Effects of Biochar on the Microenvironment of Saline-Sodic Soil and Maize Growth

Abstract

Biochar is a valuable soil amendment substance. However, no systematic study has investigated the effects of biochar on the microenvironment of saline-sodic soils and maize yield in cold areas of Heilongjiang Province. We investigated variations in soil physicochemical properties, soil bacterial and fungal community structure, maize root formation, plant dry matter accumulation, grain filling rate, and maize yield in saline soils treated with biochar (0, 20, 40, and 80 t/ha). Biochar improved saline soil properties and structure, slightly decreasing bulk density and pH and increasing the water-stable aggregate stabilization rate. Furthermore, the relative abundances of Sphingomonas, Lysobacter, Nitrospira, and Gemmatimonas and the fungal genus Guehomyces were increased, promoting the conversion of soil organic carbon and available nitrogen and phosphorus. Moreover, biochar reduced the relative abundance of some fungal pathogenic genera, including Fusarium, Gibberella, Cladosporium, Alternaria, and Epicoccum. However, shifts in soil bacterial and fungal community structure were indirectly driven by biochar-induced changes in soil physicochemical properties, with organic carbon as the most critical. Biochar promoted maize growth, development, and yield (root length, surface area, volume, dry matter accumulation, grain filling rate, and final weight). Biochar application at 40 t/ha had the greatest effect on soil microenvironment improvement, with the highest maize yield.

1. Introduction

The western part of the Songnen Plain is one of the major grain-producing areas in China. However, in recent years, improper use of arable land in the region has led to soil impoverishment, severe soil compaction, and increasing salinization. Coupled with climate change, the ecological environment in the region is very fragile: low temperature and drought in spring and heavy rainfall in summer. Consequently, soil viscosity becomes greater, infiltration capacity gets worse, and soil respiration is hindered, constraining the survival and reproduction of soil microorganisms. Consequently, the stability and productivity of the regional agroecosystem have been severely affected [1]. Therefore, it is urgent to find ways to improve and stabilize soil structure, regulate soil physicochemical properties, and create a soil environment, such that microbial activity can benefit agricultural production.

In recent years, biochar has received extensive attention for its application for soil improvement. Biochar is a stable, high-carbon product from agricultural waste biomass pyrolyzed under anoxic or hypoxic conditions [2]. Given its physical properties, such as great looseness, high porosity, and large specific surface area, biochar application can improve soil structure, reduce bulk density (BD), regulate soil “water”, “heat,” and “gas” conditions, and increase soil nitrogen, phosphorus, and potassium availability [3,4,5]. In particular, soil microorganisms are sensitive to biochar addition. For example, Hu et al. found that short-term biochar addition had a significant effect on soil microbial community composition, owing to the short-term enrichment of key bacterial and fungal taxa in the soil [6]. Similarly, studies of biochar application on sandy loams have suggested that significant changes in soil bacterial community structure occurred following biochar application. Moreover, biochar reportedly reduced the relative abundance of oligotrophic microorganisms, while promoting the relative abundance of eutrophic microorganisms [7]. In contrast, soil bacterial and fungal abundance increased, and the community structure changed significantly in soybean-maize rotation fields in black soils in Northeastern China following biochar application, which researchers attributed to variations in soil nutrients [8]. Thus, it has been inferred that the effects of biochar on changes in the composition and structure of soil microbial communities and their drivers vary with the soil properties and biochar’s original source. However, few studies have been conducted to elucidate the effects of biochar on the soil microenvironment of maize cultivated on saline-sodic soils in cold areas. Therefore, we previously conducted investigations and found that biochar application improved saline-sodic soils, enhanced soil fertility, and increased maize yield both effectively and economically [9,10]. However, there are a lack of systematic studies on the correlation between biochar application and soil microbial community diversity in salinized fields and maize yield.

In this study, a field experiment was conducted under saline-sodic soil conditions in the cold areas of Heilongjiang Province to investigate the effects of different biochar application rates on the soil microenvironment (soil physicochemical properties and soil bacterial and fungal diversity), maize growth and development, and yield. Our study provides a sound theoretical basis for the extensive application of biochar on saline-sodic soils, which is crucial for maintaining a stable and sustainable farmland soil environment.

2. Materials and Methods

2.1. Study Site and Species

The study was conducted in 2019 at the experimental station of Heilongjiang Bayi Agricultural University (46°37′ N 125°11′ E). Figure 1 shows the meteorological data (Daqing Meteorological Bureau) of the study site during the cropping season from May to October. Minimum and maximum mean daily temperatures were 6.3 and 24.7 °C, respectively. Total annual precipitation in 2019 was 512.7 mm, including 349.2 mm from July to September. However, mean annual rainfall in the area was approximately 440 mm. Thus, in 2019, rainfall was higher than normal. Notably, the ground of the test area suffered from short-term flooding between the maize jointing stage in July and the filling stage in September, owing to several heavy rainfall events.

2.2. Test Material and Experimental Design

The test soils were saline-sodic soils. The experimental material was maize straw biochar (Shenyang Longtai Biological Engineering Co., Ltd., Shenyang, China). Soil fertility of 0–20 cm tillage layer and properties of biochar are shown in

Table 1. Soil fertility and properties of biochar.

Soil	pH	organic carbon	alkaline hydrolysable nitrogen	available phosphorus	available potassium
	8.32	15.30 g/kg	128.65 mg/kg	13.05 mg/kg	139.18 mg/kg
Biochar	pH	total organic carbon	total nitrogen	total phosphorus	total potassium
	8.68	582.38 g/kg	8.42 g/kg	8.15 g/kg	29.63 g/kg

.

The experiment was conducted in a randomized block design with four treatments, B0 (0 t/ha), B20 (20 t/ha), B40 (40 t/ha), and B80 (80 t/ha), each with four replications, for a total of 16 treatments. Each test plot contained six rows, and each row was 20 m long. The total area of the test plot was 78 m². Maize was cultivated in the test plot by ridge planting with a uniform ridge spacing of 0.65 m. The total planting density was 75,000 plants/ha. The maize variety tested was Xianyu 335.

Biochar was spread on the surface of the test soil once before land preparation for tillage and mixed evenly with the topsoil layer (0–20 cm) using a rotary tiller after turning it manually. Fertilizers were applied at rates of 164.5 kg/hm² urea (46% N), 120 kg/hm² of diammonium phosphate (46% P₂O₅), and 90 kg/hm² of potassium sulfate (50% K₂O). Specifically, 70% of urea and 100% of diammonium phosphate and potassium sulfate were applied as the base fertilizers at the time of sowing, while the remaining 30% of urea was applied as follow-up fertilization at the jointing stage. Other field management measures were performed as recommended for high-yielding maize in the region.

2.3. Sampling

Soil and plant samples were collected at the jointing and grain-filling stages. A mixture of five soil samples collected at 0–20 cm depth was considered as a soil sample. Soil samples were passed through a 2 mm sieve to remove any visible roots, plant residues, and stones manually. Fresh soil samples were collected in sterile zip-lock bags and transported to the laboratory in an incubator containing an ice chest. Each soil sample was divided into two parts. One part was placed in a sterile centrifuge tube and stored at −80 °C for determination of soil microbial diversity. The other portion was placed in a cloth bag and air-dried in the laboratory to determine other soil physicochemical properties. After maize plants were collected, four plants that characterized maize growth in each plot were selected and brought intact to the laboratory for measurement.

2.4. Sample Analysis

2.4.1. Determination of Soil Physicochemical Properties

Soil pH was determined using a glass electrode with a water-to-soil ratio of 2.5:1 [11]. Soil moisture was determined by drying fresh soil (10 g) at 105 °C for 24 h [11]. Soil BD was determined using the ring knife method [11]. The stability of soil water-stable agglomerates was calculated by the mass of water-stable agglomerates with grain sizes >0.25 mm (wet sieve method) and the mass of mechanical-stable agglomerates with grain sizes >0.25 mm (dry sieve method) [12]. Soil organic carbon (SOC) was determined using the potassium dichromate oxidation method [13]. Effective nitrogen was determined using the diffusive absorption method by sodium hydroxide hydrolysis-hydrochloric acid titration [13]. Soil phosphorus availability was determined using the NaHCO₃ leaching-molybdenum antimony anti-colorimetric method [13].

2.4.2. High-Throughput Sequencing Analysis of Soil Microbial Community

Soil samples were analyzed as follows.

• DNA extraction and PCR amplification.

Total DNA extraction was performed according to manufacturer’s instructions in the E.Z.N.A.^® soil kit (Omega Bio-tek, Norcross, GA, USA). DNA concentration and purity were checked using NanoDrop2000, while DNA extraction quality was detected by 1% agarose gel electrophoresis.

Amplification of the bacterial 16S rRNA V3–V4 region was performed by PCR using bacterial specific primers 338F/806R [14]. The primer (338F/806R) sequences were as follows:

338F (5′-ACTCCTACGGGAGGCAGCAG-3′),

806R (5′-GGACTACHVGGGTWTCTAAT-3′).

PCR amplification of fungal ITS rRNA was performed using fungal specific primers ITS1F/ITS2R [15]. The primer sequences were as follows:

ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′),

ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′).

The amplification procedure was according to the following protocol: pre-denaturation at 95 °C for 3 min, 27 cycles (denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s, extension at 72 °C for 45 s), and final extension at 72 °C for 10 min (PCR instrument: ABI GeneAmp^® 9700, ThermoFisher SCIENTIFIC, Waltham, MA, USA). The amplification reaction was 20 μL, comprising 4 μL 5 × FastPfu buffer, 2 μL 2.5 mM dNTPs, 0.8 μL primer (5 μM), 0.4 μL FastPfu polymerase, 10 ng DNA template, and finally, ddH₂O up to 20 μL.

2.

Illumina MiSeq sequencing.

Products of PCR amplification were recovered using 2% agarose gels, then purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA), eluted with Tris-HCl buffer, and detected by 2% agarose gel electrophoresis. Detection and quantification were performed using QuantiFluor™-ST (Promega, Madison, WI, USA). Sequencing was performed using Illumina’s MiSeq PE300 platform (Shanghai Meiji Biomedical Technology Co., Ltd., Shanghai, China).

3.

Sequencing-data processing.

The raw sequenced sequences were quality controlled using the Trimmomatic software and spliced using the FLASH software. The OTU sequences were clustered using the UPARSE software (version 7.1 http://drive5.com/uparse/ accessed on 1 May 2020), based on 97% similarity, and single sequences and chimeras were removed during clustering. Species taxonomic annotation of each sequence was performed using RDP and compared to the Silva database (SSU123), with a comparison threshold of 70%. To compare community variation across treatments, all samples were sub-sampled by the minimum amount of data from sequencing results for subsequent analysis.

2.4.3. Determination of Root Traits in Maize

The CI-600 root monitoring system was utilized for positioning observation. A transparent root tube with a length of 100 cm was pre-buried in the ground after sowing, with a 60° angle between the root tube and the ground, and the underground part of the root tube was 80 cm long. The root system was scanned at each sampling time point, and changes were analyzed using the WinRHIZO software for root analysis.

2.4.4. Determination of Maize Growth Traits

Maize plants were separated into leaves, stems, sheaths, and seeds; then, each organ was heated at 105 °C for 30 min and dried to constant weight at 80 °C. Each part was weighed separately to calculate dry matter accumulation.

2.4.5. Determination of Maize Grain-Filling Rate

Maize plants with uniform growth during the silking stage were selected and sampled at 7 d intervals starting at 21 d after silking, and three ears of marked plants were collected from each plot. Each ear was divided into three parts: upper, middle, and lower. Moreover, 100 kernels were collected per ear, after threshing and mixing, and dried to a constant weight at 80 °C to calculate the grain-filling rate.

2.5. Data Analysis

One-way analysis of variance (ANOVA), followed by Duncan’s test, were performed using the SPSS 21.0 software to determine the statistical significance of treatment differences (p < 0.05; n = 3). Graphs were plotted using the GraphPad Prism 7 software. To illustrate the effects of biochar addition on the structure of bacterial and fungal communities, redundancy analysis was performed using the Canoco 5 software. After data standardization, the Monte Carlo replacement test was performed to assess the contribution and significance of different soil variables to the structure of soil bacterial and fungal communities. The logistic equation W = A/(1 + Be^−Ct) was used to simulate filling, with days after silking (t) as the independent variable and dry weight (W) of 100 grains as the dependent variable. In the equation, A denotes the theoretical maximum 100-kernel weight, B represents the initial value parameter, and C is the growth rate parameter. The correlations between soil physicochemical properties, soil microbial taxa, root system traits, plant growth, and yield were determined using Spearman correlation analysis.

3. Results

3.1. Effects of Biochar on Soil Physicochemical Properties

As shown in

Table 2. Effects of biochar addition on soil physico-chemical characteristics.

Period	Treatment	BD	Moisture	pH	WSAR	SOC (g/kg)	AN (mg/kg)	AP (mg/kg)
Jointing	B0	1.11 a	20.14 a	8.40 a	85.18 b	13.69 b	145.13 a	13.86 c
	B20	1.10 a	20.75 a	8.33 a	85.40 b	14.84 ab	151.95 a	15.28 b
	B40	1.07 a	20.91 a	8.32 a	88.55 a	15.72 a	164.73 a	17.12 a
	B80	1.06 a	20.92 a	8.37 a	87.32 ab	16.52 a	153.30 a	15.79 b
Filling	B0	1.37 a	25.15 a	8.38 a	78.62 b	12.13 c	120.89 b	7.82 b
	B20	1.31 ab	23.09 b	8.36 a	82.05 ab	13.91 b	137.67 ab	10.40 a
	B40	1.23 b	22.86 b	8.31 b	84.30 a	15.11 b	152.33 a	11.62 a
	B80	1.20 b	21.78 b	8.31 b	83.59 ab	18.16 a	139.25 ab	11.15 a

Note: BD: bulk density. WSAR: water-stable aggregate stabilization rate. SOC: soil organic carbon. AN: available nitrogen. AP: available phosphorus. Different letters indicate significant differences (one-way ANOVA, p < 0.05, Duncan analysis).

, no significant differences were detected in soil BD, moisture, or pH among the four treatments (B0, B20, B40, and B80) during growth or the jointing stage. However, during grain filling, all three indicators decreased to different extents, owing to the biochar application. Moreover, all three showed a decreasing trend with an increasing biochar application rate. This may be because biochar application changed the soil structure, reduced the BD, and increased the soil porosity. Meanwhile, from the meteorological conditions in the experimental area (Figure 1), we can infer that, with the onset of the rainy season from July to September, multiple heavy rainfall events led to the short-term flooding of saline-sodic soils and to near-saturation soil moisture content. With biochar application (B20, B40, and B80), soil permeability and hydraulic conductivity increased, owing to greater soil porosity, and soil moisture decreased. Moreover, the salt-based ions in the soil were partially leached away, and thus, soil pH slightly decreased. A comparison of the soil water-stable aggregate stabilization rate (WSAR) also indicated that the WSAR of the biochar treatments (B20, B40, and B80) was higher than that of the B0 treatment during both periods, with B40 treatment leading to the highest WSAR. After comparing the changes in WSAR at the jointing and grain-filling stages, we found that WSAR decreased by 7.70% in the B0 treatment, while it decreased by 4.33%, on average, across biochar application treatments. This indicated that, after the onset of flooding (filling stage), changes in soil physical properties were negligible and soil structure became more stable following biochar application. Therefore, biochar application was highly beneficial for improving the saline-sodic soil environment and for coping with the effects of heavy rainfall.

Similar phenomena were observed, with respect to soil nutrients. After comparing the variations in SOC, available nitrogen (AN), and available phosphorus (AP) at the jointing and grain-filling stages, SOC, AN, and AP decreased by 11.40%, 16.70%, and 43.58%, respectively, following B0 treatment, while they decreased, on average, by 5.07%, 8.70%, and 31.15% following biochar application. These findings imply that soil nutrient loss was severe after flooding, while biochar application mitigated the situation. After comparing the effects of different biochar application rates on soil nutrients, we found that treatments B40 and B80 increased soil SOC, AN, and AP contents to the largest extent.

3.2. Effects of Biochar on Soil Bacterial and Fungal Alpha Diversity

There were no significant differences in the effects of biochar application at different rates on the soil bacterial Shannon diversity index (

Table 3. Effects of biochar on bacteria and fungi alpha diversity index.

Treatment	Bacteria				Fungi
	Jointing		Filling		Jointing		Filling
	Shannon	Chao 1	Shannon	Chao 1	Shannon	Chao 1	Shannon	Chao 1
B0	6.69 ± 0.02 a	4915.26 ± 50.85 a	6.76 ± 0.02 a	5101.38 ± 44.60 a	3.80 ± 0.04 a	579.03 ± 30.13 a	4.03 ± 0.09 a	760.62 ± 24.64 a
B20	6.70 ± 0.02 a	4949.58 ± 116.79 a	6.72 ± 0.01 a	5167.14 ± 143.78 a	3.44 ± 0.02 b	634.89 ± 8.92 a	3.79 ± 0.09 ab	698.78 ± 6.57 b
B40	6.73 ± 0.01 a	5128.01 ± 59.34 a	6.70 ± 0.02 a	5316.60 ± 64.57 a	3.49 ± 0.06 b	620.68 ± 26.08 a	3.82 ± 0.06 ab	701.24 ± 19.64 b
B80	6.64 ± 0.05 a	5163.54 ± 70.72 a	6.74 ± 0.01 a	5407.98 ± 92.95 a	3.53 ± 0.08 b	606.79 ± 23.21 a	3.78 ± 0.05 b	642.82 ± 8.95 c

Note: Different letters indicate significant differences (one-way ANOVA, p < 0.05, Duncan analysis).

). Regarding the effects of biochar on soil fungal diversity, the corresponding Shannon index showed a significant decrease in treatments B20, B40, and B80, compared to that in B0, with decreases of 9.23%, 7.92%, and 6.86% and 5.96%, 5.21%, and 6.20% at the jointing and grain-filling stages, respectively. Under treatments B20, B40, and B80, the Chao 1 index of soil fungal richness at grain filling was significantly lower than that of the control group, indicating that soil fungal community diversity was more sensitive to biochar application than soil bacterial community diversity.

3.3. Effects of Biochar Application on Relative Abundance of Soil Bacterial and Fungal General

Biochar treatments (B20, B40, and B80) had varying effects on the relative abundance of dominant bacterial genera (Figure 2). Specifically, biochar application promoted Sphingomonas, Gemmatimonas, Lysobacter, Nitrospira, and Microvirga, and the trend of change was virtually the same at both the jointing and grain-filling stages. Specifically, on average, the relative abundance of Sphingomonas increased by 19.92%, 14.46%, and 43.55% following B20, B40, and B80 treatments, respectively, compared with B0. Meanwhile, on average, the relative abundance of Gemmatimonas increased by 9.36%, 13.62%, and 27.24% following B20, B40, and B80 treatments, respectively, compared with B0. In turn, the relative abundance of Lysobacter was significantly higher following B40 and B80 than in the B0 treatment, with average increases of 25.86% and 30.68%, respectively. Biochar treatments had significant effects on the relative abundance of Nitrospira during grain filling, increasing by 21.10%, 46.35%, and 42.21% following B20, B40, and B80 treatments, respectively, compared to B0. However, biochar treatment had a significant inhibitory effect on the Acidobacteria Subgroup 6 at the jointing stage, while this inhibitory effect decreased at grain filling.

Analysis of fungal genera detected by Illumina MiSeq high-throughput sequencing revealed that varying rates of biochar application (B20, B40, and B80) increased or significantly increased the relative abundance of the dominant fungal genus Guehomyces at both the jointing and grain-filling stages during maize growth (Figure 3a,b). Moreover, the relative abundances of both Fusarium and Gibberella showed a decreasing trend following various biochar treatments, and the performance was virtually the same at both the jointing and grain-filling stages (Figure 3c–f). Some fungal genera with less than 1% abundance showed significant changes following biochar application. For example, the relative abundances of Cladosporium, Alternaria, and Epicoccum showed a significant decrease following B20, B40, and B80 treatments, compared with those in B0, and the trends were consistent at the jointing and grain-filling stages (Figure 3g–l). Notably, Alternaria and Epicoccum almost disappeared from the soil following biochar application.

3.4. Drivers of Variation in Soil Bacterial and Fungal Community Structure

Redundancy analysis of soil bacterial and fungal community structure changes caused by environmental factors at the jointing and grain-filling stages during maize growth revealed that soil BD and pH were negatively correlated with biochar treatment (Figure 4a,c,e,g). Moreover, soil moisture exhibited a negative correlation with biochar treatment during grain filling (Figure 4c,g). In turn, the constrained P test revealed that SOC significantly altered the soil bacterial community structure at the jointing stage, explaining 42.4% of the total variation in the bacterial community (Figure 4b). Indeed, SOC and moisture had highly significant effects on bacterial community structure during the grain-filling stage, accounting for 41.3% and 35.8% of the total variation in the bacterial community, respectively. SOC and moisture were followed by BD and AP, which also had significant effects on the bacterial community structure (Figure 4d). Regarding the effects of environmental factors on soil fungal community structure, soil pH and SOC significantly altered soil fungal community structure at the jointing stage, explaining 32.0% and 27.6% of the total variation in fungal community structure, respectively (Figure 4f). Lastly, at grain filling, SOC and moisture had a significant effect on fungal community structure, explaining 20.4% and 18.7% of the total variation in fungal community structure, respectively (Figure 4h). These findings suggest that SOC is the most critical factor in changing the structures of soil bacterial and fungal communities.

3.5. Effects of Biochar on Root Growth and Development

The root volume gradually increased with increasing soil fertility (Figure 5). Notably, maize roots grew profusely, and root length (Figure 5a), root surface area (Figure 5b), and root volume (Figure 5c) grew largest under the B40 treatment and were significantly higher than those under the B0 treatment. Maize roots also showed better growth under B20, and root length, root surface area, and root volume were significantly higher than those in the control group at grain filling. However, root average diameter (Figure 5d) following biochar application was smaller than that in the control group, likely because following biochar treatment, the root system grew vigorously and developed more fine roots, thereby resulting in a lower average diameter.

3.6. Effects of Biochar on Dry Matter Accumulation

Biochar promoted dry matter accumulation by maize plants to varying degrees at the jointing stage (Figure 6a). The largest extent of dry matter accumulation was observed for the B40 treatment, in which case, the total dry matter increased by 33.96%, compared with the B0 treatment, followed by B20, which increased dry matter by 15.77%, relative to that in the control group. Following biochar treatment, the accumulation of dry matter at grain filling was significantly higher than that observed for the control group, with increases of 15.53%, 22.97%, and 14.97% following B40, B20, and B80, respectively, over B0 (Figure 6b). Specifically, B40 treatment increased leaves, stalks, leaf sheaths, and total grains by 6.57%, 16.33%, 19.58%, and 34.84%, respectively, compared with the B0 treatment.

3.7. Effects of Biochar on the Fitted Equation of Maize Grain Filling

Table 4. Maize grain-filling fitted equation and the grain-filling parameters.

Kenel Position	Treatment	Grain-Filling Fitted Equation	Parameter of Grain-Filling
			Tmax (d)	Wmax (g/Hundred Kernel)	Gmax [g/(d·Hundred Kernel)]	P (d)
Upper part	B0	W = 19.83/(1 + 36.23e−0.14t) R2 = 0.9957	25.64	9.92	0.69	42.86
	B20	W = 32.80/(1 + 60.95e−0.15t) R2 = 0.9961	27.40	16.40	1.23	40.00
	B40	W = 39.35/(1 + 55.15e−0.14t) R2 = 0.9957	28.64	19.68	1.38	42.86
	B80	W = 38.59/(1 + 70.11e−0.14t) R2 = 0.9976	30.36	19.30	1.35	42.86
Middle part	B0	W = 20.44/(1 + 39.25e−0.14t) R2 = 0.9916	26.21	10.22	0.72	42.86
	B20	W = 30.77/(1 + 44.70e−0.14t) R2 = 0.9948	27.14	15.39	1.08	42.86
	B40	W = 40.04/(1 + 30.88e−0.12t) R2 = 0.9988	28.58	20.02	1.20	50.00
	B80	W = 37.27/(1 + 36.97e−0.13t) R2 = 0.9975	27.77	18.64	1.21	46.15
Under part	B0	W = 28.36/(1 + 33.78e−0.14t) R2 = 0.9973	25.14	14.18	0.99	42.86
	B20	W = 33.74/(1 + 30.57e−0.13t) R2 = 0.9961	26.31	16.87	1.10	46.15
	B40	W = 43.00/(1 + 32.79e−0.13t) R2 = 0.9989	26.85	21.50	1.40	46.15
	B80	W = 39.83/(1 + 34.47e−0.12t) R2 = 0.9960	29.50	19.92	1.19	50.00

Note: Tmax: maximum grain-filling rate day; Wmax: the grain weight at maximum grain-filling rate; Gmax: maximum grain-filling rate; P: active filling period.

shows the fitted equation and the coefficients of determination (R²) for the different parts and treatments of the maize grain-filling process using logistic equations. R² was greater than 0.99, indicating that the equations were well-fitted and could be used to analyze the grain filling rate. On average, the maximum grain-filling rate upon biochar treatment increased by 1.65 d, compared with the control group. Moreover, the grain weight at the maximum grain-filling rate following B20, B40, and B80 treatments increased by 24.73%, 47.19%, and 39.76%, respectively, compared to that following the B0 treatment. The maximum grain-filling rate and active filling period after biochar treatment were significantly higher than those observed under the control treatment. Notably, the B40 treatment led to the maximum grain-filling rate and the longest active grain-filling period.

3.8. Effects of Biochar on Maize Yield Traits

Table 5. Effects of biochar on yield traits of maize.

Treatment	Ear Length (cm)	Barren Ear Tip (cm)	Number of Rows per Ear	Number of Grains per Ear	Hundred Kernel Weight (g)	Yield (kg/hm2)
B0	22.14 ± 0.33 a	1.54 ± 0.04 a	15.77 ± 0.19 b	39.43 ± 0.43 b	36.76 ± 0.65 b	11146.33 ± 530.99 b
B20	22.44 ± 0.46 a	1.39 ± 0.03 b	16.30 ± 0.15 a	41.10 ± 0.49 ab	37.83 ± 1.05 ab	11538.67 ± 732.13 ab
B40	22.76 ± 0.52 a	1.30 ± 0.03 b	16.80 ± 0.20 a	41.63 ± 0.62 a	40.40 ± 0.90 a	13561.00 ± 706.82 a
B80	22.37 ± 0.19 a	1.31 ± 0.02 b	16.53 ± 0.07 a	41.10 ± 0.80 ab	39.76 ± 1.34 ab	12573.33 ± 489.24 ab

Note: Different letters indicate significant differences (one-way ANOVA, p < 0.05, Duncan analysis).

shows the effects of biochar on maize yield traits. Biochar application significantly reduced the barren ear tip, while increasing the numbers of rows and grains per ear and 100-kernel weight. Specifically, biochar treatments (B20, B40, and B80) reduced the barren ear tip by 13.41% and, on average, increased the number of rows per ear by 4.90%, compared with the control group. Furthermore, there were no significant differences among biochar treatments. Specifically, B40 increased the number of grains per ear (5.58%) and 100-kernel weight (90.90%) significantly, relative to the control group. Regarding the effect of biochar on maize yield, this increased by 3.52%, 21.66%, and 12.80% following B20, B40, and B80 treatments, respectively, compared with the control. In particular, B40 contributed to a significant improvement in grain yield.

3.9. Correlations among Soil Microenvironment, Plant Growth and Development, and Crop Yield

The increase in dry matter accumulation at the grain-filling stage following biochar treatment was closely correlated with improvement of the soil microhabitat (Figure 7). Specifically, soil bacteria Nitrospira, Gemmatimonas, and Lysobacter, as well as SOC, N, AP, and WSAR, were positively or significantly positively correlated with dry matter accumulation at grain filling. Conversely, BD, pH, and soil fungi Cladosporium, Alternaria, and Epicoccum were negatively or significantly negatively correlated with dry matter accumulation at grain filling. Meanwhile, maize yield was highly significantly and positively correlated with dry matter accumulation at grain filling (p < 0.01). Therefore, biochar improved the soil microenvironment, enhanced root growth and development, and promoted plant growth and dry matter accumulation at grain filling, thereby ultimately increasing maize yield.

4. Discussion

4.1. Biochar Improved the Microenvironment of Saline-Sodic Soils

Saline-sodic soils have poor physicochemical properties, as they are characterized by notorious hardness and are highly compactable, leading to high BD, low porosity, and, consequently, poor permeability and poor aeration. However, biochar application can improve the physicochemical properties of saline-sodic soils. The findings reported herein indicated that biochar application reduced BD and increased soil porosity. Coupled with the variation in soil moisture induced by meteorological conditions (e.g., rainfall), the structures of the solid, liquid, and gas states of saline-sodic soils were improved, and the structure of soil aggregates was more stable following biochar application. Moreover, some salt-based ions were lost by rainfall, thereby slightly lowering the pH. Further, the improvement of the soil physicochemical properties serves as a key guarantee for the survival of soil microorganisms and the conversion of soil nutrients.

In this study, we found that biochar application had no significant effect on soil bacterial alpha diversity, while the relative abundance of different phyla and genera of soil bacteria was responsive to biochar addition. Thus, the application of biochar significantly increased the relative abundance of Sphingomonas and Lysobacter from the phylum Proteobacteria. Sphingomonas is a rich microbial resource with an extremely broad metabolic capacity for aromatic compounds [16]. Moreover, they can play a role in the N cycle, as a source of soil nutrient supply. Indeed, AN content also increased following biochar treatment. Lysobacter is a key biocontrol bacterium with significant antagonistic effects on a variety of plant pathogenic fungi, oomycetes, and nematodes [17], whereby increased Lysobacter may be beneficial for reducing disease incidence. Gemmatimonadetes is a phylum of biocontrol bacteria and plant growth-promoting bacteria in soils. Some researchers have suggested that the abundance of Gemmatimonadetes is closely related to phosphorus metabolism [18]. In the present study, we found that the significant increase in AP in biochar-treated soil may be induced by the increase in Gemmatimonadetes abundance. Similarly, Nitrospira plays a key role in the N cycle in soils and can participate in nitrogen nitrification. Moreover, saline-sodic soils can produce significant amounts of acidic substances under the action of nitrifying bacteria, which can help alleviate soil salinity hazards [19]. In the present study, biochar application increased the relative abundance of Nitrospira in saline-sodic soils and alleviated soil salinity stress.

Additionally, biochar application had a certain effect on soil fungal community structure. Specifically, biochar reduced soil fungal alpha diversity (Shannon, Chao 1). However, biochar significantly promoted Guehomyces of Basidiomycota. This finding is consistent with that of Yao et al. [20], who concluded that Guehomyces responded positively to biochar addition and was positively correlated with SOC. Our study also suggested a significant increase in SOC content upon biochar application. However, biochar decreased the relative abundance of Ascomycota, including Fusarium and Gibberella, which exhibited a decreasing tendency. The genus Fusarium contains many plant pathogens causing root rot in numerous crop plants [21]. Gibberella can cause stem and culm rot, which is harmful to crops [22]. Moreover, in the present study, biochar decreased the relative abundance of potential pathogens genera in some fungal genera with less than 1% abundance. For example, the relative abundance of Cladosporium, Alternaria, and Epicoccum was significantly affected by biochar and tended to disappear following biochar application. Cladosporium and Alternaria alternata are plant pathogenic bacteria that cause severe damage to crop growth [23,24]. Epicoccum normally parasitizes weakened tissues of maize or the sites where leaf-spot diseases of other species occur, producing large numbers of pathogenic sporodochium and conidiophore that endanger normal plant growth [25]. Therefore, our study indicated that biochar application reduced soil-borne pathogen populations and, thus, may have inhibited plant disease incidence. However, biochar inhibition of plant diseases is not a new finding. Moreover, some researchers have reported that biochar suppressed wheat root rot [26] and pepper blight [27], among other diseases. However, the mechanism of biochar suppression of plant diseases is highly complex and warrants further in-depth investigation.

In this study, we found that biochar applications altered the structure of soil bacterial and fungal communities. The variation in soil microbial community structure was indirectly driven by biochar-induced changes in soil physicochemical properties. In particular, SOC was the most critical factor consistently affecting bacterial and fungal community structure. Shortly after the application of carbon-rich biochar, the unstable carbon in the biochar will rapidly act on soil microorganisms and promote their growth and reproduction [28,29,30]. Furthermore, some small molecules in biochar act as potential regulators that alter soil microbial activity and community structure [31].

4.2. Biochar Promotes Maize Growth and Development and Increases Yield

The root system plays a key role in connecting the soil with the aerial plant body. Plant roots primarily anchor the plant to the soil while they absorb and transport water, nutrients, and mineral elements for plant growth and development. Therefore, they are most sensitive to changes in the soil environment. In this study, we found that plant roots growing in biochar-treated plots grew vigorously, exhibiting a significant increase in fine roots. Moreover, in this case, root length, surface area, and volume were all higher than those of maize roots without biochar application. This may be because soil structure was loosened by biochar addition, which reduced root extension resistance and facilitated root extension growth. Consistent with Prendergast–Miller [32], we concluded that roots tended to grow in biochar-mixed soil, and root elongation, tip thinning, and root expansion, shown by roots growing in biochar-treated plots, facilitated nutrient uptake from the pores of biochar particles. The multi-layered and multi-dimensional root system expands the contact area between the root system and the soil, thereby obtaining more water and nutrients for crop growth. However, varying amounts of biochar addition had different effects on plant root growth. In this study, we found that, in the B40 treatment, maize plants had the highest number of roots and the greatest root length, surface area, and volume.

Efficient plant dry-matter accumulation is the basis for high yield. Herein, we concluded that dry matter accumulation by maize plants increased significantly with biochar application, with the grain filling rate increasing and the active period of grain filling extending. Dry matter accumulation increased because biochar improved soil structure and properties, providing a rich and conducive microenvironment for the reproduction and growth of beneficial microorganisms. Furthermore, biochar enhanced the conversion of effective carbon, nitrogen, and phosphorus nutrients and promoted the growth and development of maize roots and the transfer of nutrients to the aboveground plant body, which, in turn, increased maize grain filling and reduced the barren ear tip, thereby increasing yield, which is consistent with the findings of Cheng (2016) for brown soil [33]. They concluded that biochar-treated maize reached a significant rate of dry matter increase and a considerable rate of kernel weight increase at the late stage of seed filling, thereby leading to significantly increased kernel yield and harvest index. In this study, we found that the B40 treatment was the most effective, with a 21.66% increase in yield, relative to the control group.

The costs of applying large amounts of biochar inputs and the economic benefits brought by increased crop yields still vary greatly. However, biochar effects can last for many years with a single application. Therefore, further research should focus on the mechanism underlying the long-term effects of biochar in improving saline-sodic soils and maize growth.

5. Conclusions

The application of biochar on saline-sodic soils in the Songnen Plain slightly reduced soil bulk density and pH, while it increased the soil WSAR, SOC, AN, and AP. High-throughput sequencing indicated that biochar had no significant effects on bacterial alpha diversity but reduced soil fungal alpha diversity (Shannon, Chao 1). The relative abundance of the bacteria Sphingomonas, Lysobacter, Nitrospira, and Gemmatimonas and that of the fungus Guehomyces were significantly increased by biochar treatment. However, biochar inhibited the relative abundance of some important fungal potential pathogen genera, such as Fusarium, Gibberella, Cladosporium, Alternaria, and Epicoccum. Variations in soil bacterial and fungal community structure were indirectly driven by biochar-induced changes in soil physicochemical properties. Moreover, SOC was the most critical factor consistently affecting the changes in microbial community structure. Biochar also improved maize root formation (root length, root surface area, and root volume) and increased maize dry-matter accumulation. Furthermore, biochar promoted a higher seed filling rate and prolonged the vigorous growth stage of maize, which, in turn, increased the final yield. Specifically, biochar application at a rate of 40 t/ha caused the best effects on the soil microenvironment, as manifested by the most profusive root growth, the longest active grain-filling stage, and the highest maize yield (21.66% higher than the yield of controls) observed under this treatment. Therefore, biochar application is highly beneficial for lowering agricultural costs and increasing plant performance. Lastly, biochar can be very useful for a more sustainable utilization of alkalized soils.