1. Introduction
The utilization of greenhouse production system (protected cropping) is crucial in addressing the growing global food demand, considering the challenges posed by global climate change. These systems offer sustainability and high productivity, making them essential. Greenhouse vegetable production has made significant contributions to China agricultural. However it relies heavily on fertilizer and water input, which places a considerable burden on the environment and ecology [
1,
2]. China, as the top vegetable-producing nation, achieved a staggering production of million tons of vegetables in 2017, representing for 51.2% of the global vegetables yield [
3,
4]. In comparison to open-field production systems, greenhouses have demonstrated a remarkable capacity to enhance vegetable yields. By artificially manipulating temperature and employing higher levels of fertilizer and water inputs, greenhouses can successfully produce off-season vegetables regardless of the specific climate type or region in China.
Nevertheless, the extensive use of chemical fertilizers and pesticides in greenhouses has led to significant soil and ecological issues [
1,
2]. Applying substantial quantities of chemical fertilizers and pesticides is deemed crucial in achieving high yields of greenhouse vegetables. Nonetheless, this approach fails to provide a sustainable means of consistently improving soil fertility or effectively managing pests and diseases. Numerous studies have demonstrated that prolonged utilization of chemical fertilizer and pesticide application in greenhouses leads to soil acidification, salinization and degradation [
5]. Additionally, it leads to the accumulation of heavy metals [
6], and severe pollution of groundwater and irrigation water [
7], Furthermore, it results in a decline in soil microbial diversity and enzyme activity [
8]. A multitude of studies have substantiated the excessive application of pesticides in greenhouses as a response to diseases and insect pests influenced by high temperature and humidity [
9,
10,
11].
Organic cultivation serves as a sustainable agricultural production system that enhances soil fertility, biodiversity and human health. It achieves this by prohibiting the utilization of chemical synthetics and instead emphasizes the application of organic waste or crop rotation [
12,
13]. Hence, organic cultivation is regarded as an advantageous and viable alternative to intensive agriculture, playing a significant role in the pursuit of sustainable agricultural development.
Soil aggregates, consisting of the coupling of mineral particles and organic substances, serve as fundamental units of soil structure and function [
14]. Aggregates of varying sizes exhibit distinct properties and functions. For instance, macro-aggregates (>0.25 mm) contain a higher abundance of labile organic substances and fresh litter, which are more readily decomposed by microorganisms. In contrast, stable organic carbon within micro-aggregates (<0.25 mm) is characterized by greater stability and reduced accessibility for biological degradation. Nevertheless, the prolonged use of chemical fertilizers and pesticides can detrimentally impact soil structure, disrupt the distribution of soil aggregates, and diminish their stability [
15]. SOC plays a crucial role in their formation and stability of soil aggregates by acting as a binding agent, with its properties influencing the process of aggregate formation and evolution.
Organic cultivation practices, including the application of organic fertilizer, crop rotation, and integrated management, exhibit a favorable impact on the content of SOC. Maintaining the dynamic equilibrium of SOC is of paramount importance in enhancing soil structure, soil quality, and mitigating global climate change [
16,
17]. Organic farms demonstrated significantly higher concentrations, stocks, and rates of soil organic carbon (SOC) sequestration in comparison to conventional farms [
12]. This highlights organic cultivation as a crucial approach in reducing greenhouse gas emissions. The labile organic carbon (LOC) fractions exhibit greater sensitivity to changes in agricultural practices compared to SOC, and they demonstrate a stronger correlation with soil fertility, soil microbial activity, and crop yield [
18]. LOC pool comprises easily oxidizable carbon (EOC), microbial biomass carbon (MBC), light fraction organic carbon (LFOC), and dissolved organic carbon (DOC) [
19,
20]. Research studies have demonstrated that organic cultivation practices not only increase the content of SOC, but also enhances the levels of labile organic carbon fractions [
19,
21]. In addition, organic farming practices have been shown to sustain long-term higher fertility, enhances soil microbial diversity, provide protection against pathogen infections, and facilitates the degradation of pollutants [
12,
22,
23].
Soil microorganisms play a critical role as the principal agents in the synthesis of soil organic matter. They actively contribute to the formation of soil aggregates, which in turn promotes the accumulation and long-term stability of SOC. Soil aggregates of varying particle sizes exhibit diverse physical and chemical properties, leading to a heterogeneous distribution of microbial communities and substrate availability [
24]. Soil microbial communities residing within soil aggregates play a pivotal role in energy transfer and nutrient cycling processes, with their mycelia facilitating the formation and stability soil aggregation. The microbial community structure in soil aggregates serves as a significant indicator for assessing soil carbon sequestration and ecological functionality [
25,
26]. Enzyme activity is a sensitive parameter that accurately reflects carbon turnover dynamics within the soil and serves as a valuable biological indicator for assessing soil fertility [
27]. The activity of enzyme is subject to the influence microbial communities, thereby impacting the conversion of various organic carbon forms within aggregates [
28]. Consequently, significant variations in both the organic carbon content and availability exist among soil aggregates of different particle sizes, thereby governing the distribution of enzyme activity within these aggregates [
29].
Agricultural fertilization stands as the foremost influential factor in promoting the enhancement of soil aggregates [
30]. Organic fertilizers possess a substantial quantity of organic matter, and the increment in soil organic carbon content facilitates the formation of macro-aggregates while augmenting the physical safeguarding of organic matter [
31]. However, limited research has been conducted to explore the impacts of organic cultivation on the intricate interplay among organic carbon fractions, microbial community composition, and enzyme activity at the aggregate level.
In this study, we employed a16-year long-term field experiment in greenhouses in Quzhou County, Hebei Province, China. The experiment involved organic, integrated, and conventional cultivation management. The objectives of this study were to: (i) examine the distribution patterns of organic carbon fractions and microbial community structure across various particle sizes, (ii) investigate how organic cultivation practices can enhance soil function through alterations in soil aggregates, and (iii) elucidate the mechanisms underlying carbon sequestration in organic cultivation systems. This study primarily emphasizes the impact of organic cultivation on both microbial community composition and SOC at the aggregate level, as well as the sequestration of SOC at the larger-scale bulk soil level. Additionally, it explores the relationships between these factors and vegetable yield within the greenhouse setting.
2. Materials and Methods
2.1. Study Site
In March 2002, a long-term experiment was commenced at the Quzhou Experimental Station of China Agricultural University (latitude: 36°52'N, longitude: 115°01'E), situated in the northern region of Quzhou County, Hebei Province, China. This region exhibits a temperate, semi-humid continental monsoon climate, with an average temperature of 13.1℃. The average annual rainfall in this region amounts to 556.2 mm, with the majority of it occurring between the months of July and September. This period accounts for approximately one-third of the total annual rainfall. The solar greenhouse utilized in this study had dimensions of 7 × 52 m (
Figure 1). The soil under analysis was salinized cinnamon soil. Prior to the long-term experiment, the soil at the experimental site consisted of 54.11% sand, 28.45% silt, and 17.44% clay. The physicochemical properties of the topsoil (0-20 cm) under various cultivation practices in 2002 are presented in
Table 1.
The experiment investigating greenhouse vegetable cultivation entailed three methods: conventional cultivation (CC), integrated cultivation (IC), and organic cultivation (OC). A two-season vegetable rotation was implemented within the greenhouses, with the specific types of vegetables planted each year as indicated in
Table S1. Conventional cultivation (CC) followed local traditional management practices. The primary fertilizer utilized is chemical fertilizer, with a small amount of organic fertilizer used as supplementation. Insecticides (such as triazophos, imidacloprid, and abamectin) and fungicides (such as azoxystrobin, propineb, carbendazim, and mancozeb) are employed for pest and disease control.
The chemical fertilizer application rate is 4 t ha-1 year-1, while the organic fertilizer application rate is 13.4 t ha-1 year-1. The chemical fertilizers used comprised of urea (46% N), calcium superphosphate (12% P2O5), potassium sulfate (50% K2O), and diammonium phosphate (18% N and 46% P2O5), with a mixing ratio of 3:4:5. The fertilization approach for integrated cultivation (IC) combines organic and chemical fertilizers, while biological control is primarily employed for pest and disease prevention, supplemented with the application of insecticides and fungicides in severe cases (similar to conventional farming practices). In this system, the utilization of chemical fertilizers and pesticides is reduced by 50% compared to conventional cultivation (CC). The types and mixing ratios of chemical fertilizers remain consistent with conventional cultivation (CC). The application rate of organic fertilizer is reduced by 50% compared to organic cultivation (OC). Strict adherence to organic management principles in OC prohibits the use of chemical fertilizers, pesticides, and any hormonal substances. Only organic fertilizers are applied, in conjunction with artificial control, sulfur fumigation, high temperature enclosed structures, and biological pesticides, to prevent and control pests and diseases.
Organic fertilizers are produced through a high-temperature composting process and primarily comprise local organic waste, such as chicken manure, cow manure, and straw. The application rate of organic fertilizer is 59.2 t ha
-1 year
-1. The nutrient content of organic fertilizer on a dry basis is 1.21% N, 0.60% P
2O
5, and 1.58% K
2O. The crops were fertilized three times per season, with one application of basal manure and two applications of top dressing. The irrigation in the greenhouses was centrally managed. The management of the three greenhouses was conducted simultaneously, utilizing flood irrigation as the irrigation method. Details regarding nutrient input, pesticide application, and irrigation under various cultivation methods are provided in
Table S2.
2.2 Soil Sampling and Aggregate Size Fractionation
Undisturbed soil samples were collected from three cultivation types (CC, IC, OC) at a depth of 0-20 cm on May 11, 2018. Sampling was conducted in each greenhouse following an "S" shape pattern, with a composite soil sample being created by combining every five points sampled. Finally, the average samples obtained using the quarter method were homogenized, carefully disassembled along the natural fracture points, and sieved through a 5-mm mesh. Plant and organic residues in the sieved soil were meticulously extracted using forceps. The soil samples needed for enzyme activity analysis were stored in a refrigerator at a temperature of 4℃. Subsamples weighing 200 g were subsequently subjected to shaking through sieving devices with pore diameters of 2 and 0.25 mm for a duration of 5 minutes, resulting in the separation of three size fractions: <0.25 mm (micro-aggregates), 2-0.25 mm (small macro-aggregates), and >2 mm (large macro-aggregates). The sieved soil was divided into two portions: one portion was stored at 4 ℃ for the analysis of soil enzyme activity and microbial community composition, while the other portion was utilized for the analysis of organic carbon fractions. The mean weight diameter (MWD in mm) was employed to assess aggregate stability, which was calculated using Eq (1) as described by Fattet [
32].
Where Xi represents the mean diameter of the size fractions (mm) and represents the proportion of the size fraction in the entire soil sample (%).
2.3 Soil Organic Carbon Fractions Analyses
The soil organic carbon (SOC) content was determined using the K
2Cr
2O
7 oxidation method. Specifically, 5 mL of 0.8 M K
2Cr
2O
7 solution and 5 mL of concentrated H
2SO
4 were added to the pre-weighed soil sample. The mixture was subsequently heated to boiling at a temperature range of 170℃-180℃ for a duration of 5 minutes. The residual K
2Cr
2O
7 solution was titrated using 0.2 M FeSO
4. The soil particulate organic carbon (POC) content was determined using the method outlined by Cambardella and Elliott in their publication from May-June 1992[
33]. In summary, 20 g of each soil aggregate fraction was dispersed in 100 mL of sodium hexametaphosphate by agitation with a reciprocating shaker for a duration of 18 hours. The resulting soil suspension was passed through a 53-μm sieve under distilled water to facilitate separation. All the material retained on the sieve was transferred onto a dry dish, subjected to oven-drying at 60℃ for 12 hours, and subsequently ground to determine the carbon (C) content of the dried particulate. The organic carbon (C) concentrations within the POC samples were determined using the potassium dichromate oxidation method.
The extractable organic carbon (EOC) content was estimated using the method described by Blair et al. in their publication from 1995. Furthermore, 1.5 g of each soil aggregate fraction was accurately weighed and transferred into plastic screw-top centrifuge tubes. Subsequently, 25 mL of 1/3 mol L-1 KMnO4 solution was added to each tube. All the tubes were securely sealed, agitated for a duration of 1 hour, and then centrifuged for 5 minutes at a speed of 3000 rpm. The supernatant was then diluted with deionized water, and the carbon (C) content was measured through colorimetry at a wavelength of 565 nm. Finally, the change in KMnO4 concentration was utilized to quantify the amount of carbon dioxide, based on the assumption that 1 mM of KMnO4 was consumed during the oxidation of 9 g of carbon (C).
2.4 Soil Enzyme Activities Analyses
The methods employed for measuring the activities of invertase, catalase, urease, and cellulase were as follows:
Urease: 5 g of dry soil was subjected to incubation with 20 mL of a 10% urea solution, 20 mL of citric acid buffer at pH 6.7, and 1 mL of toluene for a duration of 24 hours at 37℃ in the absence of light. Following the incubation, the soil suspension was filtered, and 3 mL of the filtrate was employed to determine the concentration of ammonium ions using the indophenol-blue colorimetric method. The activity of urease was expressed by the unit of mg kg-1 24 h-1.
Catalase: 2 g of fresh soil, 40 mL distilled water, and 5 mL of 0.3% hydrogen peroxide solution were shaken for 20 minutes. The activity of urease was expressed in units of mg kg-1 24 h-1. For catalase assay, 2 g of fresh soil, 40 mL of distilled water, and 5 mL of a 0.3% hydrogen peroxide solution were vigorously shaken for a duration of 20 minutes. Following the shaking step, 5 mL of 3 M sulfuric acid was introduced to the mixture, and the resulting soil suspension was subsequently filtered. Moreover, a 25-mL portion of the filtrate was utilized to determine the quantity of hydrogen peroxide through titration with 0.1 M potassium permanganate. The activity of catalase was expressed in units of mg g-1. Invertase: A total of 5 g of fresh soil was subjected to incubation with 15 mL of an 8% sucrose solution, 5 mL of phosphate buffer at pH 5.5, and five drops of toluene for a duration of 24 hours at 37℃ in the absence of light. Following the incubation, the soil suspension was filtered, and 1 mL of the filtrate was utilized to quantify the amount of glucose produced using the 3,5-dinitrosalicylic acid colorimetric method. The activity of invertase was expressed in units of mg g-1 24 h-1.
Cellulase: A total of 10 g of fresh soil was subjected to incubation with 20 mL of a 1% carboxymethyl cellulose solution, 5 mL of phosphate buffer at pH 5.5, and a toluene solution of carboxymethyl cellulose for a duration of 72 hours at 37℃ in the absence of light. Immediately following the incubation, the soil suspension was filtered, and 1 mL of the filtrate was employed to quantify the amount of glucose produced using the 3,5-dinitrosalicylic acid colorimetric method. The activity of invertase was expressed in units of mg kg-1 72 h-1.
2.5 High-Throughput Sequencing
The soil microbial communities at different aggregate levels were analyzed for high-throughput sequencing in different cultivations. The Fast DNA Spin Kit (MP Biomedicals, USA) was employed for soil DNA extraction, and the purity and concentration of the extracted DNA were assessed using 1% agarose gel electrophoresis. The DNA was diluted with sterile water in centrifuge tubes to a concentration of 1 ng μl
-1. The diluted DNA was used to amplify the hypervariable regions V3-V4 of the bacterial 16S rRNA gene using primers 341F and 806R. Additionally, the fungal ITS gene was amplified using primers ITS1-1F-F and ITS1-1F-R. The primer sequences for bacteria and fungi were provided in
Table S3. Moreover, the PCR reactions were presented in
Table S4, while the reaction program was displayed in
Table S5. Subsequently, the PCR products were combined and purified using a GeneJET purification kit (Thermo Fisher Scientific, USA). The raw sequences underwent quality screening and trimming using Cut adapt. The chimeric sequences were identified and removed using the UCHIME algorithm [
34]. Bacterial and fungal operational taxonomic units (OTUs) were clustered at a sequence similarity threshold of 97% using UPARSE. The SSUrRNA database and the Unit database were utilized for bacterial and fungal OTU annotation analysis, respectively [
35].
2.6 Statistical Analysis
All data were analyzed using Microsoft Excel (2016) (Microsoft, USA) and GraphPad Prism 8.0.2. Furthermore, a one-way analysis of variance (ANOVA) was utilized to evaluate the impact of various cultivations on soil aggregate distribution, as well as the content of organic carbon fractions mediated by aggregates, enzyme activity, and microbial activity. Multiple comparisons were conducted using a one-way ANOVA with a Tukey's HSD post hoc test in SPSS 20.0. Structural Equation Modeling (SEM) was employed to analyze the internal relationships between soil organic carbon fractions, enzyme activities, microbial community, and vegetable yield.
Figure 1.
Location of the experimental site and the picture of a greenhouse for organic cultivation.
Figure 1.
Location of the experimental site and the picture of a greenhouse for organic cultivation.
Figure 2.
Soil aggregate distribution, mean weight diameter of aggregates under different cultivation treatments. Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 2.
Soil aggregate distribution, mean weight diameter of aggregates under different cultivation treatments. Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 3.
The concentration of SOC, EOC, and POC in three size classes of soil aggregate under different cultivation treatments. The values denote the means of three replicates (±SE). Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 3.
The concentration of SOC, EOC, and POC in three size classes of soil aggregate under different cultivation treatments. The values denote the means of three replicates (±SE). Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 4.
The sucrase, cellulase, urease and catalase activities of three soil aggregate-size classes under different cultivation treatments. Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 4.
The sucrase, cellulase, urease and catalase activities of three soil aggregate-size classes under different cultivation treatments. Capital letters indicate significant differences among different cultivation treatments for each of the aggregate size classes (p<0.05), while lower letters indicate significant differences among aggregate size fractions in the same cultivation treatments (p<0.05).
Figure 5.
Heatmap of bacteria (a) and fungi (b) at phylum level in different particle sizes of aggregates under different cultivation treatments.
Figure 5.
Heatmap of bacteria (a) and fungi (b) at phylum level in different particle sizes of aggregates under different cultivation treatments.
Figure 6.
Vegetable yield in spring and autumn during CC, IC and OC treatments. OC (Organic cultivation); IC (integrated cultivation); and CC (Conventional cultivation). The values denote the means of three replicates (±SE).
Figure 6.
Vegetable yield in spring and autumn during CC, IC and OC treatments. OC (Organic cultivation); IC (integrated cultivation); and CC (Conventional cultivation). The values denote the means of three replicates (±SE).
Figure 7.
SEM showing that different cultivation treatments affect soil aggregates, soil organic fractions, microbial diversity, enzyme activities and vegetable yield: (a) CC, (b) IC and (c) OC. Red lines indicate a negative association, and blue lines indicate a positive association (*, p < 0.05; **, p < 0.01; ***, p < 0.001). The numbers reflect the normalized path coefficients.
Figure 7.
SEM showing that different cultivation treatments affect soil aggregates, soil organic fractions, microbial diversity, enzyme activities and vegetable yield: (a) CC, (b) IC and (c) OC. Red lines indicate a negative association, and blue lines indicate a positive association (*, p < 0.05; **, p < 0.01; ***, p < 0.001). The numbers reflect the normalized path coefficients.
Table 1.
The physicochemical properties of top soil (0-20 cm) under different cultivation in 2002.
Table 1.
The physicochemical properties of top soil (0-20 cm) under different cultivation in 2002.
Treatments |
SOC g kg-1
|
Total N g kg-1
|
Total P g kg-1
|
Available N mg kg-1
|
Available P mg kg-1
|
Available K mg kg-1
|
OC |
11.08 |
1.17 |
1.38 |
101.28 |
139.13 |
257.30 |
IC |
9.60 |
1.19 |
1.24 |
95.35 |
81.68 |
364.28 |
CC |
12.18 |
1.36 |
2.22 |
128.38 |
163.05 |
212.83 |