1 Introduction

Wheat (Triticum aestivum L.) and peanut (Arachis hypogaea L.) are the important food crops and oil crops globally. The Huang-Huai-Hai Plain is the major region for wheat and peanut production in China, accounting for more than 60% of the national production (Wang et al. 2009; Liu et al. 2019). The winter wheat–summer peanut rotation system represents an agricultural production management practice, which is widely implemented by farmers in this region. This crop cultivation method can not only improve the utilization efficiency of soil, light, and heat resources (Wang et al. 2019a) but also increase the economic benefits.

Soil is the central aspect of agronomic sustainability and the foundation of agricultural production. Soil quality indicators consist of a range of physical and chemical characteristics (e.g., soil nutrient cycling, soil structure and stability), which are linked to agricultural production (Miriam 2018; Sarker et al. 2018). Over the past decades, along with the acceleration of industrialization and urbanization processes and the improvement of people living standards (Li et al. 2017; Zhao et al. 2015), the demand for food crops and oil crops has gradually increased. However, in intensive cropping systems, soil quality degradation is a continuous phenomenon. In the winter wheat–summer peanut rotation system, unreasonable agricultural management methods are deteriorating the soil quality, resulting in low soil nutrient concentrations and soil stability (Jat et al. 2019). Such changes could, in turn, decrease plant development and reduce crop yield. Therefore, the maintenance and improvement of soil quality in wheat–peanut rotation system are critical for sustainable wheat and peanut production. It is well known that tillage and straw management can affect soil quality and may be important agricultural management practices for yield improvement.

The main purpose of tillage is to provide suitable soil conditions for crop growth. Many studies have shown that tillage practice can influence crop growth and yield by influencing soil quality indicators, including water, fertility, gas, heat, and other indicators (Javeed et al. 2013; Lampurlanés and Cantero-Martínez 2003). However, different tillage practices have different effects on soil quality indicators. Many studies have demonstrated that plow tillage plays an important role in agricultural production. Plow tillage can loosen the soil by breaking the bottom of plowed stratum (Varsa et al. 1997), and promote the soil nutrient cycling. Most importantly, plow tillage can create an appropriate environment for the seed germination, seedling establishment, and crop growth (Zhang et al. 2018; Shen et al. 2016). In addition, rotary tillage is also a common tillage method for agricultural production, which can reduce soil erosion, soil nutrient loss, and the cost of production (Sung-Arun et al. 2005; Wang et al. 2006; Su et al. 2007). However, rotary tillage probably restricts the development of agriculture by increasing the soil penetration resistance and soil bulk density (Bogunovic et al. 2018), which makes it harder for soil water to infiltrate. Therefore, it may be an important agricultural production strategy to create suitable soil conditions and improve crop yield by selecting an appropriate tillage practice.

With the continuous increase in crop yields, the amount of straw, as a by-product and an important resource, also increased progressively (Wang et al. 2019b). However, with the transformation of farmers’ lifestyles, the phenomenon of straw burning in open air has increased sharply. Straw burning not only is a huge waste of resources but also causes serious problems such as air pollution and soil degradation. Therefore, the situation regarding the comprehensive utilization of straw in the Huang-Huai-Hai Plain is very severe (Qin et al. 2015; Clare et al. 2015). Straw return, as an effective means of straw comprehensive utilization, plays an important role in regulating soil structure and protecting the ecological environment (Zhang et al. 2014). The addition of crop straw is helpful to reduce the soil bulk density, improve soil aeration, and promote root penetration into deep soil. After returning straw to the field, the nutrients in straw are released, which improves the soil organic matter and total N contents (Liu et al. 2010). Soil organic matter is critical to soil quality, which promotes dispersed soil particles to form a soil aggregation (Yao et al. 2015; Mao et al. 2019). Due to regional differences in soil properties and climate, different straw return methods not only affect crop emergence but also induce competition between straw decomposition and N utilization, negatively affecting crop yield (Tao et al. 2015; Zhou et al. 2016). Thus, the selection of an appropriate straw management method to create suitable soil condition and enhance crop yield may be an important agricultural production strategy.

Enhancing soil quality is important for the sustainable development of agricultural production. In the winter wheat–summer peanut rotation system, rotary tillage before sowing the summer peanut is the main tillage practice in this region. However, rotary tillage probably restricts the development of agriculture. Therefore, investigating differences in soil physical and chemical properties among different tillage and straw management methods is highly important for constructing an ecologically efficient agricultural production system. The objectives of the present study were as follows: (1) to evaluate the effects of different tillage and straw management methods on the soil bulk density (SBD), soil water content (SWC), and soil nutrient concentrations; (2) to analyze the effects of different tillage and straw management methods on the distribution of aggregates, aggregate stability, and aggregate-associated C concentrations; (3) to assess the effects of different tillage and straw management methods on peanut dry matter accumulation and peanut yield, in order to serve as a reference in a wheat–peanut rotation system in the Huang-Huai-Hai Plain.

2 Materials and methods

2.1 Site description

The field experiment was conducted from 2017 to 2019 at the experimental station of Shandong Agricultural University, Tai’an, China (36° 09′ N, 117° 09′ E, 126 m above sea level). The region has a warm and semi-humid continental monsoon climate, with an average annual temperature of 13.7°C, an average annual rainfall of 631.5 mm, and a frost-free period of 195 days on average. The soil is a Cambisol with 8.06% clay, 49.86% silt, and 42.08% sand, according to the World Reference Base for Soil Resources (FAO). The soil (0–20 cm) had the following properties at the start of the experiment: organic matter 13.18 g kg−1, TN 1.03 g kg−1, hydrolysable nitrogen 69.86 mg kg−1, available phosphorus 38.66 mg kg−1, available potassium 83.28 mg kg−1, pH 7.82.

2.2 Experimental design

Four field treatments in the peanut growing season were as follows: (1) moldboard plow tillage with wheat straw return (MPS), (2) rotary tillage with wheat straw return (CTS), (3) moldboard plow tillage with wheat straw removal (MP), (4) rotary tillage with wheat straw removal (CT). The machines about moldboard plow tillage and rotary tillage are provided in Fig. S1 and Fig. S2. The field experiment was set up as a split-plot design with three replicates. Each plot had a size of 120 m2 (20 × 6 m). For the straw return treatments (MPS and CTS), wheat straw was cut to a length of 5–8 cm and uniformly distributed over each experimental plot before tillage operations. For MPS treatment, the amount of straw mixed with the soil was 7200 kg ha−1 and 7500 kg ha−1 in 2018 and 2019, respectively. For CTS treatment, the amount of straw mixed with the soil was 7320 kg ha−1 and 7260 kg ha−1 in 2018 and 2019, respectively. For the straw removal treatments (MP and CT), the aboveground portion of wheat straw was removed from the soil surface by hand, while the stubble and root were left in the soil. The moldboard plow tillage experimental plots (MPS and MP) were plowed to a depth of 30 cm using a moldboard plow (1LF–435) and then tilled twice using a rotary tiller (1GQQN-250GG). The rotary tillage experimental plots (CTS and CT) were only tilled to a depth of 15 cm using a rotary tiller (1GQQN-250GG).

The summer peanut cultivar used in the present study was “Shanhua 108.” Seeds were sown in the experimental plots on June 12, 2018, and June 13, 2019; and the plants were harvested on October 7, 2018, and October 7, 2019. Peanut was sown at a density of 1.50 × 105 hills ha–1. Two seeds were planted in each hill, with a 30-cm row spacing and 20-cm plant spacing. All the experimental plots were covered with clear and impermeable polyethylene plastic film, and the plastic film was removed after the peanut was harvested. In all experimental plots, 120 kg N ha−1, 120 kg P2O5 ha–1, and 120 kg K2O ha–1 were spread on the soil surface as basal fertilizers before applying tillage practices to promote summer peanut seed germination, emergence, and growth. The N fertilizer type was urea (N 46%), the phosphate fertilizer type was calcium superphosphate (P2O5 16%), and the potash fertilizer type was potassium chloride (K2O 60%).

The winter wheat was planted after the summer peanut harvest and summer peanut straw removal. The winter wheat cultivar “Shannong 20” was planted at 30-cm inter-row spacing with a planting density of 2.25 × 106 plants ha–1. Seeds were sown in the experimental plots on October 13, 2017, and October 14, 2018; and the plants were harvested on June 6, 2018, and June 8, 2019. In addition, all the experimental plots were tilled twice with rotary tillage before sowing winter wheat. All the experimental plots received applications of 220 kg N ha−1, 120 kg P2O5 ha−1, and 120 kg K2O ha−1 of urea (N 46%), calcium superphosphate (P2O5 16%), and potassium chloride (K2O 60%). Half the amount of N fertilizer was applied as basal fertilizers, and the other half was applied to the soil at a depth of 5 cm by ditching at the jointing stage. Whereas, all phosphorus and potash fertilizers were applied as basal fertilizers.

2.3 Sampling and measurement

2.3.1 Soil sampling

Soil samples were collected before the peanut harvest in 2018 and 2019. All soil samples were randomly collected at 10-cm increments down to 30 cm from three independent areas within each experimental plot. For the determination of the soil bulk density (SBD), soil porosity (SP), and soil water content (SWC), soil samples were collected manually using a standard stainless cutting ring. For the determination of soil nutrient concentrations, soil samples were collected manually by using a soil auger (5.0 cm diameter). After removing the visible organic residue and stones, the soil samples were air dried, passed through a 0.15-mm sieve, and stored prior to analyzing soil nutrient concentrations. Furthermore, undisturbed soil samples were collected using a flat spade and stored in crush-resistant airtight plastic box to measure the water stable aggregates. To prevent deformation, the soil sample was peeled into a soil block along its structural texture and passed through an 8-mm sieve. After removing the visible organic residue and stones, all the soil samples were air dried and used to analyze the aggregate size distribution.

2.3.2 Soil bulk density, soil porosity, and soil water content

Soil bulk density was measured as the dry weight of soil per unit volume. These soil samples were placed in the cutting ring and transported to the laboratory. All of the soil samples were immediately weighed and dried at 105°C to a constant weight to calculate the SBD and SWC. The SWC was measured using the oven-drying method (Zheng et al. 2014). In addition, the soil porosity was defined as the ratio of the soil bulk density to the particle density (Aziz et al. 2013). The SWC and SP were calculated according to Eqs. (1) and (2):

$$ SWC\left(\%\right)=\frac{Wf- Wd}{Wd}\times 100 $$
(1)
$$ SP\left(\%\right)=\left(1-\frac{SBD}{SPD}\right)\times 100 $$
(2)

where SWC (%) is the soil water content, Wf is the fresh weight of the soil sample, and Wd is the dry weight of the soil sample. SP (%) is the soil porosity, SBD (g cm−3) is the soil bulk density, and SPD (g cm−3) is the soil particle density.

2.3.3 Soil nutrient concentration

The soil total organic carbon (TOC) was measured using a TOC analyzer (Acquray-TOC, Elementar, Germany), and total nitrogen (TN) was measured using a TN analyzer (Rapid N exceed, Elementar, Germany). Soil available phosphorus (AP) was measured by NaHCO3 extraction, and analyzed by the Mo-Sb colorimetric method with a spectrophotometer (UV2550, Shimadzu, Japan). Soil available K (AK) was extracted using the ammonium acetate method and measured by flame photometry (Bao 2000).

2.3.4 Aggregate separation, mean weight diameter, and geometric mean diameter

Soil aggregates were separated by shaking using the wet sieving (Elliott 1986). The water stable aggregates were divided into four particle size fractions: large macroaggregates (> 2 mm, LM), small macroaggregates (0.25–2.0 mm, SM), microaggregates (0.053–0.25 mm, MI), and silt and clay (< 0.053 mm, SC). Air-dried soil samples were passed through successive sieves of 5, 2, 1, 0.5, 0.25, and 0.053 mm to separate the aggregate fractions. Four 50 g air-dried soil samples (< 8 mm) were placed on a sieving machine (TTF-100, Shangyu Shunlong Laboratory Instruments Factory) and immersed in deionized water for 10 min, and then, the soil samples were automatically shaken in water for 50 times in 2 min with a vibration amplitude of 3 cm. After wet sieving, aggregates were carefully rinsed from each sieve back into an aluminum box, and those remaining in the bucket (< 0.053 mm) were centrifuged to isolate the < 0.053 mm fraction. All aggregates were dried to a constant weight at 60°C in an oven (DHG-9420 A; Bilon Instruments Co. Ltd., Shanghai, China), and each particle size fraction aggregate was weighed (accuracy of 0.01 g). Then, the soil aggregate samples were stored for analysis of aggregate-associated C.

The mean weight diameter (MWD) and geometric mean diameter (GMD) were calculated using Eqs. (3) and (4) (Meng et al. 2014).

$$ MWD=\frac{\sum_{i=1}^n\left( Wi\times Xi\right)}{\sum_{i=1}^n Wi} $$
(3)
$$ GMD=\exp \left[\frac{\sum_{i=1}^n Wi\times \ln (Xi)}{\sum_{i=1}^n Wi}\right] $$
(4)

where n is total number of size fractions of aggregates; Xi is the mean diameter (mm) of every particle size aggregate fraction (6.5, 3.5, 1.5, 0.75, 0.375, 0.1515, 0.0265), and Wi is the mass proportion of every particle size aggregate fraction of the total dry weight of aggregates.

2.3.5 Dry matter and nitrogen accumulation amount

During the peanut harvest, five uniform representative plant samples were selected from the center of each plot and separated into the roots, stems, leaves, and pods. These samples were dried to a constant weight at 80°C in an oven (DHG-9420 A; Bilon Instruments Co. Ltd., Shanghai, China), after heating at 105 °C for 30 min. Then, plant samples were weighed (accuracy of 0.01 g) separately to determine dry matter accumulation. TN was measured using a TN analyzer (Rapid N exceed, Elementar, Germany). The harvest index (HI) and nitrogen harvest index (NHI) were calculated as follows:

$$ \mathrm{Harvest}\ \mathrm{index}\left(\mathrm{HI}\right)=\mathrm{grain}\ \mathrm{dry}\ \mathrm{weight}/\mathrm{total}\ \mathrm{dry}\ \mathrm{weight}\ \mathrm{of}\ \mathrm{plant} $$
(5)
$$ \mathrm{Nitrogen}\ \mathrm{harvest}\ \mathrm{index}\left(\mathrm{NHI}\right)=\mathrm{grain}\ \mathrm{N}\ \mathrm{amount}/\mathrm{total}\ \mathrm{N}\ \mathrm{amount}\ \mathrm{of}\ \mathrm{plant} $$
(6)

2.3.6 Peanut yield and its components

At peanut harvest time, three 6.67 m2 plots were demarcated within each experimental plot from which no plants were sampled (Munger et al. 1998). All the peanut plants in each plot were dug out for yield determination. Ten representative plants were sampled from each treatment to record the number of pods per plant. All the pods harvested from peanut plants were air dried and weighed. Furthermore, peanut shells were husked to obtain the kernel yield and shelling percentages.

2.4 Statistical analysis

The data were processed with DPS v7.05 (Hangzhou RuiFeng Information Technology Co. Ltd., China) and SPSS 23 (SPSS Inc., Chicago, IL, USA). Significant differences among the means were compared using the least significant difference test at a 5% significance level. Graphs were plotted using SigmaPlot 12.5 (Systat Software Inc., San Jose, CA, USA) and Origin (Origin 9.1, OriginLab, MA, USA).

3 Results

3.1 Soil bulk density, soil porosity, and soil water content under different tillage and straw management methods

Table 1 shows the differences in the SBD, SP, and SWC among the different treatments at a depth of 0–30 cm in 2018 and 2019. The results showed that SBD increased with increasing soil depth. For all the treatments, the values of SBD were 1.30–1.55 g cm−3 in 2018, followed by 1.27–1.55 g cm−3 in 2019. With the same straw management method, plow tillage decreased the SBD in the 0–30 cm soil layer relative to rotary tillage. In 2019, the SBD under MPS in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers significantly (P < 0.05) decreased by 2.67%, 4.46%, and 2.68% relative to those of CTS, respectively. Under the same tillage practice, straw return decreased the SBD in the 0–30 cm soil layer relative to straw removal. Compared to MP, MPS significantly (P < 0.05) decreased the SBD in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers by 4.95%, 4.44%, and 2.03% in 2019, respectively.

Table 1 Effects of different tillage and straw management methods on soil bulk density, soil porosity, and soil water content
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The SP at a depth of 0–30 cm had the opposite trend to that of the SBD (Table 1). The SP decreased with the increase of soil depth. With the same straw management method, moldboard plow tillage increased the SP in the 0–30 cm soil layer relative to rotary tillage. Under the same tillage practice, straw return increased the SP in the 0–30 cm soil layer relative to straw removal. When compared to MP, MPS significantly (P < 0.05) increased the SP in the 0–10 cm, 10–20, and 20–30 cm soil layers by 5.06%, 5.21%, and 2.75% in 2019, respectively.

Comparing MPS with CTS and MP with CT, the comparisons showed that plow tillage increased SWC in the 0–30 cm soil layer with the same straw management method (Table 1). Compared to CTS, MPS increased the SWC in the 0–10 cm soil layer by 2.13% for the year 2018, and it significantly increased by 6.17% for the year 2019 (P < 0.05). MP also increased the SWC at 10–30 cm relative to CTS; however, the SWC at 0–10 cm under CTS was higher than that in MP. Compared to MP, MPS significantly (P < 0.05) increased the SWC in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers by 12.90%, 8.17%, and 4.36% in 2019, respectively. In addition, the SWC under CTS in the 0–30 cm soil layer was also higher than that in CT. As a result, straw return increased the SWC under the same tillage practice.

3.2 Soil nutrient concentrations under different tillage and straw management methods

The influences of the different treatments on the soil TOC, TN, AP, and AK concentrations at a depth of 0–30 cm are shown in Table 2. The soil TOC, TN, AP, and AK concentrations decreased with increasing soil depth. With the same straw management method, the TOC concentrations under moldboard plow tillage in the 0–30 cm soil layer were higher than those of rotary tillage. In 2019, MPS significantly (P < 0.05) increased the TOC concentrations in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers by 4.70%, 5.21%, and 13.29% relative to those of CTS, respectively. The variation in the TN, AP, and AK concentrations was similar to that of TOC concentrations. Under the same straw management method, the TN, AP, and AK concentrations in the 0–30 cm soil layer under moldboard plow tillage were also higher than those in rotary tillage. Comparing MPS with MP and CTS with CT, the comparisons indicated that straw return increased the TOC, TN, AP, and AK concentrations under the same tillage practice.

Table 2 Effects of different tillage and straw management methods on soil nutrient concentration
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3.3 Aggregate size distribution under different tillage and straw management methods

The distribution of aggregates with different particle sizes was different among the different treatments at a depth of 0–30 cm (Fig. 1). The mass proportion of large macroaggregates decreased with the increase of soil depth, but the mass proportion of microaggregates and silt and clay increased with increasing soil depth. The mass proportion of small macroaggregates was greater than the mass proportion of the other particle size fractions. With the same straw management method, moldboard plow tillage increased the mass proportion of large macroaggregates and small macroaggregates and decreased the mass proportion of silt and clay in the 0–30 cm soil layer relative to rotary tillage. Compared to CTS, the mass proportion of large macroaggregates under MPS in the 0–10 cm, 10–20 cm, and 20–30 cm soil layers increased by 2.60%, 0.56%, and 9.44% and 5.05%, 0.81%, and 25.94% in 2018 and 2019, respectively. Under the same tillage practice, straw return improved the formation of large macroaggregates and small macroaggregates and decreased the mass proportion of silt and clay in the 0–30 cm soil layer.

Fig. 1
figure 1

Effects of different tillage and straw management methods on soil aggregate distribution in the year 2018 (a) and 2019 (b). Error bars represent the standard error of the mean (n = 3). Different lowercase letters indicate significant differences among treatments using the LSD test at P < 0.05. MPS, moldboard plow tillage with wheat straw return; CTS, rotary tillage with wheat straw return; MP, moldboard plow tillage with wheat straw removal; CT, rotary tillage with wheat straw removal

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3.4 Aggregate stability under different tillage and straw management methods

Differences in aggregate stability at a depth of 0–30 cm were found among the different treatments (Fig. 2). The values of MWD and GMD ranged from 0.84 to 1.96 mm and from 0.27 to 0.85 mm in 2018, respectively. In 2019, the values of MWD and GMD ranged from 0.83 to 2.02 mm and from 0.26 to 0.91 mm, respectively. With the same straw management method, the MWD and GMD values under moldboard plow tillage in the 0–30 cm soil layer were higher than those of rotary tillage. In 2019, the MWD values at 0–10, 10–20, and 20–30 cm under MPS increased by 5.21%, 3.45%, and 17.12% relative to those in CTS; the GMD values at 0–10, 10–20, and 20–30 cm significantly (P < 0.05) increased by 12.78%, 9.81%, and 31.34%, respectively. MP also increased the MWD and GMD values at 20–30 cm compared to CTS; however, the MWD and GMD values at 0–20 cm under CTS were higher than those in MP. The MWD and GMD values in the 0–30 cm soil layer under MPS were significantly (P < 0.05) higher than those in MP. In addition, the values of the MWD and GMD at 0–20 cm under CTS were significantly (P < 0.05) higher than those in CT, but no significant difference was found at 20–30 cm.

Fig. 2
figure 2

Effects of different tillage and straw management methods on soil aggregate stability in the year 2018 (a, c) and 2019 (b, d). Error bars represent the standard error of the mean (n = 3). Different lowercase letters indicate significant differences among treatments using the LSD test at P < 0.05. MWD, mean weight diameter (mm); GMD, geometric mean diameter (mm); MPS, moldboard plow tillage with wheat straw return; CTS, rotary tillage with wheat straw return; MP, moldboard plow tillage with wheat straw removal; CT, rotary tillage with wheat straw removal

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3.5 Aggregate-associated C concentration under different tillage and straw management methods

Figure 3 shows the different particle size fraction aggregate-associated C concentrations at a depth of 0–30 cm among the different treatments. The concentrations of aggregate-associated C were higher in large macroaggregates than in the other particle size fractions. With the same straw management method, the aggregate-associated C concentrations under moldboard plow tillage in each particle size fraction in the 0–30 cm soil layer were higher than those of rotary tillage. The concentrations of aggregate-associated C in small macroaggregates, microaggregates, and silt and clay at 10–20 cm under MP were higher than those in CTS. MP also increased the aggregate-associated C concentrations in each particle size fraction at 20–30 cm, when compared to CTS. Furthermore, comparing MPS and MP, and CTS and CT, we found that the concentrations of aggregate-associated C in each particle size fraction treated with the straw return were higher than those in the straw removal.

Fig. 3
figure 3

Effects of different tillage and straw management methods on soil aggregate-associated C concentration in the year 2018 (a) and 2019 (b). Error bars represent the standard error of the mean (n = 3). Different lowercase letters indicate significant differences among treatments using the LSD test at P < 0.05. MPS, moldboard plow tillage with wheat straw return; CTS, rotary tillage with wheat straw return; MP, moldboard plow tillage with wheat straw removal; CT, rotary tillage with wheat straw removal

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3.6 Peanut dry matter accumulation and distribution under different tillage and straw management methods

There were differences in dry matter accumulation and distribution among the different treatments (Table 3). As for the dry matter distribution, the dry matter accumulation in peanut plant organs followed the order pod > stem > leaf > root. With the same straw management method, the dry matter accumulation and HI under moldboard plow tillage were higher than those of rotary tillage. Compared to CTS, MPS significantly (P < 0.05) increased the total dry matter accumulation by 8.43% and 8.01% in 2018 and 2019, respectively. Compared to that for CTS, the HI for MPS was significantly (P < 0.05) increased by 2.73% and 2.72% in 2018 and 2019, respectively. Straw return treatments with either plow or rotary tillage both increased the total dry matter accumulation and HI compared to the straw removal treatments. In 2019, the total dry matter accumulation under MPS significantly (P < 0.05) increased by 19.89% relative to that in MP, and for the HI, it increased by 5.05%.

Table 3 Effects of different tillage and straw management methods on peanut dry matter accumulation and distribution
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3.7 Peanut nitrogen uptake and distribution under different tillage and straw management methods

As shown in Table 4, the total N accumulation and distribution had the same trends as that of the dry matter accumulation and distribution. With the same straw management method, moldboard plow tillage increased the N accumulation and NHI relative to rotary tillage. In 2019, compared to CTS, MPS increased the total N accumulation and the NHI by 15.91% and 1.98%, respectively. The total N accumulation and NHI treated with straw return were higher than those treated with straw removal. Compared to MP, the total N accumulation and NHI for MPS significantly (P < 0.05) increased by 37.08% and 3.74% in 2019, respectively.

Table 4 Effects of different tillage and straw management methods on peanut nitrogen uptake and distribution
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3.8 Grain yield under different tillage and straw management methods

The differences in the peanut yield and its components between the different treatments are shown in Table 5. The comparisons of MPS and CTS and MP and CT demonstrated that moldboard plow tillage increased the pod yield and kernel yield with the same straw management method. As expected, straw return also increased pod yield and kernel yield relative to straw removal. Compared to CTS, MP, and CT, the pod yield under MPS significantly (P < 0.05) increased by 6.65%, 8.55%, and 14.52% in 2019, respectively. The yield components also differed among the treatments. When compared to CTS, MP, and CT, MPS significantly (P < 0.05) increased the number of pods per plant by 4.94%, 8.90%, and 19.81% in 2019, respectively. However, MPS decreased the pod number per kilogram compared to the other treatments. In addition, the shelling rate and pod yield consistently showed the same trend. MPS increased the shelling rate compared to other treatments.

Table 5 Effects of different tillage and straw management methods on peanut yield and its components
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3.9 Relationships among soil aggregate parameters

The linear regression models among the soil aggregate parameters were obtained by regression analysis (Fig. 4). The relationships between MWD and aggregate-associated C concentrations indicated that the MWD was significantly (P < 0.01) positively correlated with the aggregate-associated C concentrations in large macroaggregates, small macroaggregates, microaggregates, and silt and clay. Simultaneously, the GMD was significantly (P < 0.01) positively correlated with the aggregate-associated C concentrations in large macroaggregates, small macroaggregates, microaggregates, and silt and clay. The results indicated that aggregate stability was significantly (P < 0.01) positively correlated with the aggregate-associated C concentrations in each fraction. In Fig. 4, we observed that the MWD was significantly (P < 0.01) positively correlated with the mass proportion of large macroaggregates and significantly (P < 0.01) negatively correlated with the mass proportion of microaggregates and silt and clay. The GMD was significantly (P < 0.01) positively correlated with the mass proportion of large macroaggregates and significantly (P < 0.01) negatively correlated with the mass proportion of microaggregates and silt and clay. The mass proportion of small macroaggregates showed no significant correlation with GMD. This showed that an increase in the mass proportion of large macroaggregates contributed to the stability of soil aggregates.

Fig. 4
figure 4

Relationships among the soil aggregate parameters under different tillage and straw management methods. R2 is the coefficient of determination, single asterisk (*) and double asterisks (**) indicate significance at the 0.05 and 0.01 level, and ns represents not significant. MWD, mean weight diameter (mm); GMD, geometric mean diameter (mm)

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4 Discussion

4.1 Effect of tillage and straw management on soil bulk density, soil porosity, and soil water content

The SBD, SP, and SWC are important indicators of soil structure, which affect the movement of nutrients and air through soil and water absorption by plant roots (Ning et al. 2009; Dao 1993). Suitable tillage practice can modify the soil environment, decrease the SBD, and improve the SWC. The SBD increased with increasing soil depth among all the treatments in 2018 and 2019 (Table 1), which is consistent with other studies (Blanco-Canqui and Lal 2008; He et al. 2019). In the present study, with the same straw management method, moldboard plow tillage decreased the SBD and increased the SWC in the 0–30 cm soil layer relative to rotary tillage (Table 1). This is because moldboard plow tillage can break the bottom of plowed stratum and decrease soil compaction, resulting in a decrease in SBD (Guan et al. 2015). It can also loosen the soil and improve soil permeability and water storage space (Zink et al. 2011). Our results indicated that straw return decreased the SBD and increased the SWC under the same tillage practice (Table 1). A previous study (Ge et al. 2014) showed that the addition of straw can decrease SBD by combining straw with soil particles to form a stable and loose structure. At the same time, straw return could improve soil water-holding capacity, maintain higher soil water content, and decrease water evaporation in arid agricultural regions under soil moisture stress (Zhao et al. 2013). Overall, straw return can reduce soil mechanical impedance and increase water storage space, which improves the physical and chemical properties of the soil.

4.2 Effect of tillage and straw management on soil TOC, TN, AP, and AK concentrations

Previous studies have reported that SBD, SP, and SWC are major soil physical properties that can affect nutrient mineralization, diffusion, and nutrient turnover (Nawaz et al. 2013; Paul et al. 2010). We observed that the surface soil (0–10 cm) had higher nutrient concentrations than the subsurface soils (10–30 cm) in all the treatments (Table 2). The main reason for this pattern is that the soil profile has a spatial heterogeneity in physicochemical and biochemical soil properties (Guo et al. 2015). Moreover, different tillage practices significantly influence nutrient concentrations. In our study, we observed that moldboard plow tillage increased the soil TOC, TN, AP, and AK concentrations in the 0–30 cm soil layer with the same straw management method (Table 2). Because the working depth of the treatments MPS and MP is 30 cm, moldboard plow tillage can increase the vertical depth of soil and enlarge the storage space for nutrition-rich material relative to rotary tillage. At the same time, it could also increase the SP and facilitate the transportation of soil nutrients and gases, resulting in an increase in nutrient concentrations (Xue et al. 2019; Alcántara et al. 2016). Many studies have observed that the incorporation of straw return into soil is one of the most important factors affecting soil structural development and nutrient increase (Aulakh et al. 2001; Wagner et al. 2010). According to the results of the present study (Table 2), straw return increased the soil TOC, TN, AP, and AK concentrations under the same tillage practice. The addition of straw can modify the soil physical and chemical condition (e.g., SP, SWC, soil microbial community, and soil enzyme activity), which accelerates the nutrients released from straw into the soil (Tripathy and Singh 2003; Zhang et al. 2016.). With the addition and subsequent decomposition of crop straw, soil nutrients will increase.

4.3 Effect of tillage and straw management on soil aggregate size distribution, stability, and aggregate-associated C

Soil aggregates are the basic unit of soil structure and play an important role in the mechanisms contributing to soil structure and stability. Soil aggregates can improve air permeability, increase water content, improve nutrient cycling, and reduce soil erosion (Six et al. 2002; Spohn and Giani 2010). The MWD and GMD reflect not only the stability of aggregate but also soil’s potential for nutrient cycling (Barthès and Roose 2002; Bronick and Lal 2005). Higher values of MWD and GMD indicate that a higher mass proportion of large macroaggregates are distributed in the soil and that there is larger aggregate stability (Piccolo et al. 1997). The process of aggregation depends on a variety of aggregate binders interacting simultaneously at different spatial scales (Tisdall and Oades 1982). Aggregate binders (e.g., root exudates, TOC, and fungal hyphae) play an important role in the formation and stabilization of aggregates (Wang et al. 2018). Based on our results, the concentrations of aggregate-associated C in large macroaggregates were higher than those of other particle size aggregate-associated C concentrations (Fig. 3). In general, large macroaggregates are formed around fresh organic carbon and a larger mass proportion of large macroaggregates occur with an increase in TOC concentrations (Six et al. 2000). Our data also showed that the aggregate-associated C concentrations in microaggregates were always lower than those of other particle size fractions in every treatment (Fig. 3). This might be because the new TOC within microaggregates has relatively poor stability, which would agree with the findings of Garcíaoliva et al. (1999). Furthermore, the concentrations of aggregate-associated C in silt and clay were higher than those in microaggregates (Fig. 3). The silt and clay are stable and have a high specific surface area, thus reducing the TOC turnover and possibly promoting a longer average TOC residence time (Choudhury et al. 2014).

Soil tillage is one of the most important soil management methods. Different tillage practices can affect soil aggregation directly and indirectly through altering soil physical, chemical, and biological factors (Zhang et al. 2012). According to our results, with the same straw management method, moldboard plow tillage increased the mass proportion of large macroaggregates and the aggregate-associated C concentrations, resulting in an increase in the MWD and GMD values (Figs. 1 and 2). First, moldboard plow tillage could create a suitable soil moisture, temperature, and ventilation conditions and increase the concentrations of TOC, compared to rotary tillage. These differences can directly benefit root growth and increase root exudation (Yu et al. 2020). Aggregate binders (e.g., root exudates, TOC, and fungal hyphae) adhere to soil particles, which may improve the soil agglomeration and form relatively stable soil compound particles. Then, the stable soil compound particles promote aggregate formation (Puget et al. 2000), especially the formation of large macroaggregates that remain stable.

Another factor affecting aggregate size distribution and stability is the straw return. Our results showed that straw return improved the formation of large macroaggregates and increased the aggregate-associated C concentrations under the same tillage practice, as the same with the soil structure stability (Figs. 1 and 3). Higher residue, such as that of straw, stubble, and roots, is the main factor influencing the formation of soil aggregates. The input of straw, stubble, and roots can easily increase the available supply of C required for aggregate formation and promote the bonding of clay particles into larger aggregates, ultimately improving the stability of aggregates (Verhulst et al. 2011). The variation in the MWD and the GMD values among the treatments can be attributed to the variation of the aggregate particle size and the TOC concentrations in the soil (Puget et al. 1995). We found that an increase in the mass proportion of large macroaggregates and the aggregate-associated C concentrations improved aggregate stability (Fig. 4).

4.4 Effect of tillage and straw management on peanut dry matter and nitrogen accumulation and peanut yield

Previous studies have shown that suitable tillage practice can promote the growth of crop and improve dry matter accumulation and grain yield (Miriti et al. 2012; Piao et al. 2016). The effects of tillage practice on crop yield are mainly influenced by the physical and chemical characteristics of soil, which in turn increase nutrient uptake and utilization, obtaining higher crop biomass and yield (Muñoz-Romero et al. 2010). Although a few studies have reported that tillage has no significant effect on dry matter accumulation and crop yield (Hao et al. 2001), there are also some different ideas. Guan et al. (2014) reported that PT can increase root dry matter accumulation and summer maize grain yield. In the present study, with the same straw management method, moldboard plow tillage increased peanut total dry matter accumulation, N accumulation, and pod yield relative to rotary tillage (Tables 3, 4, and 5). The reason for this might be that moldboard plow tillage can break the bottom of plowed stratum and improve soil properties (Botta et al. 2006), further increasing plant nutrient uptake from soil, resulting in allowing optimal crop yield (Singh et al. 2013; Chu et al. 2016). Rotary tillage may increase the resistance of peanut pegs to penetrate the soil surface and thereby lead to a decrease in peanut yield (Haro et al. 2008). Previous studies also demonstrated large benefits of straw return for increasing succeeding crop yield (Zhu et al. 2014; Xia et al. 2018). The results of our experiment showed that straw return treatments increased the total dry matter accumulation, N accumulation, and pod yield (Tables 3, 4, and 5). This might be due to the differences in the soil structure, temperature, and nutrient supply. Straw return decreases soil compaction and increases soil temperature, soil enzymatic activity, and nutrient concentrations (Clarke et al. 2015; Fahad et al. 2016). All of these improvements in soil physical and chemical reactions may contribute to crop nutrient absorption and growth, further increasing crop dry matter accumulation, ultimately obtaining the highest grain productivity (Wu et al. 2015; Yang et al. 2016).

5 Conclusions

The field trial evaluated the effects and changes of different tillage and straw management methods on soil quality, dry matter and N accumulation, and peanut yield in a winter wheat–summer peanut rotation system. MPS improved the soil physical and chemical properties (i.e., increased soil porosity, soil water content, soil nutrient concentrations, and soil aggregate stability), increased the peanut dry matter and N accumulation, and resulted in the largest peanut yield. Therefore, after harvesting the winter wheat, moldboard plow tillage with wheat straw return (MPS) to seed the summer peanut may be a suitable soil management practice for improving soil physical and chemical properties and increasing peanut yield in the Huang-Huai-Hai Plain. Future studies should focus on the effects of different tillage and straw management methods on peanut rhizobial richness and diversity and rhizobium-peanut symbiotic N fixation.