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Article

Effects of Continuous Straw Return on Soil Nutrients and Microbial Community Structure of Paddy Fields in Northeast China

by
Juntao Ma
,
Qiuju Wang
* and
Jiahe Zou
Heilongjiang Academy of Agricultural Sciences, No. 368 Xuefu Road, Nangang District, Harbin 150086, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(6), 1404; https://doi.org/10.3390/agronomy15061404
Submission received: 1 December 2024 / Revised: 29 April 2025 / Accepted: 12 May 2025 / Published: 6 June 2025
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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Abstract

:
Albic soil, which is generally oligotrophic, is a typical low-yield soil widely distributed in China. It is still unclear how to effectively improve soil fertility and strengthen the sustainable development of agricultural cultivation. For this purpose, 8-year field experiments were performed to determine the effects of continuous rice straw return on soil nutrient characteristics, yield, and the soil microbial community. Straw incorporation into albic soil significantly contributed to nutrient accumulation, containing alkali-hydrolysed nitrogen, available phosphorus, available potassium, and total organic carbon, thereby increasing rice yield. The number of spikelets per panicle increased from 93.96 to 97.58, and the grain filling value increased from 88.11 to 91.44%. Additionally, rice yield increased over the 8 consecutive years of straw return, and the rice yield of straw return treatments ranged from 10,048.27 to 10,605.18 kg/ha. High-throughput sequencing and classification revealed that the composition of bacterial and fungal communities was similar among treatments, but there were significant differences in species abundance, which was associated with lignocellulose degradation. Overall, the continuous return of straw, a native organic material, is a promising approach for soil amendment, with resource-saving and environmentally friendly characteristics.

1. Introduction

Albic soil, which is representative of the white–grey albic layer with low yield, is distributed throughout Heilongjiang and Jilin Provinces in China. The total area covered by albic soil in China is approximately 5.27 million ha, which exceeds 60% of the general zone in the cold region of the northeast [1]. Unreasonable long-term farming and resource utilisation, soil organic matter loss, and excessive chemical fertiliser application have resulted in variations in the soil’s physical structure and nutrient content [2,3]. The albic layer is generally highly viscous, highly acidic, and hardened with characteristics of low ventilation and water permeability, which are detrimental to crop growth, decreasing yield. With the continuous development of agricultural production, it is necessary to effectively improve the soil fertility of albic soil and reinforce the sustainability of the farming industry.
Maize (Zea mays L.), wheat (Triticum aestivum L.), and rice (Oryza sativa) are important feed and food resources cultivated worldwide [4]. The requirements of agricultural production are expanding with the rapid global population growth. Constantly and steadily supplying rice is not only an economic issue but also a principal element affecting political and social stability. As the world’s most produced crop, it will be challenged with the disposal of agricultural residues, of which crop straw is predominant. In recent decades, its inappropriate handling, such as openly burning straw, which is one of the most widely used methods for removing crop residues, has not only wasted resources but has also had a serious negative impact on the atmospheric and ecological environment [5,6]. During harvesting periods, the substantial increase in atmospheric particulate matter, including haze, smog, and other environmental hazards, causes severe air pollution and poses a great threat to human life and health [7]. The effective utilisation of straw resources is an important basis for the development of resource-saving, environmentally friendly, and green agriculture.
Straw, as a predominant agricultural residue, provides substantial amounts of organic matter and essential nutrients, such as organic carbon (C), nitrogen (N), phosphorus (P), and potassium (K), which are closely related to plant growth [8]. Soil enzymes, including cellobiohydrolase, peroxidase, amylase, and β-1,4-glucosidase, are widely recognised as proximate drivers in the processing of soil organic matter decomposition, transformation, and mineralisation [9,10,11]. Direct straw return is a primary management approach for regulating the soil nutrient cycle, reducing the soil bulk density, and maintaining the soil’s physical and chemical properties, such as acidity and alkalinity and organic C [11], N, P [12], and K contents [13]. In a long-term straw return experiment, the soil total N content and N sequestration rates increased by 20.01 and 120.95%, respectively, due to the variation in the C:N ratio in the experimental field caused by amino acid N accumulation [14]. Straw return in a granulated form is a promising approach for enhancing soil organic C fractions, of which microbial biomass C has the highest value at all soil depths [15]. Straw return to the field also has a considerable influence on the richness and diversity of soil microbial communities [16]. Soil is known as the “natural base” for microorganisms, which is the richest resource of bacteria and fungi. Soil microbial communities that are physically close to the roots or rhizosphere of plants play crucial roles in organic matter decomposition, soil nutrient cycling, pollutant degradation, plant health maintenance, and disease suppression. The relative abundance of Bradyrhizobium, a N-fixing rhizobacterium that promotes the soil microbial N cycle and provides N to the soil, is accumulated through wheat straw return. In addition, the return of wheat and maize straw to the experimental field significantly increased the abundance of Chaetomium, a well-known microbial cell factory known for its ability to generate a wide array of bioactive secondary metabolites [17,18]. The diversity and relative abundance of soil bacteria and fungi communities fluctuates with the amount of straw application. Short-term straw return increased the abundance of Geobacter and Crenohrix, which may be related to the iron cycle process in paddy soil [19]. Therefore, understanding the soil microbial community under these agricultural practices is imperative for assessing the soil ecological health status and nutrient element cycling.
In a previous study, researchers attempted to improve albic soil to increase crop yield; chemical fertiliser application, the mechanical breakage of the albic layer, and adjustment to the acid–base properties were employed as the predominant methods for albic soil improvement [20]. However, most of these methods could not effectively improve the nutrient distribution of albic soil, and the development of resource-saving and environment-friendly comprehensive management methods remains a challenge. For this purpose, continuous straw return to the paddy field was performed and investigated for eight years at a rice experimental base, which has albic soil. To provide a comprehensive understanding of straw return to the experimental field, we comprehensively evaluated the nutrition profile of the soil, the fungal disease index, compositional characteristics of soil microbial communities, and rice yield. The findings of this study provide a theoretical basis and a promising approach for albic soil management, thereby fostering sustainable agricultural development in northeast China.

2. Materials and Methods

2.1. Experimental Site Description

This investigation was performed from 2016 to 2023 at a single-cropping rice experimental base in Jiansanjiang, Heilongjiang Province, China (47°34′1, 132°17′ E). This region has a cold temperate and humid monsoon climate with an annual average temperature of 2.6–3.5 °C, an average annual precipitation of 350–840 mm, a frost-free period of approximately 124 days, and an annual active temperature of approximately 2600 °C. The paddy soils of the experimental site are albic soil, with a typical white–grey albic layer, which is distributed throughout the provinces of Heilongjiang and Jilin. Albic soil is composed of an albic layer 20–40 cm below slightly black soil and has a generally low-yielding characteristic due to its dense physical structure and low soil fertility. Following the autumn rice harvest each year, straw is processed in this manner. After the winter period, when the soil temperature surpassed 5 °C, water was introduced to the field’s surface. The water level was maintained at 3–5 cm, and once the soil settled, rice transplanting was conducted.

2.2. Field Experiment Design

The objective was to increase the soil fertility and crop yield in the albic soil region. At the rice experimental base, continuous straw return to the paddy field was performed and investigated for 8 years (the biomass of the returned rice straw was 7500 kg/ha in 2016–2023). Many organic materials were found in the rice straw, in which the N, C, P, and K contents were 8.21, 472.16, 1.32, and 2.17 g/kg, respectively. The experiment consisted of three experimental fields, and each test plot was 700 m2. Three plots (replicates) were created for each condition. The rice straw returned to the paddy field was ‘Long Geng 31’, which has high yield and insect and pathogen resistance. Straw was returned to the paddy field using the following procedure: In the maturity stage, rice straw was crushed into small pieces using a pulveriser and randomly applied to the field’s surface. The mulched straw was rotated into the soil using a rotary tiller, and the return depth was 0–20 cm. No other field crop perturbation was performed, except straw return and rice planting. The operating procedures were the same in each year of the experiment. Experiments were divided into two groups with different treatments: (1) the control group (CK; no straw return) and (2) rice straw return (SR). The straw in the experimental field was returned to the field, with an average organic C content of 34.65%, total N content of 0.542%, and C:N ratio of 64:1. The experiment did not consider the nutrient balance over the 8-year period, as the C and N deposition from paddy fields cannot be estimated as they enter the soil and evaporate into the hydrosphere and atmosphere. In the sowing and maturity stages, soil samples were randomly collected in each treatment. The soil samples were selected at a depth of 0–10 and 10–20 cm.

2.3. Effects of Continuous Straw Return on the Soil Nutrient Content

Soil samples were randomly collected from the experimental plots at 0–10 and 10–20 cm depths during the rice sowing and harvest periods. All samples were naturally air-dried and screened through a 40-mesh sieve. The alkali-hydrolysed N, available P, available K, and total organic C (TOC) contents were determined following the method described by Douglas and Olsen [21,22]. To determine the alkali-hydrolysed N content, a method utilising the principles of alkaline hydrolysis was employed to hydrolyse soil samples with sodium hydroxide (NaOH, C01315101, Nanjing China) addition under high-temperature sealed conditions. This process converted organic N into ammonium N. The resulting ammonia was collected through diffusion or distillation, absorbed by boric acid (C06801802, Nanjing China), and quantified using standard acid titration techniques. This method effectively indicated the soil’s short-term mineralisable N potential. The available P content was determined using Olsen’s classical sodium bicarbonate extraction method (0.5 mol/L NaHCO3 C01315301, Nanjing China, pH 8.5), which utilises competitive adsorption mechanisms to extract active P fractions. The extract was then quantified spectrophotometrically using the molybdenum–antimony ascorbic acid colorimetric method, providing precise characterisation of P availability in neutral-to-alkaline soils. The available K content was determined through extraction using neutral ammonium acetate (1 mol/L NH4OAc, C04105801, Nanjing China), in which cation exchange mechanisms facilitated the release of exchangeable K from soil colloids. The filtered extract was subsequently measured via flame photometry, a method that ensures simplicity and minimises interference. The TOC content was determined following the modified Walkley–Black wet oxidation method, as adapted by Douglas. This involved the oxidation of organic C to CO2 using K dichromate–sulphuric acid under heated conditions. The residual oxidant was back-titrated with ferrous sulphate to quantify the C content.

2.4. Yield

To determine the various indices under continuous straw return treatment, 20 m2 plots, separated by plastic film-wrapped ridges, were sampled in 2023. Each treatment had three replicates. Three groups containing 30 rice samples were randomly selected from each experimental plot in the maturity stage; spikelets per panicle, 1000-grain weight, grain filling, panicles, and yield were measured in accordance with the methods described by Zhou et al. [23]. Each plot was threshed separately to ensure data accuracy.

2.5. Effects of Continuous Straw Return on Fugal Disease Incidence

Rice is one of the main grain crops cultivated worldwide. Rice plants face significant threats from a range of fungal, bacterial, and viral plant pathogens. For instance, rice leaf blast, rice false smut, and other plant diseases occur frequently and have a serious impact on rice yield. To determine the influence of straw return on the growth status of pathogenic fungi, the incidence of multifarious plant mycoses, such as rice leaf blast, panicle neck blast, rice sheath blight, sheath rot disease, and rice false smut were determined. Rice blast and sheath blight were evaluated by natural inoculation in the field. For each treatment, 30 rice samples were collected. Three replicates were maintained in each treatment, and the experiment was repeated twice.
A disease index was calculated for rice leaf blast and sheath rot diseases using the following disease severity scale: 0—no symptom development; 1—a lesion area accounting for 25% of the whole flag leaf sheath; 2—a lesion area accounting for 25–50% of the entire flag leaf sheath; 3—a lesion area accounting for 50–75% of the entire flag leaf sheath; 4—a lesion area accounting for more than 75% of the entire flag leaf sheath. The disease index was calculated using the following formula: Disease index = 100 × Σ (Number of diseased leaves × Disease severity rating)/(Total number of investigated leaves × Highest representative disease severity rating).
A disease index was similarly calculated for panicle neck blast, rice sheath blight, and rice false smut using the following scale: 0—no symptom development; 1—one diseased grain per panicle; 2—two diseased grains per panicle; 3—three to five diseased grains per panicle; 4—six to nine diseased grains per panicle; 5—more than ten diseased grains per panicle. The disease index was calculated using the following formula: Disease index = 100 × Σ (Number of diseased grains × Disease rating)/(Total number of investigated grains × Highest representative disease rating).

2.6. Microbial Community Assessment Using Illumina

Total microbial genomic DNA was extracted from each of the eight samples (1.0 g soil samples from two depths in the sowing and maturity stages under the CK and SR treatments) using an E.Z.N.A.® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to the manufacturer’s instructions. The harvested DNA was assessed for quality and concentration using Nanodrop 2000 (NanoDrop Technologies, Wilmington, DE, USA). For bacteria, the hypervariable region V3–V4 of the 16S rRNA gene was amplified using the universal primer pair 338F (5’-ACTCCTACGGGA GGCAGCA-3’) and 806R (5’-GGACTACHVGGG TWTCTAAT-3’) to determine the composition of the bacterial community [24]. The internal transcribed spacer (ITS) region of the fungal community was amplified using the primer sets ITS1F (5’-CTTGGTCATTTAGAGGAA GTAA-3’) and ITS2 (5’-GCTGCGTTCTTCATCGAT GC-3’) [25]. All samples were amplified in triplicate. High-throughput sequencing analysis of microbiota in various specimens was performed based on the Illumina MiSeq PE300 platform/NovaSeq PE250 platform (Illumina, San Diego, CA, USA) by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). Raw FASTQ files were de-multiplexed using an in-house perl script, quality-filtered with fastp version 0.19.6 [26], and merged by splicing sequences using FLASH 1.2.7 [27]. Subsequently, based on the Silva classification database, the taxonomy of each representative operational taxonomic unit (OTU) sequence was analysed using RDP Classifier (version 2.2, with a confidence threshold of 0.7) to confirm the community composition of each sample [28]. Bioinformatics analysis of the soil microbiota was carried out using the Majorbio Cloud platform (https://cloud.majorbio.com, accessed on 7 October 2024). α-diversity (Mothur, version 1.30) and β-diversity (QIIME, version 1.8.0) analyses were performed to compare the differences in microbial diversity among treatments to evaluate the effects of rice straw return on the soil microbial community structure.

2.7. Data Analysis

A one-way or two-way analysis of variance (ANOVA) was performed to assess the statistically significant differences in the diversity indices among samples. Three biological replicates for each treatment were evaluated. The asterisks in the figures denote significant differences as follows: * p < 0.05; ** p < 0.01; and *** p < 0.001.

3. Results

3.1. Effects of Long-Term Straw Return on Soil Nutrient Characteristics

Long-term straw return at the single-cropping rice experimental base had a positive impact on the soil nutrient content (Table 1). In the sowing stages, the alkali-hydrolysed N content of SR was significantly increased to 119.26 and 117.46% in the 0–10 and 10–20 cm soil layers, respectively, compared to that of CK. The same tendency was observed in the two tested layers in the maturity stage. The alkali-hydrolysed N content was significantly higher under SR than under CK, showing an increase of 134.16 and 136.53%. A higher N content was observed in the maturity stage than in the sowing stage. The TOC content was higher under SR. However, no significant correlation was found between the specimens collected under SR, regardless of the sampling depth or growth stage. In contrast, the variation in available P and available K contents showed slight differences. During the first sampling stage, the available P content was notably enhanced to 115.72 and 115.00% in the 0–10 and 10–20 cm soil tillage layers, respectively, under SR compared to CK; in the maturity stage, it increased to 122.27 and 119.34%, respectively. However, the available P content in all tested samples showed a decrease with longer treatment time. Similarly to the available P content, compared to that under CK, the available K content of the tested samples under the SR treatment improved markedly but showed a decreasing trend with the increase in processing time. The CK values decreased from 220.79 and 219.24 mg/kg to 143.75 and 158.58 mg/kg, respectively. They also declined separately from 280.21 and 276.74 mg/kg to 188.39 and 206.56 mg/kg.

3.2. Disease Index Evaluation of Phytopathogenic Fungi in Paddy Field Experiments

Soil- and air-borne diseases are the principal factors affecting crop yield. In this study, to evaluate the impact of SR on the incidence of phytopathogenic fungi, disease indices for five pathogenic fungi, to which rice is susceptible in the northeastern region of China, were measured in the experimental field. In the field experiment, rice leaf blast and panicle neck blast caused the highest disease incidence (Figure 1a,b). In contrast, the rice sheath blight disease index was slightly lower than those of the above two fungi (Figure 1d). In addition, sheath rot disease and rice false smut shared the lowest incidence (less than 10) of all detected strains (Figure 1c,e). There were no remarkable differences in the disease indices of four plant diseases, namely panicle neck blast, sheath blight, sheath rot disease, and rice false smut, between CK and SR. However, there was a significant effect on the incidence of the rice leaf blast. Under SR, the disease index significantly improved, and the value increased from 23.48 to 27.73.

3.3. Variation in Grain Yield

As shown in Figure 2, no apparent difference was observed in the 1000-grain weight or panicles between SR and CK. In contrast, the number of spikelets per panicle and the grain filling performance of the samples varied under SR, thereby contributing to an overall increase in rice yield. For the 1000-grain weight, although there was no statistical difference between CK and SR with a random sampling approach, the 8-year average value of the experiment increased from 25.23 to 26.52 g, compared to that in CK (Figure 2c). Moreover, as shown in Figure 2a,b, SR improved the number of spikelets per panicle from 93.96 to 97.58 and enhanced grain filling from 88.11 to 91.44%, compared to CK. The increasing tendency of these detection indices is an important indicator for the effect on rice yield. In addition, this might have occurred because of the increase in alkali-hydrolysed N, available P, available K, and TOC in the soil, which improve the final yield of paddy rice, providing valuable insights into soil vitality. Therefore, the rice yield under SR ranged from 10,048.27 to 10,605.18 kg/ha, whereas under CK, it ranged from 8344.02 to 10,161.02 kg/ha. The samples under SR produced obviously greater grain yield over the 8 consecutive years, and the average value increased by 8.83% (Figure 2e). Furthermore, under SR, the total N in the plants was marginally higher than that under CK; however, the TOC increased significantly, further demonstrating that it resulted in a more sufficient nutrient supply for crop growth, thereby increasing yield (Figure S1). Similarly to these results, correlation analyses showed a strong and positive relationship between several crop yield indices and noticeable changes in soil nutrient content under SR. As shown in Figure S2, the alkali-hydrolysed N, TOC, and available P and K were significantly positively correlated with the number of spikelets per panicle, 1000-grain weight, and grain yield. And they also had essential influences on the total C and N contents in plants, which was evidenced by the high correlation values.

3.4. Soil Microbial Community Composition Under Continuous Straw Return

The α-diversity metrics utilising the Shannon and Simpson indices, which are essential indicators of microbial diversity and richness, revealed differences in the soil microbial community for all treatments sampled from different depths and growth stages. The α-diversity indices for the bacterial and fungal communities in the soil samples from each treatment are presented in Figure 3. Based on high-throughput sequencing data and bacterial microbial soil diversity analysis, the Shannon indices under SR were enhanced in both soil layers in the sowing stage compared to those in the natural soil (Figure 3a). In contrast to those under CK, these indices under SR first increased and then decreased to the minimum value with increasing soil depth in the maturity stage. Furthermore, a similar pattern was also observed in the diversity of fungal microorganisms (Figure 3b). The Shannon index was higher under SR than under CK, indicating that SR had a positive impact on the bacterial and fungal diversity. In addition, the Simpson index presented the opposite tendency compared to the Shannon index. Except for the detection results in the deeper layer (10–20 cm) from sampling in the maturity stage, the index was significantly lower under SR than under CK (Figure 3c,d). The Simpson index, which is associated with the richness of microbial communities and the relative proportion of species in a community, is based on probability theory. The lower the Simpson index is, the higher the microbial diversity in the micro-environment is. Based on these observations, the bacterial and fungal diversity under SR was also dramatically improved, assuming that straw return influenced the composition and abundance of soil communities.
Bacterial and fungal β-diversity were analysed to evaluate changes in the microbial community structure after straw return. The β-diversity metrics utilising principle coordinate analysis (Figure 4) revealed that for bacterial communities in the sowing and maturity stages, there were remarkable differences in the tested samples of soil microorganisms between CK and SR, in which PC1 explained 20.53 and 31.71% of the variation, respectively, and PC2 explained 19.29 and 20.79% of the variation, respectively (Figure 4a,c). Fungal communities in various stages also displayed apparent differences between the treatment group and control, with PC1 explaining 44.46 and 48.38% of the variation, respectively, and PC2 explaining 16.58 and 18.54% of the variation, respectively (Figure 4b,d). Additionally, a Venn diagram was employed to calculate the number of shared and unique OTUs among samples. The number of bacterial OTUs under SR in the sowing stage was 4229 in the 0–10 cm layer and 3836 in the 10–20 cm layer, whereas under CK, it was 3901 and 3660, respectively (Figure S3a). In the maturity stage, the number of unique bacterial OTUs was 3796 and 3602 under CK and 3854 and 3450 under SR in the 0–10 and 10–20 cm layers, respectively, which was lower than the number of shared bacterial OTUs during the sowing stage (Figure S3c). In contrast with the bacterial community, the number of unique fungal OTUs under CK was 757 and 435 in the 0–10 cm soil layer and 767 and 564 in the deeper soil layer. However, there were slight differences in the variation trend of the samples under SR. In the two stages, the value in the shallow soil revealed a clearly enhanced tendency, which then decreased in the deeper layer (Figure S3b,d). These statistical results show that, compared to that under the control group, the soil microbial composition of the different treatment groups under SR led to differences in the bacterial and fungal microbial composition in the soil, resulting in the significant promotion of microbial community diversity.
High-throughput sequencing and classification results revealed differences in bacteria and fungi at the phyla level among the treatments sampled in the sowing and maturity stages. In the sowing stage, Proteobacteria was the most dominant bacterial phylum under SR in the 0–10 (19.60%) and 10–20 cm soil layers (18.96%). This was distinguished from CK, in which the most abundant phylum was Chloroflexi (19.37%), followed by Actinobacteriota (18.61%), in the 0–10 and 10–20 cm soil layers. Chloroflexi had the highest relative abundance at the phylum level in all samples collected in the maturity stage, comprising 18.95–24.29% of the total sequences. It also displayed a significant upward trend in the microbial flora with the extension of planting time, in contrast to the control groups. Furthermore, the variation in Bacteroidota was similar to that in Chloroflexi in the majority of samples. In contrast, Acidobacteriota and Actinobacteriota were reduced with long-term treatment (Table S1). Regarding fungal communities, Basidiomycota was widely distributed in the 10–20 cm soil layer and was the most abundant bacteria phylum in all tested samples, and CK showed the highest abundance in the 10–20 cm soil layer, comprising 68.35% of the total sequences. Moreover, the abundance of Mortierellomycota increased significantly in the maturity stage, especially in the shallow soil layer. However, the opposite trend was observed for Ascomycota in all tested stages (Table S2).
Burkholderiales, Bacteroidales, Micrococcales, Rhizobiales, and Anaerolineales were the dominant bacterial orders in the soil samples (Figure 5), with a total concentration of the primary microbial community ranging from 29.23 to 45.16%. The value of all samples taken from different depths in the maturity stage exceeded 35% (Table 2). The relative abundance of Burkholderiales was 8.59–11.97%, on average, which was the highest in the majority groups, followed by Bacteroidales, with a mean relative abundance of 7.38–14.90%. The abundance of Burkholderiales was improved under SR in the sowing stage, especially in the deeper soil layer, but the opposite was observed in the maturity stage. Under SR, the relative abundance was significantly improved compared to that under CK, especially in the maturity stage. In addition, the relative abundances of Micrococcales and Anaerolineales clearly decreased under SR compared to CK. The data of disparate samples showed that a longer treatment time resulted in a significant increase in the abundance of Anaerolineales. The proportion of reads in the aforementioned microbial communities (Burkholderiales, Bacteroidales, Micrococcales, and Anaerolineales) changed dramatically, suggesting that rice straw return influenced the bacterial composition and abundance of soil communities.
In the field experiments, the fungal species composition analytical findings were visualised using stacked plots depicting the variation in community structure at the order level for all treatment groups taken in different plant growth stages. The fungal community was dominated by Filobasidiales in natural soils with or without straw return, showing ranges of 26.65–38.31% and 28.81–52.15%, respectively (Figure 6). There were no significant differences in the relative abundance of Filobasidiales between the control and treatment groups, except for the samples collected from the deeper soil layer in the sowing stage. The microorganisms with the second highest mean abundance across treatments sampled in the sowing stage were Thelebolales, which exhibited a significantly improved tendency under SR. The relative abundance of Mortierellales varied dramatically with long-term treatment, and a declined trend was detected under SR. In addition, SR improved the relative abundance of Pleosporales in the 10–20 soil layer in the sowing stage (Table 3). These findings reveal that SR promoted the fungal community in certain soil layers and crop growth periods, thereby changing their relative abundance.

4. Discussion

4.1. Effects of Long-Term Straw Return on Soil Fertility Quality and Rice Yield

Straw return has a positive influence on crop yield by affecting the absorption, transportation, utilisation, and accumulation of soil nutrients to a certain extent. In the past several decades, considerable scientific research has been conducted on the effects of straw return on crop yield, but the results are inconsistent [29,30]. To improve nutrient composition and enhance crop yields in albic soil, a field experiment with straw return was carried out for 8 consecutive years in northeast China. The results of this study showed that the nutrient content of alkali-hydrolysed N was markedly increased in comparison to that under CK in the 0–10 cm and 10–20 cm soil tillage layers, which shared a mean value range of 117.46–136.53% (Table 1). Typically, the straw return depth was greater than 20 cm, which is referred to as the deep application of straw. This method can be used for maize and wheat [13]. For rice, the depth is generally less than 20 cm [19]. In this research, a straw return depth less than 20 cm was used.
In alignment with existing research, straw return was shown to significantly increase the TOC content (Table 1), which provides essential organic C and altered the soil C:N ratio, enhancing soil fertility and supporting sustainable agricultural systems [31,32,33]. A meta-analysis of 446 datasets from various studies in China indicated that straw return increased the soil organic C (SOC) content by an average of 13.97% [31]. Furthermore, the duration of straw return is critical, with optimal outcomes observed within 6–9 years of continuous application, after which the benefits may decline [31]. This is corroborated by a global synthesis reporting an average SOC increase of 3.68 Mg C ha−1 due to straw return, with a corresponding C efficiency of 20.51% [32].
Additionally, straw return has been demonstrated to promote SOC accumulation over extended periods. In China, for example, increased straw return has resulted in significant SOC accumulation in croplands over the past 40 years (1980–2020), with an average national C sequestration rate of 27 Tg C yr−1 [33]. This long-term accumulation is crucial for enhancing soil health and mitigating climate change. Consistently with these findings, straw return is an effective management practice for regulating soil nutrients and reducing the loss of SOC, alkali-hydrolysed N, available P, and available K from agricultural soils. For example, in an experiment conducted by Zhao et al. [34], SOC varied from −0.96 to 5.83 mg/ha relative to the initial C stock, and the values in the 0–20 cm layer were higher than that in the deeper soil layers. Duvalet et al. [35] found a strong linear relationship between residue C input and SOC variation. Straw return, whether mixed into or buried in the soil, positively affected the supply of soil alkali-hydrolysed N, promoted the SOC and total N contents in the surface layer (0–10 cm), and enhanced the soil enzyme activity, significantly increasing grain yield with an average of 20.99 and 15.90% in different layers, respectively, especially under dry conditions [36]. The consistent application of straw in agricultural fields is a primary factor contributing to the enhancement of the soil’s available K content. During the plant growth cycle, particularly in the rapid growth stage, there is a substantial demand for K to facilitate various physiological processes, which primarily account for the reduction in the soil’s available K content. Furthermore, in northeast China, the plant growth period is predominantly from May to October. During this period, increased precipitation and irrigation practices significantly contribute to the depletion of available K in the soil.
The nutrient composition of soil fluctuates with the planting period. In this study (Table 1), the indices in all samples showed a declining tendency after long-term treatment, compared to after the sowing stage, which might be attributed to nutrient consumption during the physiological process of plant growth [37,38,39], including the development of floral buds and the production of shoot and root biomass. According to Wang [40], rice straw addition remarkably improved the labile P content in soil, and the residual P components in the soil were mostly stocked in an effective state, allowing direct absorption and utilisation by plants. In agreement with the reported results, straw return causes drastic fluctuations in the soil nutrient content [2], further demonstrating that it is a promising strategy for albic soil amendment. Furthermore, as expected, the number of spikelets per panicle and grain filling performance of the samples varied under SR, increasing by 93.96–97.58 g and 88.11–91.44%, respectively, compared to CK (Figure 2). With the improvement of these detection indices and the soil nutrient content, rice production was greatly improved in the experimental fields. Furthermore, correlation analysis revealed a significant positive correlation between the soil nutrients and crop yields and was also closely related to the total N and C contents in plants (Figure S1), demonstrating that the accumulation of soil nutrients resulting from successive straw return is a critical factor that directly contributes to the improvement of crop yield. Accordingly, continuous straw return is an effective method for disposing agricultural residues, improving the soil fertility of albic soil, and reinforcing the sustainability of the farming industry.

4.2. Long-Term Straw Return Drives Soil Microbial Community Changes

Soil microbial communities play an essential role in nutrient cycling and crucial physiological processes in plant growth. Maintaining the soil structure and its diversity is an extremely important index to evaluate soil quality. With continuous straw return to the paddy field, the relative abundance and diversity of bacteria and fungi detected using high-throughput sequencing technology were changed significantly. In bacterial communities, Proteobacteria, Chloroflexi, Acidobacteriota, Actinobacteriota, and Bacteroidota predominated at the phylum level (Table S1), and this result agrees with previous studies in agricultural soils [41,42]. These five categories of microorganisms accounted for more than 70% of all bacteria in all treatment groups. Among these, Proteobacteria, which actively participates in the process of soil denitrification and the iron cycle [43,44], was the most dominant bacterial phylum under SR in the 0–10 (19.60%) and 10–20 cm soil layers (18.96%) in the sowing stage, showing an increasing trend compared to under CK. The relative abundances of Bacteroidales in Bacteroidota increased significantly at high levels of straw addition in the 10–20 cm soil layer (Table 2), functioning as a biological indicator to evaluate agricultural soil utilisation [45] and a degrader of refractory crystal structure [46]. The average richness of Anaerolineales in Chloroflexi (Table 2) declined compared with that in CK, and the abundance in the maturity stage was significantly higher than that in the sowing stage (Table 2). Chloroflexi species are well known due to their ability to facilitate lignocellulose in straw [47]. Furthermore, Actinobacteriota and Micrococcales, which produce a variety of secondary metabolites with antibacterial ability, were markedly reduced under SR [48]. The disease index of rice leaf blast was significantly improved (from 23.48 to 27.73) under SR (Figure 1a), indicating that straw return provides good circumstances for pathogen growth and increases the risk of disease epidemic outbreaks [49]. At the fungal phylum level, the dominant phyla were Basidiomycota and Ascomycota, and the relative abundance of Ascomycota, which can produce luxuriant cellulose and lignin to decompose organic matter in the soil, was significantly increased in the deeper soil layer [50]. The order Thelebolales is important in the phylum Ascomycota; in this study, the mean abundance of Thelebolales was influenced by straw return (Table 3). Previous research has demonstrated that several species under this taxon generate antifreeze proteins and secondary metabolites and are promising valuable resources for the development of biotechnology [51].
The activity of microorganisms depends on soil parameters, such as humidity, temperature, and the pH. The experimental site is situated in the northeastern region of China, which characterised by a cold temperate climate zone. As elaborated in Section 2.1, the site’s key climatic parameters, including the mean annual temperature, annual precipitation, frost-free period, and annual active temperature, are based on 8-year-average data (2016–2023). This approach accounts for interannual climatic variability and ensures robust characterisation of the experimental environment. The albic soils at this location inherently possess low levels of organic matter, N, and P, making them representative of the region’s typical low-fertility soils. Consequently, although changes in soil nutrient composition over the 8-year period were not individually detailed in this study, they were assessed in terms of the cumulative effects resulting from successive straw return.

5. Conclusions

In the rice planting field, the experimental results concerning the soil nutrient content indicated that SR significantly enhanced SOC, available P, alkali-hydrolysed N, and available K accumulation, compared to CK. In comparison to the CK treatment, SR positively influenced the number of spikelets per panicle and grain filling, contributing to an overall increase in rice yield. The significant alterations in nutrient composition in albic soil represent another major factor contributing to the substantial fluctuations observed in crop yield-related indices. Soil microbial community analyses showed that SR had varying effects on soil microbial diversity and community structure in albic soil, enhancing the proliferation of bacteria and fungi in specific soils. For example, compared to CK, the SR treatment demonstrated greater efficacy in increasing the relative abundance of Bacteroidales in the deeper soil layers of samples collected in both the sowing and maturity stages. Conversely, the concentrations of the other two predominant species, Anaerolineales and Micrococcales, demonstrated a declining trend under SR. In terms of the fungal community, Thelebolales, which represented the second highest mean abundance among microorganisms, exhibited a significantly increasing trend under SR. In contrast, the variation trend of Mortierellales was opposite to that of Thelebolales under SR in the maturity stage. Collectively, these findings suggest that straw incorporation may positively influence the enhancement of nutrient composition in albic soil and offer potential environmental benefits.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agronomy15061404/s1, Figure S1. The effect of continuous straw return to the field on the amount of plant nutrients. The data are presented as the mean ± SEM. The degree of significance is indicated as *, p < 0.05. Figure S2. Correlation analysis between crop yield and the nutrients in the soil and plants. Figure S3. Venn diagrams of the OTU distribution of the 16S rRNA gene (a,c) and the ITS gene (b,d) of the treatments sampled in diverse soil layers and growth stages. Note: nr: no rice straw return in the sowing stage; sr: rice straw return in the sowing stage; hnr: no rice straw return in the maturity stage; hsr: rice straw return in the maturity stage. Table S1. Relative abundance of bacteria at the phylum level (the richest microorganism) in paddy soil among the eight treatments. Table S2. Relative abundance of fungi at the phylum level (the richest microorganism) in paddy soil among the eight treatments.

Author Contributions

J.M. and Q.W. contributed to the concept and design. J.M. performed the research and analysed the data. J.M. and J.Z. wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (Grant number 2022YFD1500800) and Central Leading Local Science and Technology Development Project (SBZY2024E010-02).

Data Availability Statement

Please contact the author to request the data.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

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Figure 1. Disease index evaluation of rice leaf blast (a), panicle neck blast (b), sheath rot disease (c), rice sheath blight (d), and rice false smut (e). CK: no rice straw return; SR: rice straw return. NS: no significant difference; *** p < 0.001.
Figure 1. Disease index evaluation of rice leaf blast (a), panicle neck blast (b), sheath rot disease (c), rice sheath blight (d), and rice false smut (e). CK: no rice straw return; SR: rice straw return. NS: no significant difference; *** p < 0.001.
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Figure 2. Effects of rice straw return on crop yield and its components in the experimental paddy field (2023). (a) Number of spikelets per panicle. (b) Grain filling (%). (c) 1000-grain weight (g). (d) Panicles (×104/ha). (e) Grain yield ((kg/ha). Note: CK: no rice straw return. The data are presented as the mean ± SEM. The degree of significance is indicated as * p < 0.05.
Figure 2. Effects of rice straw return on crop yield and its components in the experimental paddy field (2023). (a) Number of spikelets per panicle. (b) Grain filling (%). (c) 1000-grain weight (g). (d) Panicles (×104/ha). (e) Grain yield ((kg/ha). Note: CK: no rice straw return. The data are presented as the mean ± SEM. The degree of significance is indicated as * p < 0.05.
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Figure 3. α-diversity of soil bacterial and fungal communities among the treatments sampled in the sowing and maturity stages. Shannon index of bacterial microorganisms in different soil layers (a). Shannon index of fungal microorganisms in different soil layers (b). Simpson index of bacterial microorganisms in different soil layers (c). Simpson index of fungal microorganisms in different soil layers (d).
Figure 3. α-diversity of soil bacterial and fungal communities among the treatments sampled in the sowing and maturity stages. Shannon index of bacterial microorganisms in different soil layers (a). Shannon index of fungal microorganisms in different soil layers (b). Simpson index of bacterial microorganisms in different soil layers (c). Simpson index of fungal microorganisms in different soil layers (d).
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Figure 4. Principle coordinate analysis to evaluate the influence of straw addition on bacterial and fungal β-diversity in diverse soil layers and growth stages. Statistical pairwise comparisons were performed using the Adonis method (p < 0.05, permutation = 999). Comparison of bacterial (a) and fungal (b) communities between the control group and the straw return treatment in the sowing stage. Comparison of bacterial (c) and fungal (d) communities between the control group and the straw return treatment in the maturity stage. Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 and sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
Figure 4. Principle coordinate analysis to evaluate the influence of straw addition on bacterial and fungal β-diversity in diverse soil layers and growth stages. Statistical pairwise comparisons were performed using the Adonis method (p < 0.05, permutation = 999). Comparison of bacterial (a) and fungal (b) communities between the control group and the straw return treatment in the sowing stage. Comparison of bacterial (c) and fungal (d) communities between the control group and the straw return treatment in the maturity stage. Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 and sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
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Figure 5. Taxonomic classification and relative abundance of bacterial communities at the order level. (a). Bacterial communities in the sowing stage. (b). Bacterial communities in the maturity stage. Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 nad sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
Figure 5. Taxonomic classification and relative abundance of bacterial communities at the order level. (a). Bacterial communities in the sowing stage. (b). Bacterial communities in the maturity stage. Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 nad sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
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Figure 6. Stacked plots of fungal community distribution at the order level. (a). Fungal community in the sowing stage. (b). Fungal community in the maturity stage; effects of straw returned on the relative abundance of soil microorganism. The relative abundance of Filobasidiales, Thelebolales, Mortierellales, and Pleosporales at the order level in the sowing and maturity stages (Table 2, n = 3). Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 and sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
Figure 6. Stacked plots of fungal community distribution at the order level. (a). Fungal community in the sowing stage. (b). Fungal community in the maturity stage; effects of straw returned on the relative abundance of soil microorganism. The relative abundance of Filobasidiales, Thelebolales, Mortierellales, and Pleosporales at the order level in the sowing and maturity stages (Table 2, n = 3). Note: nr10 and nr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; sr10 and sr 20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the sowing stage; hnr10 and hnr20: no rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage; hsr10 and hsr20: rice straw return sampled in the 0–10 and 10–20 cm soil layers, respectively, in the maturity stage.
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Table 1. Influence of different treatments on the alkali-hydrolysed nitrogen, available phosphorus, available potassium, and total organic carbon contents in paddy fields. Note: CK: no rice straw return; SR: rice straw return.
Table 1. Influence of different treatments on the alkali-hydrolysed nitrogen, available phosphorus, available potassium, and total organic carbon contents in paddy fields. Note: CK: no rice straw return; SR: rice straw return.
PeriodDepth
(cm)		TreatmentAlkali-Hydrolysed Nitrogen (mg/kg)Available
Phosphorus (mg/kg)		Available
Potassium (mg/kg)		Total Organic
Carbon (%)
Sowing stage0–10CK87.82 ± 4.3044.13 ± 0.74220.79 ± 9.853.16 ± 0.04
SR104.73 ± 4.6151.07 ± 0.86280.21 ± 4.823.71 ± 0.08
10–20CK86.32 ± 6.1744.18 ± 0.66219.24 ± 5.933.14 ± 0.06
SR101.39 ± 4.1050.81 ± 1.02276.74 ± 7.983.68 ± 0.06
Maturity stage10–20CK83.89 ± 5.5337.59 ± 0.56143.75 ± 5.303.15 ± 0.06
SR112.55 ± 1.9845.96 ± 0.36188.39 ± 6.963.80 ± 0.08
0–10CK81.91 ± 4.7837.53 ± 0.65158.58 ± 4.373.14 ± 0.04
SR111.83 ± 3.6644.79 ± 0.72206.56 ± 6.473.76 ± 0.07
Table 2. Relative abundance of bacteria and fungi at the order level in paddy soil sampled in the sowing stage. Note: CK: no rice straw return; SR: straw return.
Table 2. Relative abundance of bacteria and fungi at the order level in paddy soil sampled in the sowing stage. Note: CK: no rice straw return; SR: straw return.
1 0–10 cm10–20 cm
KingdomOrderCKSRCKSR
BacteriaBurkholderiales0.0933 ± 0.04110.0963 ± 0.02210.0904 ± 0.02570.1153 ± 0.0280
Bacteroidales0.0800 ± 0.00660.0738 ± 0.00930.0768 ± 0.01480.1098 ± 0.0334
Micrococcales0.0619 ± 0.01160.0438 ± 0.01710.1356 ± 0.06540.0462 ± 0.0193
Rhizobiales0.0524 ± 0.00550.0644 ± 0.01430.0496 ± 0.00340.0494 ± 0.0063
Anaerolineales0.0612 ± 0.02360.0429 ± 0.01770.0412 ± 0.01980.0345 ± 0.0119
FungiFilobasidiales0.3890 ± 0.18080.3274 ± 0.10380.5215 ± 0.09390.3201 ± 0.0317
Thelebolales0.0935 ± 0.05220.1117 ± 0.03120.0852 ± 0.01600.1345 ± 0.0374
Pleosporales0.0514 ± 0.07190.0413 ± 0.04570.0119 ± 0.00580.0844 ± 0.0834
Mortierellales0.0595 ± 0.03190.1034 ± 0.03220.0569 ± 0.00940.0712 ± 0.0622
Table 3. Relative abundance of bacteria and fungi at the order level in paddy soil sampled in the maturity stage. Note: CK: no rice straw return; SR: straw return.
Table 3. Relative abundance of bacteria and fungi at the order level in paddy soil sampled in the maturity stage. Note: CK: no rice straw return; SR: straw return.
0–10 cm10–20 cm
KingdomOrderCK SR CK SR
BacteriaBacteroidales0.0840 ± 0.02800.0735 ± 0.01700.1161 ± 0.00990.1489 ± 0.0245
Burkholderiales0.1187 ± 0.00500.0953 ± 0.01380.1111 ± 0.02130.0859 ± 0.0094
Anaerolineales0.1224 ± 0.02860.1055 ± 0.02780.0872 ± 0.05300.0817 ± 0.0301
Rhizobiales0.0408 ± 0.00330.0542 ± 0.01480.0470 ± 0.01810.0495 ± 0.0207
Micrococcales0.0505 ± 0.02330.0360 ± 0.02380.0369 ± 0.01910.0224 ± 0.0092
FungiFilobasidiales0.2881 ± 0.22780.2665 ± 0.03660.4108 ± 0.06410.3831 ± 0.0968
Mortierellales0.3456 ± 0.47930.2383 ± 0.05180.1035 ± 0.04620.0697 ± 0.0465
Thelebolales0.1385 ± 0.1710 0.1061 ± 0.01880.1018 ± 0.06970.1809 ± 0.1254
Pleosporales0.0030 ± 0.00140.0071 ± 0.00560.0703 ± 0.11190.0053 ± 0.0050
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Ma, J.; Wang, Q.; Zou, J. Effects of Continuous Straw Return on Soil Nutrients and Microbial Community Structure of Paddy Fields in Northeast China. Agronomy 2025, 15, 1404. https://doi.org/10.3390/agronomy15061404

AMA Style

Ma J, Wang Q, Zou J. Effects of Continuous Straw Return on Soil Nutrients and Microbial Community Structure of Paddy Fields in Northeast China. Agronomy. 2025; 15(6):1404. https://doi.org/10.3390/agronomy15061404

Chicago/Turabian Style

Ma, Juntao, Qiuju Wang, and Jiahe Zou. 2025. "Effects of Continuous Straw Return on Soil Nutrients and Microbial Community Structure of Paddy Fields in Northeast China" Agronomy 15, no. 6: 1404. https://doi.org/10.3390/agronomy15061404

APA Style

Ma, J., Wang, Q., & Zou, J. (2025). Effects of Continuous Straw Return on Soil Nutrients and Microbial Community Structure of Paddy Fields in Northeast China. Agronomy, 15(6), 1404. https://doi.org/10.3390/agronomy15061404

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