performed based on OTUs and their abundance using the methodology outlined by Caporaso et al. [19] with QIIME (v1.8.0) software, and the results were visualized using R (v3.6.0) software. Species composition was illustrated through bar charts derived from species annotations and relative abundance data, analyzed with R (v3.6.0) software.
3. Results and Analyses
3.1. Leaf Enzyme Activities
In terms of POD activity (Table 1), during the bud stage, flowering stage, bolling stage, and boll-opening stage, the microbial fertilizer treatments (MF1, 1125 kg/ha; MF2, 1875 kg/ha; MF3, 2625 kg/ha) significantly enhanced leaf POD activity to varying extents compared to the control (CK). Moreover, an increase in the microbial fertilizer application rate corresponded with a progressively significant enhancement in leaf POD activity. Specifically, treatment MF3 resulted in significant increases of 32.39%, 47.13%, 58.60%, and 109% in POD activity compared to CK during the bud stage, flowering stage, bolling stage, and boll-opening stage, respectively.
Regarding SOD activity, compared to the control, all microbial fertilizer treatments significantly enhanced leaf SOD activity to varying degrees. Additionally, during all growth stages, treatment MF3 significantly increased SOD activity by 34.88%, 38.85%, 33.49%, and 29.91% compared to CK in the bud stage, flowering stage, bolling stage, and boll-opening stage, respectively.
Regarding MDA levels, compared to the control, all microbial fertilizer treatments significantly decreased the MDA content, specifically showing reductions of 5.36~22.52%, 11.49~15.88%, 12.05~24.19%, and 19.47~29.02% during the bud stage, flowering stage, bolling stage, and boll-opening stage, respectively. This suggests that microbial fertilizer treatments contribute to alleviating the process of lipid peroxidation, thereby reducing the degree of membrane damage.
3.2. Plant Height and Number of Cotton Branches
Because cotton was subjected to topping and sprayed with mepiquat chloride during the bolling stage, there was no change in plant height between the boll-opening stage and bolling stage (Table 2). Compared to the control, microbial fertilizer treatments (MF1, MF2, MF3) led to higher plant heights. In the bud stage, flowering stage, and bolling stage, microbial fertilizer treatments (MF1, MF2, MF3) significantly increased plant height by 12.12~18.98%, 10.88~13.62%, and 10.90~14.18% compared to CK, respectively.
The number of fruit branches is a key metric for evaluating the yield potential and regenerative capacity of cotton. With results similar to those for plant height, the microbial fertilizer treatments at varying doses consistently resulted in a higher number of fruit branches compared to CK across all growth stages. The medium-dose treatment (MF2) significantly increased the number of fruit branches by 69.97%, 65.82%, 15.14%, and 18.48% compared to CK during the four growth stages. The high-dose treatment (MF3) significantly increased the number of fruit branches by 67.99%, 74.96%, 17.91%, and 20.80% compared to CK during the four growth stages.
These results demonstrate that microbial fertilizers not only enhance vegetative growth (increased plant height) but also optimize the reproductive distribution in cotton, enabling more potential sites for flowering and boll formation, thereby creating conditions for higher yields.
3.3. Yield and Yield Composition Factors
Table 3 illustrates that the different microbial fertilizer treatments enhanced the cotton seed yield and lint yield by increasing the number of bolls per plant and the weight per boll. Additionally, with an increase in the microbial fertilizer application rate, the number of bolls per plant, weight per boll, seed cotton yield, and lint yield all exhibited an upward trend. Among these treatments, MF3 showed the most optimal performance, significantly increasing the number of bolls per plant, weight per boll, seed cotton yield, and lint yield by 20.81%, 27.67%, 54.35%, and 75.37%, respectively, compared to CK.
3.4. Changes in Soil Microorganisms Under Different Treatments
3.4.1. Alpha-Diversity Analysis
Alpha diversity, as a comprehensive metric reflecting species richness and evenness, is primarily associated with the number of species and the uniformity of individual distribution within the community (Table 4). Regarding the bacterial diversity of cotton, there were no significant differences in Chao1, Observed Species, PD whole tree, or Shannon indices among the different treatments across the four developmental stages. In contrast, with respect to fungal diversity, at the cotton bud stage, the PD whole tree index was highest in treatment MF3, followed by MF2, with treatment MF3 showing increases of 10.50% and 11.42% relative to MF1 and CK, respectively. No significant differences were detected in the remaining alpha-diversity indices under the different treatments.
3.4.2. Community Distribution
The variations in bacterial and fungal communities at the phylum and genus taxonomic levels are illustrated in Figure 1 and Figure 2. In this context, “unidentified” is used to denote taxa that have not been classified, while “other” represents the collective group of unlisted taxa.
At the phylum level, the bacterial community was predominantly composed of Acidobacteriota, Proteobacteria, and Planctomycetota based on relative abundance. Throughout the four developmental stages of cotton, their relative abundances consistently ranked as MF3 > MF2 > MF1 > CK. In the fungal community, Ascomycota (44.40%~72.08%) was the most abundant, followed by Mortierellomycota (6.43%~23.82%) and Basidiomycota (4.30%~9.75%). Similarly, their relative abundances across the four cotton growth stages adhered to the order MF3 > MF2 > MF1 > CK.
At the genus level, Candidatus Udaeobacter (3.04~8.93%) was the most relatively abundant bacterial genus, followed by Candidatus Nitrosotalea (1.62~3.99%). No significant differences were observed among different treatments across the four cotton growth stages. Regarding the fungal community, Mortierella (6.20~26.59%) was the most abundant, followed by Acremonium (6.17~24.83%), with no significant differences among treatments across the four cotton growth stages.
3.4.3. Beta Diversity
PLS-DA (Partial Least Squares Discriminant Analysis) is a supervised discriminant statistical method that enables the prediction of microbial community categories under different treatments.
Sequencing the soil 16SV4 region reveals that different microbial fertilizer treatments (CK, MF1, MF2, MF3) show distinct distribution patterns across sample points during various cotton growth stages (Figure 3). Compared to the non-microbial fertilizer treatment (CK), the microbial fertilizer treatments (particularly the high-dose MF3) show a more pronounced separation from the CK group at each growth stage, indicating that the application of microbial fertilizers alters the composition of the soil bacterial microbial community. Furthermore, the bacterial community distributions during the bud stage and flowering stage are significantly different from those during the bolling stage and boll-opening stage, reflecting the dynamic succession of the bacterial microbial community structure in response to the cotton growth and development stages.
The sequencing of the soil ITS1 region indicates that different microbial fertilizer treatments and various growth stages give rise to significant differences in fungal community characteristics (Figure 4). Compared to the non-microbial fertilizer treatment (CK), all microbial fertilizer treatments (MF1, MF2, MF3) exhibit clear separation trends at each growth stage, with the differences becoming more pronounced with higher application rates (MF3). This demonstrates that the addition of exogenous microbial fertilizers effectively modifies the structural configuration of the soil fungal community.
4. Discussion
4.1. Characteristics of Soil Microbial Diversity in Summer-Sown, Short-Season-Cultivated Cotton
This research comprehensively analyzed the characteristics of soil microbial diversity in summer-sown, short-season-cultivated cotton across different growth stages (bud, flowering, boll, and boll-opening stages) and with varying levels of microbial fertilizer application (CK, MF1, MF2, and MF3). By examining α- and β-diversity indices of bacterial and fungal communities, community composition, and structural characteristics, and by conducting cluster analyses using multivariate statistical methods such as Partial Least Squares Discriminant Analysis (PLS-DA), it was found that soil microbial communities exhibit differences under temporal variations and microbial fertilizer treatments. These findings provide a scientific foundation for a deeper understanding of soil microecological processes within summer-sown, short-season cultivation systems.
First, the results of the α-diversity analysis (including Chao1, Observed Species, Shannon, Simpson, PD whole tree, and Goods coverage) indicate that, although there are no statistically significant differences among the indicators, we can still observe considerable variation in the values of different metrics. This variation might be due to the lack of multi-year, multi-site field trials and possibly a result of the low number of replicates in the measurements. However, it can still be concluded that different application rates of microbial fertilizers and growth stages have an impact on the species richness and diversity of soil bacterial and fungal communities (though no significant differences were observed in this experiment). Moderate application of microbial fertilizers (e.g., MF2 and MF3 treatments) promoted an increase in soil fungal diversity and phylogenetic diversity (PD whole tree) during the cotton budding stage while also increasing the potential abundance of specific beneficial microbial groups. Furthermore, the variations in community diversity across different growth stages in this study suggest that cotton root exudates and the soil microenvironment continuously evolve throughout plant development, thereby influencing the assembly processes of soil microbial communities [20,21].
At the community structure level, the bacterial and fungal communities under different treatments showed different trends of variation at both the phylum and genus levels. The relative abundance of major bacterial phyla such as Proteobacteria, Actinobacteria, and Acidobacteria fluctuated dynamically with microbial fertilizer application rate and growth stage, suggesting that the addition of microbial fertilizers may alter soil nutrients and microenvironmental conditions, thereby promoting the increase in microbial genera with specific functions (such as nitrogen fixation, organic matter decomposition, and phosphorus solubilization) [22,23]. The fungal community exhibited dynamic changes in the abundance of major phyla such as Ascomycota and Basidiomycota, which may be related to the increased abundance of beneficial fungal groups (such as fungi with growth-promoting or disease-preventing functions), thus contributing to improved cotton resistance and yield potential [24].
The β-diversity analysis results (based on PLS-DA plots of the 16S rRNA and ITS1 regions) further validate the significance of differences in microbial community structures under various treatment conditions [25]. Different microbial fertilizer application strategies resulted in clear separations of communities within multidimensional space, indicating that microbial fertilizer treatments exert a selective effect on soil microbial communities [26]. This discovery can offer reference recommendations for formulating effective microbial fertilizer management practices, enabling farmland managers to optimize and adjust fertilizer application rates based on community structure changes in the production of summer-sown, short-season-cultivated cotton.
In conclusion, the findings of this study demonstrate that suitable levels of microbial fertilizer application are closely linked to specific cotton growth stages, and together they synergistically affect the assembly of and dynamic changes in soil bacterial and fungal communities. Changing the precision of microbial fertilizer application not only boosts soil microbial diversity and functional potential, but may also provide microbiological support for the sustainable increase in cotton yields and its adaptation to stress. This provides a more robust scientific foundation for enhancing the environmental adaptability and yield stability of summer-sown, short-season-cultivated cotton.
4.2. Effect of Microbial Fertilizer on Cotton Growth
Peroxidase (POD) and superoxide dismutase (SOD), key components of the antioxidant defense system, play a central role in eliminating reactive oxygen species (ROS). Their elevated activity levels can enhance plant resistance to oxidative stress. Similarly, malondialdehyde (MDA), a product of membrane lipid peroxidation, serves as an indicator of the extent of oxidative damage to cell membranes. The results of this study indicate that varying levels of microbial fertilizer application have a significant impact on the growth and development processes and yield traits of cotton. By comprehensively considering factors such as leaf enzyme activity, plant heights, numbers of fruit branches, and yield components, it was found that microbial fertilizers not only promote the morphological growth of cotton (e.g., increased plant height and number of fruit branches) but also influence the physiological and metabolic processes of the crop.
Firstly, the increase in activities of POD (peroxidase) and SOD (superoxide dismutase) in the leaves, along with the decrease in MDA (malondialdehyde) content, indicates that appropriate microbial fertilizer treatments can enhance the antioxidant defense mechanisms of cotton. This improvement may be related to the role of microbial communities in the rhizosphere in promoting the secretion of growth hormones and the transformation of nutrients [27,28]. For example, beneficial microorganisms can enhance plant tolerance to abiotic stresses and improve leaf metabolic balance by secreting plant hormone analogs (such as IAA) and enzyme substances [29]. The enhanced enzyme activities directly reduce the accumulation of reactive oxygen species (ROS) and the degree of membrane lipid peroxidation, enabling plants to maintain high physiological activity and growth vigor during key growth and developmental stages (such as the bud, flowering, bolling, and boll-opening stages).
In terms of morphological indicators, this study found that microbial fertilizer treatments significantly increased cotton plant height and the number of fruit branches. This result is consistent with previous studies indicating that microbial fertilizers promote plant growth by improving the soil microenvironment, enhancing nutrient supply, and increasing root absorption capacity [30]. The introduction of microbial communities can strengthen the diversity and stability of the rhizosphere microbial ecosystem, thereby promoting the efficient transformation and effective supply of soil nutrients (such as nitrogen, phosphorus, and potassium) [31]. The resulting growth-promoting effects not only are reflected in plant architecture but also lay the foundation for subsequent photosynthetic accumulation and assimilate transport by improving canopy structure and leaf area index.
An improvement in yield traits is one of the key findings of this study. Analyses of the boll number, boll weight, lint percentage, and seed cotton yield indicate that the moderate application of microbial fertilizers (such as treatments MF2 and MF3) significantly enhances seed cotton and lint yields. This is consistent with the increase in nutrient efficiency and the promotion of assimilate accumulation mediated by microbial fertilizers [32]. During the reproductive growth stage of cotton, appropriate microbial fertilizer application can increase the number of flower buds and boll weight, allowing plants to receive more nutrient supply and physiological support at critical yield formation stages, thereby achieving higher final yields. This process is also related to the role of microbial communities in improving soil structure, such as enhancing soil aggregate stability and micropore proportion, thereby optimizing the root growth environment and increasing water and nutrient use efficiency [33].
In summary, this study provides a comprehensive explanation of the promotional effects of microbial fertilizers on cotton growth from three points of view: physiology (enzyme activity, membrane lipid peroxidation), morphology (plant height, number of fruit branches), and yield (boll number, boll weight, lint percentage, yield). The results indicate that the positive regulatory effects of microbial fertilizers are not limited to a single dimension but involve multiple mechanisms acting synergistically, enabling cotton to achieve stronger stress resistance, better growth vigor, and higher yield benefits. Future research could explore the universality and stability of the effects of microbial fertilizer applications on cotton growth and development in different soil environments and cultivation systems.
5. Conclusions
Appropriate microbial fertilizer application rates (MF2 and MF3) promoted an increase in soil fungal diversity and phylogenetic diversity (PD whole tree) during the cotton bud stage. Meanwhile, throughout cotton growth, dynamic changes in the soil microbial community structure occurred, and the interaction between microbial fertilizers and growth stages jointly influenced the spatiotemporal distribution patterns of microbial communities. Additionally, microbial fertilizers enhanced the physiological activity and stress resistance of cotton by increasing antioxidant enzyme activity in leaves and reducing MDA content. This promoted the growth of plant height and the number of fruit branches, increased the number and weight of bolls, and improved yield quality, thereby optimizing yield. In summary, microbial fertilizers show promising application prospects in summer-sown short-season cotton cultivation in the Yangtze River Basin. By changing soil microbial diversity and promoting plant growth, microbial fertilizers increased cotton yield. This study provides valuable insights for optimizing fertilization strategies in the region, supporting the transition to more sustainable and mechanized cotton farming. Future research should further explore the long-term effects of microbial fertilizer application on soil health and cotton quality, and assess their applicability and integration potential in large-scale agricultural practices across different regions.
Author Contributions
Conceptualization, Z.X., X.T. and A.L.; methodology, Z.X., X.W. and X.X.; software, Z.Z.; validation, Z.X., X.W. and X.X.; formal analysis, Z.Z.; investigation, X.T.; resources, Q.W.; data curation, D.Y.; writing—original draft preparation, Z.X.; writing—review and editing, X.W.; visualization, X.X.; supervision, X.T. and A.L.; project administration, Q.W. and A.L.; funding acquisition, X.T. and A.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Hunan Provincial Department of Agriculture and Rural Affairs (XIANG CAI JIAN ZHI (2023) No. 98 and (2024) No. 162), the Hunan Provincial Postgraduate Student Research and Innovation Project (CX20240638), and the Hunan Provincial Cotton Industry Technology System Cultivation and Seed Breeding Post Expert Project (XIANG NONG FA (2022) No. 31).
Institutional Review Board Statement
Not applicable.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.
Conflicts of Interest
The authors declare no competing interests.
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Figure 1.
Distribution of microbial communities in soil samples under different treatments during various growth stages. (a) Bacterial communities at the phylum level; (b) fungal communities at the phylum level.
Figure 1.
Distribution of microbial communities in soil samples under different treatments during various growth stages. (a) Bacterial communities at the phylum level; (b) fungal communities at the phylum level.
Figure 2.
Distribution of microbial communities in soil samples under different treatments during various growth stages. (a) Bacterial communities at the genus level; (b) fungal communities at the genus level.
Figure 2.
Distribution of microbial communities in soil samples under different treatments during various growth stages. (a) Bacterial communities at the genus level; (b) fungal communities at the genus level.
Figure 3.
Performance of soil microbial bacteria based on β-diversity under different periods: (a) bud stage, (b) flowering stage, (c) bolling stage, and (d) boll-opening stage.
Figure 3.
Performance of soil microbial bacteria based on β-diversity under different periods: (a) bud stage, (b) flowering stage, (c) bolling stage, and (d) boll-opening stage.
Figure 4.
Performance of soil microbial fungi based on β-diversity under different periods. (a) Bud stage, (b) flowering stage, (c) bolling stage, and (d) boll-opening stage.
Figure 4.
Performance of soil microbial fungi based on β-diversity under different periods. (a) Bud stage, (b) flowering stage, (c) bolling stage, and (d) boll-opening stage.
Table 1.
Effects of microbial fungal fertilizers on POD, SOD and MDA enzyme activities of cotton leaves.
Table 1.
Effects of microbial fungal fertilizers on POD, SOD and MDA enzyme activities of cotton leaves.
| Period | Treatment | POD/(U·g−1) | SOD/(U·g−1) | MDA /(nmol·g−1) |
|---|---|---|---|---|
| Bud stage | CK | 2384.56 ± 57.15 d | 209.67 ± 16.84 b | 340.21 ± 10.21 a |
| MF1 | 2756.74 ± 58.88 c | 245.45 ± 19.02 ab | 321.97 ± 11.45 b | |
| MF2 | 2948.05 ± 90.51 b | 252.15 ± 28.23 ab | 300.60 ± 8.85 c | |
| MF3 | 3156.81 ± 145.72 a | 282.81 ± 15.36 a | 263.58 ± 6.29 d | |
| Flowering stage | CK | 2569.80 ± 77.55 d | 284.78 ± 6.51 c | 405.31 ± 8.02 a |
| MF1 | 2910.86 ± 59.52 c | 345.13 ± 16.04 b | 358.72 ± 3.88 b | |
| MF2 | 3406.85 ± 84.08 b | 366.14 ± 15.23 b | 356.93 ± 15.96 b | |
| MF3 | 3781.00 ± 30.88 a | 395.43 ± 11.37 a | 340.95 ± 9.12 b | |
| Bolling stage | CK | 2963.58 ± 93.48 d | 335.48 ± 7.94 c | 462.61 ± 13.86 a |
| MF1 | 4085.58 ± 197.55 c | 388.62 ± 14.03 b | 406.87 ± 11.10 b | |
| MF2 | 4448.56 ± 65.45 b | 419.71 ± 15.81 ab | 388.62 ± 31.11 bc | |
| MF3 | 4700.38 ± 75.50 a | 447.82 ± 12.68 a | 350.70 ± 2.64 c | |
| Boll-opening stage | CK | 1545.48 ± 61.78 c | 240.85 ± 7.46 c | 547.62 ± 7.59 a |
| MF1 | 2652.64 ± 122.19 b | 286.73 ± 4.47 b | 441.00 ± 10.06 b | |
| MF2 | 3072.31 ± 200.99 a | 298.15 ± 8.30 ab | 399.71 ± 15.98 c | |
| MF3 | 3232.49 ± 50.25 a | 312.88 ± 4.06 a | 388.68 ± 7.64 c |
According to Duncan’s test (p < 0.05), different lower-case letters indicate significant differences between treatments under the same indicator.
Table 2.
Effect of microbial fungal fertilizer on cotton plant height and number of cotton branches.
Table 2.
Effect of microbial fungal fertilizer on cotton plant height and number of cotton branches.
| Period | Treatment | Plant Height/cm | Number of Cotton Branches |
|---|---|---|---|
| Bud stage | CK | 48.10 ± 1.25 c | 3.53 ± 0.29 b |
| MF1 | 53.93 ± 1.10 b | 5.16 ± 0.57 a | |
| MF2 | 56.03 ± 1.25 ab | 6.00 ± 0.36 a | |
| MF3 | 57.23 ± 0.55 a | 5.93 ± 0.25 a | |
| Flowering stage | CK | 86.43 ± 1.10 c | 6.67 ± 0.61 b |
| MF1 | 95.83 ± 1.25 b | 10.87 ± 0.31 a | |
| MF2 | 96.30 ± 0.66 ab | 11.06 ± 0.81 a | |
| MF3 | 98.20 ± 0.46 a | 11.67 ± 0.42 a | |
| Bolling stage | CK | 107.37 ± 2.22 b | 10.83 ± 0.51 b |
| MF1 | 119.07 ± 8.21 a | 11.80 ± 0.20 ab | |
| MF2 | 120.13 ± 4.87 a | 12.47 ± 0.58 a | |
| MF3 | 122.60 ± 5.50 a | 12.77 ± 0.51 a | |
| Boll-opening stage | CK | 107.37 ± 2.22 b | 11.20 ± 0.53 b |
| MF1 | 119.07 ± 8.21 a | 12.90 ± 0.85 a | |
| MF2 | 120.13 ± 4.87 a | 13.27 ± 0.40 a | |
| MF3 | 122.60 ± 5.50 a | 13.53 ± 0.65 a |
According to Duncan’s test (p < 0.05), different lower-case letters indicate significant differences between treatments under the same indicator.
Table 3.
Effects of microbial fertilizers on cotton yield and yield components.
| Treatment | Boll Number per Plant/Pieces | Boll Weight/g | Lint Percentage/% | Seed Cotton Yield/(kg·ha−1) | Lint Yield/(kg·ha−1) |
|---|---|---|---|---|---|
| CK | 21.00 ± 1.59 b | 2.53 ± 0.06 b | 35.96 ± 0.83 a | 4066.74 ± 255.07 c | 1461.23 ± 65.93 c |
| MF1 | 23.77 ± 0.42 ab | 2.73 ± 0.06 b | 39.60 ± 1.47 a | 4970.46 ± 177.25 b | 1969.62 ± 135.91 b |
| MF2 | 24.70 ± 0.92 a | 3.07 ± 0.15 a | 39.97 ± 2.78 a | 5793.60 ± 333.41 ab | 2313.73 ± 170.52 ab |
| MF3 | 25.37 ± 0.31 a | 3.23 ± 0.15 a | 40.81 ± 0.70 a | 6276.83 ± 373.11 a | 2562.49 ± 184.65 a |
According to Duncan’s test (p < 0.05), different lower-case letters indicate significant differences between treatments under the same indicator.
Table 4.
Diversity and abundance of bacteria and fungi under different microbial fertilizer treatments based on various cotton growth stages.
Table 4.
Diversity and abundance of bacteria and fungi under different microbial fertilizer treatments based on various cotton growth stages.
| Classification | Period | Treatment | Chao1 | Observed Species | PD Whole Tree | Shannon |
|---|---|---|---|---|---|---|
| Bacteria | Bud stage | CK | 8185.19 ± 466.34 a | 6769.20 ± 443.47 a | 335.26 ± 22.17 a | 10.53 ± 0.25 a |
| MF1 | 8081.91 ± 124.49 a | 6626.00 ± 120.02 a | 325.15 ± 7.02 a | 10.51 ± 0.15 a | ||
| MF2 | 8221.69 ± 162.26 a | 6848.83 ± 70.56 a | 333.73 ± 2.92 a | 10.71 ± 0.12 a | ||
| MF3 | 7978.57 ± 205.43 a | 6630.17 ± 187.07 a | 325.31 ± 10.77 a | 10.54 ± 0.18 a | ||
| Flowering stage | CK | 8356.91 ± 124.63 a | 6990.60 ± 81.31 a | 317.23 ± 4.16 a | 10.66 ± 0.10 a | |
| MF1 | 8222.83 ± 34.74 a | 6922.63 ± 138.80 a | 316.39 ± 4.44 a | 10.67 ± 0.09 a | ||
| MF2 | 8269.78 ± 59.30 a | 7024.97 ± 76.03 a | 319.70 ± 6.53 a | 10.71 ± 0.12 a | ||
| MF3 | 8339.52 ± 112.32 a | 6954.97 ± 58.82 a | 315.65 ± 1.38 a | 10.66 ± 0.06 a | ||
| Bolling stage | CK | 8066.15 ± 239.82 a | 6789.63 ± 182.82 a | 291.79 ± 11.26 a | 10.65 ± 0.12 a | |
| MF1 | 8119.73 ± 155.86 a | 6754.63 ± 114.06 a | 288.75 ± 3.20 a | 10.61 ± 0.16 a | ||
| MF2 | 8081.62 ± 267.10a | 6757.60 ± 150.03a | 292.55 ± 5.04a | 10.65 ± 0.06a | ||
| MF3 | 8245.98 ± 213.49 a | 6842.00 ± 135.53 a | 293.36 ± 5.39 a | 10.71 ± 0.05 a | ||
| Boll-opening stage | CK | 8332.57 ± 232.85 a | 6996.83 ± 113.47 a | 312.62 ± 3.72 a | 10.68 ± 0.11 a | |
| MF1 | 8449.62 ± 114.24 a | 7003.47 ± 124.94 a | 315.68 ± 7.94 a | 10.68 ± 0.06 a | ||
| MF2 | 8308.74 ± 274.94 a | 6926.87 ± 241.90 a | 310.52 ± 6.91 a | 10.62 ± 0.12 a | ||
| MF3 | 8171.77 ± 486.10 a | 6836.27 ± 360.10 a | 307.89 ± 11.39 a | 10.53 ± 0.33 a | ||
| Fungi | Bud stage | CK | 1281.65 ± 64.20 a | 1136.30 ± 42.02 a | 205.56 ± 6.47 b | 6.33 ± 0.30 a |
| MF1 | 1239.97 ± 46.04 a | 1064.33 ± 36.23 a | 207.28 ± 6.25 b | 6.01 ± 0.32 a | ||
| MF2 | 1238.76 ± 51.38 a | 1055.97 ± 5.33 a | 210.31 ± 5.61 ab | 6.10 ± 0.25 a | ||
| MF3 | 1274.35 ± 49.62 a | 1075.00 ± 27.87 a | 229.04 ± 5.79 a | 6.25 ± 0.22 a | ||
| Flowering stage | CK | 1309.30 ± 90.17 a | 1104.00 ± 107.46 a | 247.93 ± 23.14 a | 5.70 ± 0.43 a | |
| MF1 | 1296.56 ± 103.83 a | 1123.33 ± 75.27 a | 242.93 ± 18.94 a | 6.44 ± 0.15 a | ||
| MF2 | 1215.02 ± 133.57 a | 1038.67 ± 121.13 a | 228.08 ± 22.19 a | 5.08 ± 0.75 a | ||
| MF3 | 1311.08 ± 92.62 a | 1144.00 ± 105.30 a | 238.24 ± 10.23 a | 5.80 ± 0.66 a | ||
| Bolling stage | CK | 1231.32 ± 96.88 a | 1019.00 ± 128.75 a | 241.27 ± 36.89 a | 5.12 ± 0.32 a | |
| MF1 | 1204.80 ± 35.11 a | 1013.63 ± 59.79 a | 234.94 ± 17.32 a | 5.38 ± 0.62 a | ||
| MF2 | 1283.12 ± 105.02 a | 1106.00 ± 74.30 a | 268.82 ± 29.42 a | 5.76 ± 0.82 a | ||
| MF3 | 1357.49 ± 134.39 a | 1165.67 ± 51.79 a | 270.06 ± 15.25 a | 5.94 ± 0.40 a | ||
| Boll-opening stage | CK | 1241.06 ± 77.17 a | 990.63 ± 118.59 a | 224.14 ± 44.08 a | 6.05 ± 0.60 a | |
| MF1 | 1307.51 ± 57.92 a | 1052.30 ± 25.55 a | 244.01 ± 10.60 a | 5.99 ± 0.14 a | ||
| MF2 | 1246.91 ± 213.65 a | 1010.63 ± 147.94 a | 223.36 ± 24.83 a | 5.93 ± 0.80 a | ||
| MF3 | 1257.38 ± 75.36 a | 1001.27 ± 66.14 a | 223.10 ± 8.82 a | 5.70 ± 0.37 a |
According to Duncan’s test (p < 0.05), different lower-case letters indicate significant differences between treatments under the same indicator.
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Xie, Z.; Wang, X.; Xie, X.; Yang, D.; Zhou, Z.; Wang, Q.; Liu, A.; Tu, X. Complex Microbial Fertilizer Promotes the Growth of Summer-Sown Short-Season-Cultivated Cotton and Increases Cotton Yield in the Yangtze River Basin by Changing the Soil Microbial Community Structure. Agronomy 2025, 15, 404. https://doi.org/10.3390/agronomy15020404
AMA Style
Xie Z, Wang X, Xie X, Yang D, Zhou Z, Wang Q, Liu A, Tu X. Complex Microbial Fertilizer Promotes the Growth of Summer-Sown Short-Season-Cultivated Cotton and Increases Cotton Yield in the Yangtze River Basin by Changing the Soil Microbial Community Structure. Agronomy. 2025; 15(2):404. https://doi.org/10.3390/agronomy15020404
Chicago/Turabian StyleXie, Zhangshu, Xiaorong Wang, Xuefang Xie, Dan Yang, Zhonghua Zhou, Qiming Wang, Aiyu Liu, and Xiaoju Tu. 2025. "Complex Microbial Fertilizer Promotes the Growth of Summer-Sown Short-Season-Cultivated Cotton and Increases Cotton Yield in the Yangtze River Basin by Changing the Soil Microbial Community Structure" Agronomy 15, no. 2: 404. https://doi.org/10.3390/agronomy15020404
APA StyleXie, Z., Wang, X., Xie, X., Yang, D., Zhou, Z., Wang, Q., Liu, A., & Tu, X. (2025). Complex Microbial Fertilizer Promotes the Growth of Summer-Sown Short-Season-Cultivated Cotton and Increases Cotton Yield in the Yangtze River Basin by Changing the Soil Microbial Community Structure. Agronomy, 15(2), 404. https://doi.org/10.3390/agronomy15020404
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