Effects of Alfalfa–Grass Mixed Sowing on Grass Yield and Rhizosphere Soil Characteristics

Abstract

This research investigated the impact of various mixed sowing combinations on soil nutrients and grass yield within the rhizosphere across different seasons. Three varieties of leguminous forages—Medicago sativa ‘Gannong No. 3’ (GN3), M. sativa ‘Gannong No. 9’ (GN9), and M. sativa ‘Juneng No. 7’ (JN7)—as well as three varieties of grasses—Leymus chinensis ‘Longmu No. 1’ (LC), Agropyron mongolicum ‘Mengnong No. 1’ (AC), and Bromus inermis ‘Yuanye’ (BI)—were used as experimental materials for mixed sowing combinations; the monocultures of each material served as controls. We explored the seasonal effects of different legumes and grasses intercropping combinations on rhizosphere soil nutrients and grass yield in the Hexi Corridor region of China. The results indicated that the levels of soil enzyme activity, microbial biomass, and soil nutrients in the rhizosphere across the various treatments followed the following sequence: summer > spring > autumn. The soil enzyme activities and microbial biomass of various mixed sowing combinations were significantly higher than those of the monocultures within the same growing season (p < 0.05). Specifically, the activities of alkaline phosphatase (APA), catalase (CAT), soil microbial biomass carbon (SMBC), soil microbial biomass nitrogen (SMBN), soil microbial biomass phosphorus (SMBP), soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), and available potassium (AK) within the GN9+BI group were the highest among all treatments. The hay yields of GN3, GN9, and JN7 were markedly greater than those of their respective mixed sowing combinations (p < 0.05). Correlation analysis revealed a positive relationship between enzyme activities, microbial biomass, and soil nutrient levels. This comprehensive evaluation indicated that the mixed sowing combinations of GN9 + BI and GN9 + LC are particularly well suited for widespread adoption in the Hexi Oasis irrigation area.

1. Introduction

The Hexi Corridor is situated in the western region of Gansu Province, serving as a convergence zone for the Loess Plateau, the Mongolian Plateau, and the Qinghai–Tibet Plateau [1]. The region is primarily engaged in traditional agricultural and pastoral activities and stands as a crucial green ecological barrier for China [2]. The Hexi Corridor is an ideal location for developing artificial grasslands, characterized by its flat terrain and abundant sunlight. Nevertheless, most agricultural activities in the region heavily depend on irrigation due to persistent drought, scant rainfall, and high annual evaporation rates [3]. This situation not only hinders the development of grassland animal husbandry but also undermines the balance of the agricultural structure [4]. Artificial grasslands are key components of modern animal husbandry systems. They play a positive role in improving economic efficiency, increasing livestock carrying capacity, enhancing agricultural productivity, conserving water and soil, and transforming the ecological environment [5]. Consequently, it is of paramount importance to cultivate high-yield artificial grasslands that are finely attuned to the unique ecological environment of the Hexi region.

Establishing high-quality, high-yield artificial grasslands is a critical strategy to address regional imbalances between forage supply and livestock demand while preventing the degradation of natural grasslands [6]. Mixed sowing of leguminous forages and grasses enhances soil resource efficiency [7], improves forage quality [8], and increases the resistance and resilience of grasslands [9]. This approach is widely regarded as the primary method for establishing artificial grasslands [10]. However, the Leguminosae and Gramineae families compete for essential resources, including light, water, nutrients, and space within these systems. The stable coexistence of two species or the extinction of one species is a common result of this dynamic competition [11,12]. The sustainability of mixed sowing production practices is essential for achieving optimal production performance and ecological stability in artificial grasslands [13]. Therefore, selecting appropriate mixed sowing combinations is essential for establishing high-quality, high-yield grasslands and for maintaining the ecological stability of grassland communities.

Soil serves as the foundational medium for plant growth and development, with its biological properties acting as essential indicators for evaluating soil quality [14]. Soil enzyme activities and microbial biomass play a crucial role in maintaining soil quality, regulating fertility characteristics, and enhancing biological activity [15]. Some researchers have observed that the activities of soil urease and sucrase in legume–gramineae mixture grasslands significantly exceed those in monoculture systems; moreover, these soil enzyme activities increase with a higher proportion of leguminous forage [16]. Lu et al. [17] discovered that a legume-to-grass ratio of 5:5 enhances the absorption and yield of nitrogen and phosphorus across various mixed planting arrangements. Wu et al. [18] demonstrated that the technique of legume–grass intercropping helps to improve soil nitrogen content by analyzing different fertilization regimes and mixed sowing arrangements. Li et al. [19] revealed that integrating millet with alfalfa can modulate the soil microbial community by enhancing soil nutrient levels, thereby increasing productivity. At the same time, planting alfalfa with a high crude protein content alongside grass that has high fiber digestibility enhances the nutritional value of grass production [20,21].

Numerous studies have investigated the effects of different fertilization treatments [18], mixed sowing ratios [17], and single mixed sowing combinations [19] on legume–grass mixed-sown grasslands. However, comprehensive research on the influence of multiple legume–grass forage mixed sowing combinations on grassland soil biological properties remains limited. How to enhance the biological characteristics of soil and improve grassland productivity and ecological function through the optimization of mixed planting combinations in the unique ecological area of the Hexi Oasis remains an urgent scientific challenge that needs to be addressed. Therefore, this study systematically investigates the effects of different mixed sowing combinations on soil properties in the Hexi oasis area using three varieties of alfalfa and different varieties of grasses. By elucidating the impacts of various mixed sowing combinations on soil enzyme activity, microbial biomass, and nutrient uptake, this study seeks to fill the existing research gap and offer scientific insights and technical support to promote the sustainable development of grassland ecosystems in this region.

2. Materials and Methods

2.1. Overview of Test Site

The experiment was conducted at the Wuwei Forage Experimental Station (37°55′ N, 102°40′ E) of Gansu Agricultural University from 2022 to 2023. The meteorological data for the year of planting showed that the area’s annual average temperature was 13 °C, with an elevation of 1530.88 m. Precipitation measures 201 mm annually on average per year. There were 150 frost-free days, characteristic of a temperate arid desert environment. The soil types are Calcisols and Greyzems [22]. According to years of meteorological data, precipitation measured 150 mm, the average yearly temperature was 7.2 °C, the extreme maximum temperature was 40.8 °C, the extreme minimum temperature was −32 °C, and the frost-free period lasted for 154 days. The annual effective accumulated temperature (≥10 °C) was 3003 °C. Prior to planting (April 2022), soil samples were collected from the 0–20 cm layer, and the concentrations of organic carbon, total nitrogen, total phosphorus, and total potassium were measured at 6.76, 0.56, 1.62, and 10.85 g/kg, respectively. Additionally, the levels of available nitrogen, phosphorus, and potassium were found to be 65.80, 11.24, and 83.95 mg/kg. The soil’s pH was recorded as 8.70 (the pH of the soil–water solution was measured using a pH meter and a water-to-soil ratio of 2.5:1 was maintained).

2.2. Test Materials

Medicago sativa ‘Gannong No. 3’ (GN3), M. sativa ‘Gannong No. 9’ (GN9), M. sativa ‘Juneng No. 7’ (JN7), Leymus chinensis ‘Longmu No. 1’ (LC), Agropyron mongolicum ‘Mengnong No. 1’ (AC), and Bromus inermis ‘Yuanye’ (BI) were chosen as the experimental materials. Alfalfa seeds were supplied by the College of Pratacultural Science of Gansu Agricultural University. Leymus chinensis seeds were provided by the Institute of Grass Industry at the Heilongjiang Academy of Agricultural Sciences, while Agropyron cristatum seeds were sourced from Inner Mongolia Agricultural University. Bromus inermis seeds were purchased from Beijing Zhengdao Seed Industry Company (Supplementary Table S1).

2.3. Experimental Design

A randomized block design was used in this experiment, with 15 distinct treatments that were each repeated three times for a total of 45 experimental plots (Figure 1 and

Table 1. Experimental design.

Cropping Patterns	Treatments
Single cropping	GN3, GN9, JN7, LC, AC, BI
Mixture cropping	GN3 + LC, GN3 + AC, GN3 + BI, GN9 + LC, GN9 + AC GN9 + BI, JN7 + LC, JN7 + AC, JN7 + BI

Note: GN3: Medicago sativa ‘Gannong No. 3’, GN9: M. sativa ‘Gannong No. 9’, JN7: M. sativa ‘Juneng No. 7’, LC: Leymus chinensis ‘Longmu No. 1’, AC: Agropyron mongolicum ‘Mengnong No. 1’, and BI: Bromus inermis ‘Yuanye’.

). The length and width of each experimental section were 5 × 3 m, respectively, with a total area of 15 m². On 1 May 2022, manual trenching was conducted, and strip sowing was performed in alternate rows at a 1:1 ratio. The sowing rates for alfalfa, Leymus chinensis, Agropyron cristatum, and Bromus inermis in the mixed sowing treatment were set at 1.0, 3.0, 1.5, and 3.0 g/m², respectively. In comparison to the mixed sowing rates, the sowing rate for the monoculture was doubled. The optimal sowing depths for Leguminosae and Gramineae were selected to be 2.0 cm and 3.0 cm, respectively. No fertilizer was applied during the experiment. Manual weeding was carried out three times in the sowing year, and sufficient irrigation was provided during the sowing period and after each cutting. All other field management practices were maintained consistently across the plots.

2.4. Measuring Indicators

Cutting and yield measurements were conducted during the early flowering period of alfalfa. The first, second, and third harvests were scheduled for 8 June, 16 July, and 3 September 2023. Edge rows in each plot were removed, resulting in an effective sample area of 9.6 m². The fresh weights of the alfalfa and grasses were measured separately. A sample of 500 g of fresh material was taken from each combination and then dried at 65 °C until a constant weight was achieved. The hay yield of the mixed grassland was calculated based on the fresh grass yield and the dry-to-fresh weight ratio.

Using the multi-point sampling method, we randomly selected five leguminous and five gramineous plant samples from each plot in May, July, and September 2023. After carefully removing the soil surrounding the root systems, we gently brushed off any soil tightly adhered to the roots, mixed the samples, and placed them in a sampling box at 4 °C for transport to the laboratory. Finally, the soil sample was divided into two portions: one portion was stored at 4 °C for the determination of soil microbial biomass. In contrast, the other portion was naturally air-dried for soil enzyme and nutrient analysis.

The soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), and soil moisture content (SWC) were determined using the potassium dichromate volumetric method, the alkaline diffusion method, the molybdenum-antimony colorimetric method, the flame photometry method, and the drying method, respectively [23]. Soil urease (UA) was measured using the indophenol blue colorimetric method. Soil alkaline phosphatase (APA) was measured using the disodium phenyl phosphate colorimetric method. Soil catalase (CAT) was determined by potassium permanganate titration. Soil sucrase (SA) was analyzed using the 3,5-dinitrosalicylic acid colorimetric method [24]. Soil microbial biomass carbon (SMBC) was measured using the chloroform fumigation extraction method followed by potassium dichromate titration. Soil microbial biomass nitrogen (SMBN) was determined through chloroform fumigation extraction combined with the Kjeldahl method. Soil microbial biomass phosphorus (SMBP) was analyzed using chloroform fumigation extraction and the molybdenum antimony anti-colorimetric method [25].

2.5. Statistical Analysis of Data

Microsoft Excel (v 2019) was employed in conjunction with the SPSS (v 26.0) software to conduct one-way ANOVA. Duncan’s multiple range test was utilized for post-hoc comparisons. Correlation analysis was performed using the Origin (v Pro 2021) software. The comprehensive analysis method employs grey relational degree analysis, which ranks factors based on the degree of correlation between each indicator and the reference sequence, determined by the magnitude of the grey relational degree. This ranking allows for the assessment of the relative importance of various factors influencing the mixed-sown grassland. By integrating multiple indicators or factors, the method avoids the limitations of evaluations based on a single indicator. It synthesizes information from multiple dimensions into a comprehensive relational degree indicator, providing a more holistic and objective reflection of the overall performance of the mixed sowing treatment. We conducted grey relational analysis using 13 indicators from different seasons. The calculation formula is presented as follows [26]:

$$\begin{array}{c}\text{Correlation coefficient}:\\ {\zeta }_k={\displaystyle \frac{\frac{\min }{i}\frac{\min }{k}\left|X_0\left(k\right)-X_i\left(k\right)\right|+\rho \frac{\max }{i}\frac{\max }{k}\left|X_0\left(k\right)-X_i\left(k\right)\right|}{\left|X_0\left(k\right)-X_i\left(k\right)\right|+\rho \frac{\max }{i}\frac{\max }{k}\left|X_0\left(k\right)-X_i\left(k\right)\right|}}\end{array}$$

(1)

$$\text{Where} \left|X_0\left(k\right)-X_i\left(k\right)\right| \text{recorded as} {∆}_i\left(k\right), {∆}_i\left(k\right)=\left|X_0\left(k\right)-X_i\left(k\right)\right|,\rho =0.5$$

(2)

$$\text{Correlation degree}:(\mathrm{n} \text{represents the number of samples}) r_i={\displaystyle \frac{1}{n}}{\displaystyle \sum _{k=1}^n{\zeta }_i}\left(k\right)$$

(3)

$$\text{Weight coefficient}: w_i={\displaystyle \frac{r_i}{{\displaystyle \sum r_i}}}$$

(4)

$$\text{Weighted correlation degree}: r_i^{\prime }={\displaystyle \sum _{k=1}^n{w}_i}\left(k\right){\zeta }_i\left(k\right)$$

(5)

3. Results

3.1. Seasonal Variation of Enzyme Activity in Rhizosphere Soil

The enzyme activities in each treatment indicated a seasonal trend of summer > spring > autumn (Figure 2). The soil enzyme activities in all mixed sowing treatments were significantly higher than those in their corresponding monoculture treatments (p < 0.05). During spring, summer, and autumn, compared to the monoculture of GN3, the mixed sowing combinations GN3 + LC, GN3 + AC, and GN3 + BI exhibited increases in SA content by 14.25 to 81.69%, UA by 11.81 to 29.27%, APA by 0.06 to 25.14%, and CAT by 1.27 to 54.79%. When compared to the monoculture of gramineous forages, these combinations showed increases in SA content by 6.34 to 95.41%, UA by 10.92 to 75.55%, APA by 11.22 to 157.76%, and CAT by 3.96 to 75.70%.

Similarly, compared to the monoculture of GN9, the mixed sowing combinations GN9 + LC, GN9 + AC, and GN9 + BI demonstrated increases in SA content by 1.77 to 28.15%, UA by 4.73 to 25.51%, APA by 0.03 to 71.08%, and CAT by 2.27 to 27.61% during spring, summer, and autumn. Relative to the monoculture of gramineous forages, these combinations exhibited increases in SA content by 19.47 to 96.97%, UA by 12.15 to 73.23%, APA by 16.05 to 106.50%, and CAT by 12.38 to 79.88%.

For JN7, the mixed sowing combinations JN7 + LC, JN7 + AC, and JN7 + BI showed increases in SA content by 9.80 to 80.13%, UA by 20.75 to 53.69%, APA by 10.67 to 42.81%, and CAT by 7.35 to 52.37% compared to the monoculture of JN7 during spring, summer, and autumn. When compared to the monoculture of gramineous forages, these combinations exhibited increases in SA content by 0.13 to 62.42%, UA by 23.91 to 66.98%, APA by 32.21 to 148.71%, and CAT by 0.77 to 57.62%.

3.2. Seasonal Variation of Rhizosphere Soil Microbial Biomass

The contents of SMBC, SMBN, and SMBP in all treatments exhibited a seasonal pattern of summer > spring > autumn (Figure 3). The soil microbial biomass carbon, nitrogen, and phosphorus in each mixed sowing treatment were significantly higher than those in their corresponding monoculture treatments (p < 0.05). During spring, summer, and autumn, compared to the monoculture of GN3, the mixed sowing combinations GN3 + LC, GN3 + AC, and GN3 + BI showed increases in SMBC content by 26.54 to 58.98%, SMBN by 25.48 to 142.25%, and SMBP by 70.41 to 301.08%. When compared to the monoculture of gramineous forages, these combinations exhibited increases in SMBC content by 6.52 to 62.41%, SMBN by 68.46 to 278.04%, and SMBP by 1.90 to 264.19%.

Similarly, compared to the monoculture of GN9, the mixed sowing combinations GN9 + LC, GN9 + AC, and GN9 + BI demonstrated increases in SMBC content by 9.72 to 52.97%, SMBN by 9.65 to 223.78%, and SMBP by 27.09 to 306.01% during spring, summer, and autumn. Relative to the monoculture of gramineous forages, these combinations showed increases in SMBC content by 18.65 to 52.24%, SMBN by 30.32 to 327.75%, and SMBP by 95.89 to 402.13%.

For JN7, the mixed sowing combinations JN7 + LC, JN7 + AC, and JN7 + BI exhibited increases in SMBC content by 31.92 to 101.91%, SMBN by 0.72 to 76.51%, and SMBP by 172.23 to 361.39% compared to the monoculture of JN7 during spring, summer, and autumn. When compared to the monoculture of gramineous forages, these combinations showed increases in SMBC content by 8.93 to 51.50%, SMBN by 49.09 to 207.41%, and SMBP by 38.79 to 224.10%.

3.3. Changes in Hay Yield and Soil Nutrients Under Different Mixed Sowing Treatments

3.3.1. Forage Hay Yield

The annual hay yield of GN3, GN9, and JN7 was significantly superior to that of their respective intercropping combinations (p < 0.05). The annual hay yields of GN3 + LC, GN3 + AC, and GN3 + BI were lower than GN3 by 36.46%, 31.15%, and 15.08%, respectively (

Table 2. Hay yield as influenced by treatment and mowing period.

Treatments	The First Mowing/(kg/hm2)	The Second Mowing/(kg/hm2)	The Third Mowing/(kg/hm2)
GN3 + LC	6020 ± 193.7 FG	2743 ± 154.3 G	2193 ± 95.6 F
GN3 + AC	6548 ± 81.0 D	3325 ± 82.5 E	1999 ± 31.1 G
GN3 + BI	7532 ± 71.2 BC	4111 ± 202.8 C	3000 ± 146.3 D
GN3	7667 ± 389.3 B	5227 ± 202.1 A	4350 ± 32.7 A
GN9 + LC	7450 ± 313.2 BC	3696 ± 73.7 D	3830 ± 146.1 C
GN9 + AC	6240 ± 29.9 EF	3317 ± 74.3 E	2442 ± 124.4 E
GN9 + BI	8180 ± 154.4 A	4104 ± 140.5 C	3910 ± 47.3 C
GN9	8261 ± 80.7 A	4974 ± 94.3 B	4268 ± 192.5 AB
JN7 + LC	5770 ± 221.1 G	3462 ± 59.3 E	3002 ± 31.2 D
JN7 + AC	6474 ± 195.0 DE	2497 ± 52.7 H	2920 ± 50.6 D
JN7 + BI	7307 ± 257.5 C	3133 ± 56.9 F	2454 ± 50.9 E
JN7	8060 ± 27.4 A	5038 ± 77.2 B	4119 ± 134.0 B
LC	2464 ± 81.9 H	997 ± 25.2 I	506 ± 5.91 I
AC	1277 ± 29.4 I	428 ± 37.8 J	277 ± 31.1 J
BI	2463 ± 135.2 H	819 ± 44.3 I	666 ± 43.1 H

Note: GN3: Medicago sativa ‘Gannong No. 3’, GN9: M. sativa ‘Gannong No. 9’, JN7: M. sativa ‘Juneng No. 7’, LC: Leymus chinensis ‘Longmu No. 1’, AC: Agropyron mongolicum ‘Mengnong No. 1’, and BI: Bromus inermis ‘Yuanye’. The values are the means ± standard deviation (the degree of deviation is reflected between the data and the average value). Different capital letters indicate significant differences among treatments of different mix combinations in the same season (p < 0.05).

). Similarly, GN9 + LC, GN9 + AC, and GN9 + BI decreased 14.44%, 31.45%, and 7.48% lower than GN9, respectively. JN7 + LC, JN7 + AC, and JN7 + BI all had declines from JN7 of 28.94%, 30.93%, and 25.10%, respectively.

3.3.2. Rhizosphere Soil Nutrients

The contents of SOM, AN, AP, and AK followed the order summer > spring > autumn in each treatment (Figure 4). The nutrient levels of each mixed sowing were significantly higher than those of their respective monocultures (p < 0.05).

During spring, summer, and autumn, the mixed sowing combinations GN3 + LC, GN3 + AC, and GN3 + BI showed increases in SOM content by 0.11 to 59.67%, AN by 7.69 to 77.20%, AP by 9.63 to 102.50%, and AK by 12.88 to 28.46% compared to the monoculture of GN3. When compared to the monoculture of gramineous forages, these combinations exhibited increases in SOM content by 31.52 to 97.43%, AN by 10.97 to 59.37%, AP by 30.34 to 121.89%, and AK by 14.50 to 44.17%.

Similarly, the mixed sowing combinations GN9 + LC, GN9 + AC, and GN9 + BI demonstrated increases in SOM content by 1.09 to 56.24%, AN by 22.10 to 83.07%, AP by 26.33 to 150.17%, and AK by 6.10 to 46.52% compared to the monoculture of GN9. Relative to the monoculture of gramineous forages, these combinations showed increases in SOM content by 27.41 to 103.80%, AN by 18.05 to 108.01%, AP by 62.28 to 156.10%, and AK by 17.64 to 42.39%.

In the case of JN7, the mixed sowing combinations JN7 + LC, JN7 + AC, and JN7 + BI exhibited increases in SOM content by 2.02 to 36.55%, AN by 13.04 to 53.82%, AP by 18.27 to 72.36%, and AK by 10.83 to 36.15% compared to the monoculture of JN7. When compared to the monoculture of gramineous forages, these combinations showed increases in SOM content by 30.71 to 67.15%, AN by 16.71 to 58.17%, AP by 26.82 to 97.64%, and AK by 17.51 to 53.68%.

3.4. Correlation Analysis

The concentrations of SMBC, SMBN, and SMBP for each intercropping treatment and the activities of SA, APA, UA, and CAT show strong or extremely significant positive associations with the rhizosphere soil’s nutrient levels (p < 0.05 or p < 0.01) (Figure 5).

3.5. Comprehensive Evaluation of Rhizosphere Soil

Using grey relational analysis to calculate the ranking of various mixed broadcast combinations (

Table 3. The correlation degree of different legume–gramineae mixtures.

Treatments	Weighted Relevance Degree	Rank
GN3 + LC	0.597	9
GN3 + AC	0.613	6
GN3 + BI	0.689	3
GN3	0.548	11
GN9 + LC	0.719	2
GN9 + AC	0.604	8
GN9 + BI	0.744	1
GN9	0.564	10
JN7 + LC	0.622	5
JN7 + AC	0.605	7
JN7 + BI	0.667	4
JN7	0.523	12
LC	0.516	13
AC	0.485	15
BI	0.500	14

Note: GN3: Medicago sativa ‘Gannong No. 3’, GN9: M. sativa ‘Gannong No. 9’, JN7: M. sativa ‘Juneng No. 7’, LC: Leymus chinensis ‘Longmu No. 1’, AC: Agropyron mongolicum ‘Mengnong No. 1’, and BI: Bromus inermis ‘Yuanye’.

), the results are as follows: GN9 + BI > GN9 + LC > GN3 + BI > JN7 + BI > JN7 + LC > GN3 + AC > JN7 + AC > GN9 + AC > GN3 + LC > GN9 > GN3 > JN7 > LC > BI > AC.

3.6. Cluster Analysis

Cluster analysis was performed using various grey correlation values (Figure 6). When the Euclidean distance was set to 5, the data could be categorized into three distinct groups. The first category of soil demonstrates excellent characteristics, including GN9 + BI, GN9 + LC, GN3 + BI, and JN7 + BI. The second category exhibits good characteristics, comprising JN7 + LC, GN3 + AC, JN7 + AC, GN9 + AC, and GN3 + LC. The third category shows poor performance, represented by GN9, GN3, JN7, LC, BI, and AC.

4. Discussion

4.1. Effects of Legume–Gramineae Mixtures Grassland on Enzyme Activities in Rhizosphere Soil

Soil enzymes are pivotal in the uptake and utilization of nutrient elements by plants, thus serving as a key indicator of soil fertility [27]. Certain researchers have noted that intercropping in grasslands can enhance the efficiency of aerobic respiration by improving soil aeration, which in turn boosts soil enzyme activity [28]. This research found that soil enzyme activity in each intercropping treatment exceeded that of the monoculture treatment, which is consistent with previous studies. This phenomenon involves nitrogen consumption during grass growth, which stimulates leguminous plants to convert atmospheric nitrogen into plant-available ammonium nitrogen through rhizobia, thereby enhancing soil nitrogen availability [29]. This process enhances root activity in mixed-sown grasslands and increases the secretion of root exudates, including organic acids, amino acids, and sugars, which serve as energy and carbon sources for soil microbial activity [30,31]. The heightened microbial activity accelerates the decomposition of soil organic matter, releasing additional nutrients for plant uptake [32]. Furthermore, the increase in microbial populations and their metabolic activities directly contribute to the transformation of various soil compounds, resulting in elevated activities of SA and UA [33]. In addition, specific components of root exudates, such as organic acids, can directly regulate the synthesis and activity of soil enzymes by modulating the soil pH, thereby creating a more favorable environment for enzymatic reactions [34]. In this study, the UA activity of the JN7 + LC significantly increased, which could further facilitate the transformation of organic nitrogen in the soil and promote the hydrolysis of urea, thereby influencing soil nitrogen metabolism [24]. APA plays a crucial role in converting organic phosphorus in the soil into inorganic phosphate, which plants can absorb and utilize [35]. The above-ground biomass of mixed grasslands significantly increases, resulting in a greater interspecies facilitation effect than a competitive effect. This dynamic is more conducive to the accumulation of APA in plants, thereby enhancing APA activity [36]. Mixed sowing can improve soil permeability, promote the decomposition of hydrogen peroxide to release oxygen, and prevent the accumulation of hydrogen peroxide during the metabolic processes of soil and organisms [37]. As a result, mixed sowing demonstrates significantly higher CAT activity compared to monoculture treatments [38]. This study found that the increase in APA and CAT activities in GN9 + BI was greater than in other treatments, indicating that this approach has a higher potential for soil phosphorus conversion, the enhancement of soil permeability, and the decomposition of toxic peroxides.

Previous research has primarily emphasized the influence of individual factors on soil enzyme activity [39], such as the enhancement of soil aeration through intercropping practices while neglecting the intricate ecological interactions involving nitrogen fixation and root exudate dynamics. This study offers a comprehensive exploration of the mechanisms through which legume–grass mixed sowing elevates soil enzyme activity, thereby contributing to a more integrated understanding of soil fertility enhancement in intercropping systems. Nevertheless, detailed investigations into the specific constituents of root exudates and their exact roles in modulating nitrogen fixation and soil enzyme activity remain limited. Future research should prioritize these areas to deepen the understanding of the mechanisms that drive soil enzyme activity variations in legume–grass mixed-sown ecosystems.

4.2. Effects of Legume–Gramineae Mixed Grassland on Microbial Biomass in Rhizosphere Soil

As the most dynamic component of terrestrial ecosystems, soil microorganisms are instrumental in nutrient degradation, humus formation, and the regulation of plant diversity, thus ensuring the proper functioning of the ecosystem [40]. The microbial biomass in the rhizosphere soil of each mixed sowing was significantly higher than that of the monoculture treatment in this research. This may be explained by the complementary ecological niches occupied by diverse plant species in mixed-sown grasslands, which enhances resource utilization efficiency [41]. In particular, root exudates serve as a significant source of carbon and energy for microorganisms while also potentially increasing microbial community diversity and activity through modifications to the soil microenvironment, including changes in pH and redox potential [31]. Furthermore, the plant residues from mixed sowing grasslands increase the organic matter content of the topsoil, supply nutrient sources for microorganisms, and indirectly stimulate the active growth of these microorganisms [32].

Soil enzymes participate in the cycling and transformation of organic and inorganic forms of carbon, nitrogen, and phosphorus. They significantly contribute to the formation of soil organic matter and humus [27]. Soil microorganisms, as the primary source of soil enzymes, exhibit activity levels that are closely correlated with enzyme activity. The observed increase in enzyme activity in this study may be attributed to the abundant carbon sources provided by above-ground wilting materials, which enhance microbial activity [25]. Importantly, soil microorganisms not only synthesize enzymes but may also modulate enzyme activity through positive feedback mechanisms as their populations grow [42]. This study found that the rhizosphere SMBC, SMBN, and SMBP contents of GN9 + BI were the highest. This indicates that the mixed sowing combination may enhance the soil microbial ecosystem through several mechanisms. Firstly, the root morphology and exudates of GN9 and BI likely exhibit complementary characteristics, providing a more balanced nutrient supply for microorganisms [31]. Secondly, the growth cycles and nutrient demands of these two plant species may be temporally offset, which minimizes interspecies competition and improves resource utilization efficiency [43]. In contrast, other mixed sowing combinations may not fully realize their potential benefits due to heightened interspecies competition or less efficient resource utilization.

4.3. Changes in Hay Yield and Soil Nutrients in Legume–Gramineae Mixed Grassland

The mixed sowing of forage species can significantly enhance both the yield and quality of the forage [44,45]. The selection of appropriate intercropping combinations can influence the yield and nutritional quality of the forage [46]. However, some studies have indicated that the yield of a monocultured forage may surpass that of an intercropped forage [47,48]. Three leguminous monocultures in this research produced noticeably more hay than their corresponding mixed grasslands. This might be because the experiment’s mix ratio was 1:1 and twice as many leguminous monocultures were sown in each mixed combination. The leguminous monocultures exhibited greater plant heights than non-leguminous grasses, attributed to the distinct growth characteristics of each group throughout the entire growth period. This difference resulted in a higher hay yield per unit area for the leguminous monocultures compared to their corresponding mixed grasslands. Moreover, the uneven distribution of precipitation in the Hexi region hinders the formation of nitrogen-fixing nodules in leguminous grasses. The competition of leguminous monocultures and grass for nitrogen in the soil limits grass growth and results in lower hay yields in the mixed sowing compared to the monoculture [49].

Soil nutrients are the primary factors that influence the growth of forage grasses in intercropped grasslands and can also serve as a key indicator for assessing soil quality and fertility [50]. Leguminosae and Gramineae root systems have differences in both temporal and spatial distribution, as well as variations in nutrient absorption areas and sensitivity. These differences can help reduce competition for nutrients [10]. The nutrient content of rhizosphere soil in each mixed treatment was significantly higher than that in the monocultures in this research. This is attributed to the fact that mixed grasslands can enhance the diversity of microbial communities in the soil. This increased diversity promotes soil mineralization and effectively raises the nutrient content of the soil [51]. Luo et al. [52] found that mixed sowing was more beneficial for soil microbial activity than using monocultures as it increases soil enzyme activity and promotes the accumulation of soil nutrients. Simultaneous mixed sowing increases the root system per unit volume of soil, increase soil humus, and effectively accumulate soil nutrients [53].

4.4. Seasonal Changes in Soil Enzymes, Microbial Biomass, and Soil Nutrients in the Rhizosphere of Legume–Gramineae Mixed Grassland

The enzyme activity, microbial biomass, and soil nutrients in the rhizosphere soil of each mixed planting treatment were highest in summer and lowest in autumn, consistent with previous research findings [54]. This may be due to the Hexi Corridor’s favorable hydrothermal conditions during the summer, which accelerate plant root growth, enhance soil respiration, boost soil microbial activity, and indirectly promote nutrient transformation and release [55]. In addition, the substantial amount of debris on the surface supplies essential nutrients for the growth of soil microorganisms, leading to an optimal total population of these microorganisms [54].

Leguminous and gramineous plants demonstrate both competitive and complementary dynamics in resource utilization within mixed sowing systems [6]. Gramineous plants exhibit rapid growth and superior competitiveness for resources such as light and water during their early stages [7]. In contrast, leguminous plants grow more slowly during the early stages. As their growth period extends, they gradually begin to utilize their nitrogen-fixing abilities and their symbiotic relationships with microorganisms [29]. For instance, in spring, gramineous plants dominate the uptake of soil moisture and nutrients to support their rapid growth, while leguminous plants focus on establishing symbiotic associations with rhizobia [56]. By summer, the nitrogen-fixing efficiency of leguminous plants increases, providing additional nitrogen to support the growth of gramineous plants [16]. In autumn, as temperatures decline, soil microbial activity decreases, and the interactions among plants, soil, and microorganisms weaken [57]. This seasonal variation explains the observed declines in soil enzyme activity, microbial biomass, and nutrient content during autumn compared to summer and spring. Studies have demonstrated that water significantly enhances the effectiveness of soil nutrients and facilitates the transfer of nitrogen within the soil [58]. The rate of nitrogen transfer tends to increase with the increase in water content [56]. An optimal soil moisture content engenders a highly conducive soil environment [59]. In such an environment, the solubility of nutrient elements in the soil is markedly enhanced, and the migration rate of these nutrients is significantly accelerated [60]. This enhanced condition provides an abundant supply of nutrients for the growth of microorganisms, substantially augmenting their activity [61]. Consequently, a larger quantity of soil enzymes is synthesized, thereby constructing a virtuous material cycle chain.

Correlation analysis revealed a significant positive relationship between soil nutrients, enzyme activities, and microbial biomass, highlighting the synergistic interactions between soil enzymes and microbial biomass, as well as the critical role of soil nutrients in facilitating this interdependence. This study further elucidated the distinct effects of different mixing combinations on soil nutrient dynamics, microbial communities, and enzymatic activities. Particularly, the GN9 + BI treatment demonstrated a marked increase in microbial biomass and activity compared to monoculture systems, which may be attributed to enhanced resource utilization efficiency and diminished interspecific competition. Additionally, this treatment led to elevated soil nutrient levels, thereby reinforcing the positive correlation among soil nutrients, enzymatic activities, and microbial biomass.

5. Conclusions

Significant seasonal variations in grass yield and soil characteristics are observed across different mixed sowing combinations. The activities of SA, UA, APA, CAT, SMBC, SMBN, SMBP, SOM, AN, AP, AK, and SWC in rhizosphere soil follow the order of summer > spring > autumn. The soil enzyme activity, microbial biomass, and soil nutrients of each mixed sowing were significantly higher than those of their respective monoculture in the same season. The hay yield of the legume monoculture treatment was significantly higher than that of the corresponding mixed sowing combination. Correlation analysis indicated that soil enzymes and microbial biomass are positively correlated with soil nutrients. The comprehensive evaluation and cluster analysis indicated that the GN9 + BI and GN9 + LC treatments perform well, making them the optimal mixed sowing combinations for the Hexi Oasis irrigation area. Based on the research findings, the following seasonal management strategies should be adopted in the Hexi irrigation area: enhance water and fertilizer management during summer, implement fertilization and irrigation earlier in spring, and prioritize soil conservation in autumn. Additionally, the mixed sowing approach should be promoted in ecologically fragile regions, such as the Hexi Irrigation District, and integrated into long-term agricultural planning to improve soil resilience against degradation and provide robust support for the sustainable development of regional agriculture.