Optimizing Seeding Ratio for Legume Forage to Maximize System Productivity and Resource Use Efficiency in Mixed Cropping Systems

Abstract

Cereal and legume mixed cropping has been widely adopted to increase forage production in the sustainable development of agriculture and livestock. Among the different mixed cropping combinations, forage sorghum and lablab bean mixed cropping can be adapted globally. However, knowledge regarding the relation between forage production, interspecific competition, and resource utilization efficiency in the forage sorghum and lablab bean mixed cropping system remains unclear. A 3-year field experiment was conducted in 2020, 2021, and 2022 to investigate the effects of different cropping systems (16.5 kg·ha⁻¹ lablab bean mixed cropping with forage sorghum [SD1], 33.0 kg·ha⁻¹ lablab bean mixed cropping with forage sorghum [SD2], 49.5 kg·ha⁻¹ lablab bean mixed cropping with forage sorghum [SD3], 66.0 kg·ha⁻¹ lablab bean mixed cropping with forage sorghum [SD4], sole forage sorghum [SS], and sole lablab bean [DD]) on forage production, forage quality, competition parameters, water use efficiency (WUE), and radiation use efficiency (RUE). The results obtained revealed that mixed cropping practices enhanced forage yield by mitigating soil water depletion and optimizing canopy structures. Specifically, SD3 treatment was an efficient farming practice that increased system dry matter yield by 32.6–67.5%, crude protein yield by 12.5–15.1%, WUE by 9.2–67.4%, and RUE by 39.6–38.2% compared with other treatments. In addition, SD4 treatment increased crude protein content by 11.1% compared with forage sorghum monocropping; however, there were no significant differences in crude protein between SD3 and SD4 mixed cropping systems. The land equivalent ratio values were greater than one when forage sorghum was mixed with lablab bean, especially for the SD3 system (averaged 1.43). In addition, forage sorghum was more dominant and had higher aggressiveness (0.65) and competitive ratios (3.44) than lablab bean. This indicates that mixing cereals with legumes enhances RUE by interspecific competition. Consequently, the SD3-mixed cropping system is recommended for supporting the sustainable development of agriculture and livestock production in the arid region of China when considering forage production and nutritional quality.

1. Introduction

Livestock production is an integral part of agricultural production as well as the income of farmers in developed and developing countries. Meat, egg, and milk production in China in 2021 was 66.2% higher than it was 20 years ago, which will lead to severe feed shortage problems [1]. Therefore, a sustainable, high-yield, and high-quality forage production system is urgently required owing to the rapid growth of the livestock industry. The arid region of Ningxia is an important area for livestock production in China and is located at the border of the Loess Plateau and the Mu Us Desert [2]. However, in addition to the fragile ecological environment and severe wind-induced soil erosion, the scarcity and low quality of forage are the main factors limiting local livestock production [3,4]. Consequently, there is a need to develop sustainable agriculture techniques and select forage management measures that meet this demand.

Cereal and legume mixed cropping is an important strategy for meeting increased forage demand and using land efficiently in modern Chinese agriculture, and it has been widely adopted worldwide [5,6]. Husse et al. [7] reported that mixed cropping increases forage yield by 23–31% compared with monoculture. Tao et al. [8] reported that mixed cropping has an average land equivalent ratio (LER) of 1.18–1.23 compared with monoculture. In addition, probably research have reported that interspecific interactions play a key role in facilitating efficient resource use when the two crops are grown together [5]. In particular, competition between crops can enhance or offset yield benefits by altering the species composition within a mixed cropping system [7]. Mao et al. [9] found that through this competitive effect, the yield of the mixed cropping system increased by 23–34%. However, competitive effects can also reduce crop yields. For example, Armstrong et al. [10] reported that dry matter yield of maize + velvet bean was decreased by 11.5% and 5.8% in maize + scarlet runner bean over maize alone. Therefore, choosing proper crops and a mixed cropping system is critical to increasing forage yield while maintaining high quality.

Sorghum (Sorghum bicolor L.) is a C₄ crop known for its high biomass production, robust photosynthetic and carbon uptake capabilities, abundant fiber and starch content, and exceptional water efficiency [11]. Lablab bean (Lablab purpureus L.) is an annual or perennial legume with vigorous tendrils, well-developed main roots, and strong nitrogen-fixing capabilities. A mixed cropping system of these two crops represents a new cereal/legume crop [12] with superior nutritional quality owing to better crude protein (CP) and other nutritional values [13]. Notably, mixed cropping is an efficient use of water. Studies suggest that mixed cropping improves water use efficiency (WUE) through a rational combination of crops and the spatial arrangement of root systems to coordinate water demand periods [14]. For example, the WUE of proso millet increased by 13.3–53.5% in a proso millet/mung bean intercropping system [15]. In addition, the WUE of wheat was significantly increased by 5.2–16.9% in a wheat/maize mixed cropping system [16]. The arid region of Ningxia is strongly characterized by a semiarid monsoon climate, and precipitation varies greatly. Therefore, how growth and forage yield in a forage sorghum/lablab bean mixed cropping system respond to water availability remains uninvestigated. Furthermore, light is particularly important for crop growth; the yield advantage with mixed cropping system is associated with greater light resource use resulted from optimizing the canopy structure to capture more interception of photosynthetically active radiation (PAR) compared with sole cropping. Husse et al. [7] reported that the total light interception rate of forage sorghum and lablab bean mixed cropping was 29.2% higher than that of monoculture, resulting in a 16.0% increase in forage yield. In addition, Gong et al. [17] reported that proso millet/mung bean intercropping increased radiation use efficiency (RUE) by 18.0% and yield by 21.9% compared with monoculture. However, the relation between forage yield and intercepted PAR in mixed cropping systems, as well as forage quality, depends on the proportion of components in the mixtures, especially the proportion of legumes [18], and is an important determinant for realizing the potential increase in nutritional value [19]. Therefore, optimizing the seeding ratio of lablab bean in forage sorghum/lablab bean mixed cropping systems to achieve the multiple goals of agricultural and livestock sustainability is worthwhile.

Hence, the objectives of this study are (i) to evaluate the impact of lablab bean seeding ratio on forage yield and nutritional quality in mixed cropping systems; (ii) to assess the relationship between forage productivity and interspecific competition, water utilization, and RUE under different mixed cropping systems; and (iii) to explore the optimal mixed cropping systems according to WUE, RUE, productivity, and nutritional indices.

2. Materials and Methods

2.1. Site and Experiment Set Up

Field experiments were conducted in Sidunzi, Yanchi County, Ningxia, China (N 37°46′26″, E 107°26′16″; elevation: 1460 m) from 2020 to 2022. The climate of the study site is temperate continental monsoon, and precipitation exhibits irregular patterns and is primarily concentrated around mid-May to early September. The average annual total hours of sunshine and growing days were 2303.5 and 242, respectively [20]. The physicochemical properties of the soil in the experimental area are characterized as gray desert with a pH value of 8.5. At 0–30 cm depth of the soil, the organic matter, total N, available P, and available K determined prior to any tillage practices were 6.78 g·kg⁻¹, 0.76 g·kg⁻¹, 12.45 mg·kg⁻¹, and 137.33 mg·kg⁻¹, respectively. Figure 1. illustrates the average air temperature and precipitation recorded monthly during the course of the experiment.

2.2. Experimental Design and Field Management

The field experiment was conducted in a randomized complete block design with four replications. “Green Hulk” [forage sorghum (Sorghum bicolor L.)] and “Rungao” [lablab bean (Lablab purpureus L.)] were selected, and the seeds were provided by Beijing Best Grass Industry Co., Ltd., Beijing, China. The experiment included four mixed cropping treatments, sole forage sorghum, and sole lablab bean. The seeding rate in the mixed cropping system was 18.0 kg·ha⁻¹ for forage sorghum and 16.5 kg·ha⁻¹ (SD1), 33.0 kg·ha⁻¹ (SD2), 49.5 kg·ha⁻¹ (SD3), and 66.0 kg·ha⁻¹ (SD4) for lablab bean, respectively. The seeding rates in monocropping forage sorghum and lablab bean were 18.0 kg·ha⁻¹ and 49.5 kg·ha⁻¹, respectively.

Forage sorghum and lablab bean were sown on 2 May 2020, 5 May 2021, and 8 May 2022. The spacing between forage sorghum plants was 23 cm, and row spacing was 30–70–30–70 cm (alternating row spacing). Lablab bean was planted next to forage sorghum in mixed cropping, and the cropping patterns of each system are shown in Figure 2. According to local fertilization recommendations, apply before sowing at rates equivalent to urea (N, 46%) 180 kg N ha^–1 and diammonium phosphate 120 kg P ha^–1, respectively. Forage crops were harvested on 10 September 2020, 11 September 2021, and 14 September 2022. Soil drip irrigation was used in the experiment, with 100 cm interval of drip tape and 30 cm interval of drip head and a plant growth stage irrigation volume of 2600 m³ ha⁻¹ in 2020 and 2022 and 3300 m³ ha⁻¹ in 2021.

2.3. Measurements and Calculations

2.3.1. Interspecific Competition and System Productivity Index

The land equivalent ratio (LER) was calculated by using the following equation:

$$\mathrm{LER}={\displaystyle \frac{{\mathrm{Y}}_{\mathrm{SD}}}{{\mathrm{Y}}_{\mathrm{SS}}}}+{\displaystyle \frac{{\mathrm{Y}}_{\mathrm{DS}}}{{\mathrm{Y}}_{\mathrm{DD}}}}$$

(1)

where Y_DD and Y_SS are yields of pure stands of lablab bean and forage sorghum and Y_DS and Y_SD are yields of lablab bean and forage sorghum in the mixed cropping system, respectively. LER values greater than 1 indicate an advantage of mixed cropping over monoculture.

Aggressivity (A) represents an increase or decrease in the yield of one plant relative to another in a mixed cropping system [9,21]. If A is >0, it means that the species is more competitive than the other species; if A = 0, the competition between the two species is equal, and if A is <0, the competition between the species is less than that of the other species. A is calculated from the equation below:

$${\mathrm{A}}_{\mathrm{S} }={\displaystyle \frac{{\mathrm{Y}}_{\mathrm{SD}}}{{\mathrm{Y}}_{\mathrm{SS}}\times {\mathrm{X}}_{\mathrm{SD}}}}-{\displaystyle \frac{{\mathrm{Y}}_{\mathrm{DS}}}{{\mathrm{Y}}_{\mathrm{DD}}\times {\mathrm{X}}_{\mathrm{DS}}}}$$

(2)

where X_DS is the ratio of lablab bean to mixed cropping and X_SD is the ratio of forage sorghum to mixed cropping. If A_S > 1 is positive, then the forage sorghum is more competitive than lablab bean; if A_S = 0, forage sorghum and lablab bean are equally competitive; and if A_S < 1 is negative, then the forage sorghum is less competitive than lablab bean.

The competition ratio (CR) can represent the competitive strength of crops in a mixed cropping system, and the CR was calculated from the following equations:

$${\mathrm{CR}}_{\mathrm{S} }={\displaystyle \frac{{\mathrm{LER}}_{\mathrm{S}}}{{\mathrm{LER}}_{\mathrm{D}}}} \times {\displaystyle \frac{{\mathrm{X}}_{\mathrm{DS}}}{{\mathrm{X}}_{\mathrm{SD}}}}$$

(3)

$${\mathrm{CR}}_{\mathrm{D}}={\displaystyle \frac{{\mathrm{LER}}_{\mathrm{D}}}{{\mathrm{LER}}_{\mathrm{S}}}} \times {\displaystyle \frac{{\mathrm{X}}_{\mathrm{SD}}}{{\mathrm{X}}_{\mathrm{DS}}}}$$

(4)

where LER_D and LER_S represent LUE of lablab bean and forage sorghum, respectively. The greater the CR value, the more competitive the crop is.

2.3.2. Soil Water Content and Soil Water Storage

Soil samples (5.5 cm in diameter) were drilled and dried at 0–200 cm soil depth, and soil water content (SWC) was measured every 20 cm. The measurements were carried out before the sowing period and at the harvesting stages. Five soil samples were collected at random locations from each plot. All three samples from the same treatment area were pooled into one sample and thoroughly mixed for analysis. The drying method was used to determine SWC and soil water storage (SWS) [20]:

$$\mathrm{SWC}= ({\mathrm{Z}}_1-{\mathrm{Z}}_2)/{\mathrm{Z}}_{2 }· 100\%$$

(5)

$$\mathrm{SWS}=\mathsf{\Sigma }\mathrm{S}{\mathrm{Z}}_{\mathrm{n}} \times \mathrm{B}{\mathrm{D}}_{\mathrm{n}} \times \mathrm{H} \times 10/100$$

(6)

where Z₁ (g) is the wet weight of the soil and Z₂ (g) is the dry weight of the soil. SWS is the soil water storage, SZ_n (mm) is the SWC (%) in layer n, BD_n (g cm⁻³) is the soil bulk density (g cm⁻³) in layer n, and H is the thickness of 20 cm.

2.3.3. Evapotranspiration

Evapotranspiration (ET) during the growth period (from sowing to harvest) of sorghum and lablab bean is calculated using the soil water balance equation [22]:

$$\mathrm{ET}=\mathsf{\Delta }\mathrm{S}+\mathrm{P}+\mathrm{I}+\mathrm{U}-\mathrm{R}-\mathrm{D}$$

(7)

where ΔS is the change in water storage in the 0–100 cm soil layer (mm), P is the total rainfall in the growing season (mm), I is the total irrigation rate (mm), U is the total upward capillary flow into the root zone (mm), R is the surface runoff (mm), and D is the total lower root zone drainage below the 100 cm soil layer. Since the soil surface of each experimental plot is flat and the groundwater level is 2.5 m below the soil surface, the values of R and U are assumed to be negligible. No flood events occurred during the 3 years, so deep drainage is meaningless.

2.3.4. Water Use Efficiency

Water use efficiency (WUE), the WUE of crude protein yield (WUE_CPY), and irrigation water use efficiency (WUE_I) were calculated from the following equations [23]:

$$\mathrm{WUE}=\mathrm{DM}/\mathrm{ET}$$

(8)

$${\mathrm{W}\mathrm{U}\mathrm{E}}_{\mathrm{C}\mathrm{P}\mathrm{Y}} = \mathrm{CPY}/\mathrm{ET}$$

(9)

$${\mathrm{WUE}}_{\mathrm{I}} = \mathrm{DM}/\mathrm{I}$$

(10)

where DM is the dry matter yield (t·ha⁻¹) and ET (mm) is the evapotranspiration. CPY is crude protein yield (t·ha⁻¹) and I (mm) is the total irrigation amount [24].

2.3.5. Photosynthetically Active Radiation and Leaf Area Index

Each treatment of PAR and leaf area index (LAI) of the mixed cropping system was measured between 10:30 and 14:00 on a sunny day, and each measurement was in triplicate at different heights using an AccuPAR LP-80 linear probe meter (METER Group, Inc., Pullman, WA, USA). The canopy was divided into upper (half canopy height) and lower (soil surface) areas according to the number of plant nodes. At least five measurements of PAR and LAI were taken at each height of different plots and measured vertically from bottom to top. Intercepted PAR (IPAR) (MJ·m^–2) and RUE (g·MJ⁻¹) were determined as follows [25]:

$$\mathrm{RUE}={\displaystyle \frac{\mathrm{DM}}{\mathsf{\Sigma }\mathrm{IF}}}$$

(11)

where DM is the dry matter yield (t·ha⁻¹) and I is the daily input PAR (MJ·m^–2). The daily total radiation value was multiplied by 0.5 for the conversion of total radiation to PAR. F represents the proportion of IPAR in a certain day. Therefore, F is used to calculate the cumulative IPAR of different cropping patterns.

2.3.6. Dry Matter Yield

Plant samples were collected during the forage sorghum heading period, and samples were collected by hand cutting from the ground from three randomly selected 2.3 m² (1 m × 2.3 m) locations in each plot. A subsample of three randomly selected holes from each plot was returned to the laboratory, and the samples were dried at 65 °C to a constant weight to determine dry matter yield, which was converted to dry matter yield and expressed in t·ha⁻¹.

2.3.7. Nutritional Value

Prior to nutrient content determination, dried forage sorghum and lablab bean were ground and passed through a 1 mm sieve. Ground lablab bean samples were mixed with forage sorghum samples based on the percentage contribution of lablab bean to total yield, and the mixed samples were analyzed for feed nutritional value by near-infrared reflectance spectroscopy (SN 117618, Berlin, Germany). The main quality components included CP, acid detergent fiber (ADF), neutral detergent fiber (NDF), and relative feed quality (RFQ) was calculated using ADF and NDF.

$$\mathrm{RFQ}=82.38-(0.7515\times \mathrm{ADF}) \times 120/\mathrm{NDF}/1.23$$

(12)

2.4. Statistical Analyses

All experimental data were analyzed using Microsoft Excel 2019, and graphs were generated using Origin Pro 2021b. SPSS 23.0 software was used to determine the differences between mixed cropping systems and years by analysis of variance (ANOVA), and means were compared using the Tukey HSD test at α = 0.05.

3. Results

3.1. Forage Sorghum and Lablab Bean Competition

The land equivalent ratio (LER) was significantly affected by the year and treatment (Figure 3A–C). There were no differences in the LER between the SD3 and SD2 treatments; however, the LER of the SD3 and SD4 treatments were on average significantly higher (by 10.4%) than that of the SD1 treatment. The LER of the SD3 treatment obtained the highest value (1.44), showing an increase of 14.9% compared with that of the SD1 treatment (p < 0.05).

The aggressivity (A) was significantly affected by year, treatment, and their interaction (Figure 3D–F). In 2020, the A_S values varied from −0.13 to 0.74 and the A_D values varied from −0.74 to 0.13. In 2021, the A_S values varied from 0.28 to 1.05 and the A_D values varied from −0.28 to −1.15. In 2022, the A_S values ranged from 0.53 to 0.91 and the A_D values varied from −0.53 to −0.91.

The competition ratio (CR) was significantly affected by year, treatment, and their interaction (Figure 3G–I). In 2020, there was no difference in the CR_S between the SD3 and SD4 treatments; however, CR_S was on average significantly higher (by 75.0% and 53.8%) than that of the SD1 and SD2 treatments, respectively. The CR_D in 2020 in the SD1 treatment was significantly higher than that in the SD2, SD3, and SD4 treatments by 46.1%, 73.0%, and 76.5%, respectively (p < 0.05). In 2021, the highest CR_S was obtained under the SD4 treatment, which was 79.8% and 57.6% higher compared with the those in the SD1 and SD2 treatments, respectively. CR_D in 2021 of the SD1 treatment was significantly higher (0.75), showing an increase of 53.3%, 78.7%, and 80.0% compared with those in the SD2, SD3, and SD4 treatments, respectively. In 2022, the CR_S of the SD4 treatment was the highest, which was 43.3% higher than the average CR_S of the SD1 and SD2 treatments. In addition, the CR_D of the SD1 treatment was significantly higher those of the SD2, SD3, and SD4 treatments by 36.7%, 53.1%, and 55.1%, respectively (p < 0.05). SD3 and SD4 have higher CR_S in 2021 than in 2020 and 2022, whereas SD1 and SD2 have the highest CR_S in 2022.

3.2. Soil Water Content and Water Use Efficiency

There was a significant difference in the soil water content (SWC) at the 0–200 cm soil layers from the sowing to the harvesting stage among the different treatments (Figure 4A–C; p < 0.05). In 2020, the SWC values were in the order SD1 (13.67%) > SS (13.04%) > SD2 (12.98%) > SD4 (12.13%) > SD3 (11.70%) > DD (9.31%) (Figure 4A). In 2021, the SWC values were in the order SS (12.71%) > SD1 (12.43%) > SD4 (12.26%) > SD2 (12.12%) > SD3 (11.43%) > DD (10.30%) (Figure 4B). In 2022, the SWC values were in the order SS (12.67%) > SD1 (11.99%) > SD4 (11.75%) > SD2 (11.62%) > SD3 (11.12%) > DD (10.54%) (Figure 4C).

Evapotranspiration (ET) varied among treatments, but there was no significant effect of the year and treatment × year interaction. In 2020 and 2021, ET in the SD3 treatment had significantly lower values, which were 363.81, and 322.25 mm, respectively, and decreased by 10.90%, and 11.58% compared with the SS (

Table 1. Effect of mixed cropping patterns on evapotranspiration, WUE, WUE_CPY, and WUE_I from 2020 to 2022.

Year	Treatment	Evapotranspiration (mm)	Water Use Efficiency (kg ha−1 mm−1)	Water Use Efficiency for Crude Protein Yield (kg ha−1 mm−1)	Irrigation Water Use Efficiency (kg ha−1 mm−1)
2020	SS	406.0 ± 7.33 b	61.52 ± 1.11 d	5.72 ± 0.10 d	96.00 ± 2.20 d
	DD	422.6 ± 2.54 a	31.98 ± 0.19 e	4.64 ± 0.03 e	51.98 ± 1.11 e
	SD1	382.1 ± 4.41 c	78.83 ± 0.91 c	5.70 ± 0.07 d	115.81 ± 2.49 c
	SD2	392.2 ± 3.30 bc	84.66 ± 0.71 b	9.44 ± 0.08 c	127.69 ± 2.09 b
	SD3	363.8 ± 7.78 d	97.61 ± 2.09 a	11.37 ± 0.24 a	136.46 ± 0.94 a
	SD4	388.9 ± 3.08 c	82.35 ± 0.65 b	10.22 ± 0.08 b	123.15 ± 2.84 b
2021	SS	357.4 ± 5.06 b	63.01 ± 0.89 d	5.80 ± 0.08 d	68.21 ± 2.25 d
	DD	388.0 ± 1.60 a	29.59 ± 0.12 e	4.18 ± 0.02 e	34.79 ± 0.54 e
	SD1	331.0 ± 3.40 cd	80.76 ± 0.83 c	8.60 ± 0.09 c	80.67 ± 2.16 c
	SD2	338.0 ± 2.32 c	86.03 ± 0.59 b	9.68 ± 0.07 b	88.12 ± 1.23 ab
	SD3	322.3 ± 5.36 d	94.89 ± 1.58 a	11.08 ± 0.18 a	92.61 ± 2.32 a
	SD4	334.7 ± 3.15 c	81.31 ± 0.77 c	9.90 ± 0.09 b	82.45 ± 2.90 bc
2022	SS	399.6 ± 1.16 b	55.21 ± 0.16 d	4.87 ± 0.01 e	84.84 ± 0.87 d
	DD	465.1 ± 1.52 a	27.48 ± 0.09 e	3.93 ± 0.01 f	49.16 ± 1.69 e
	SD1	345.7 ± 1.75 e	73.03 ± 0.37 c	7.78 ± 0.04 d	97.11 ± 1.47 c
	SD2	362.2 ± 1.68 d	77.77 ± 0.36 b	8.62 ± 0.04 c	108.33 ± 1.28 b
	SD3	363.2 ± 1.95 d	81.07 ± 0.44 a	9.19 ± 0.05 a	113.24 ± 1.22 a
	SD4	387.9 ± 2.13 c	72.24 ± 0.40 c	9.06 ± 0.05 b	107.78 ± 1.69 b
Variation source
Year		NS	NS	NS	NS
Treatment		**	**	**	**
Year × Treatment		NS	NS	NS	NS

Different letters represent significant differences among all treatments (p < 0.05). NS, not significant. **, p < 0.01.

; p < 0.05).

The water use efficiency (WUE), water use efficiency of crude protein yield (WUE_CPY), and irrigation water use efficiency (WUE_I) were significantly affected by treatment interactions. In addition, the 3-year experiment revealed that the mixed cropping treatment significantly increased WUE, WUE_CPY, and WUE_I, and the average order was SD3 > SD2 > SD4 > SD1 > SS > DD (Table 1). Specifically, the 3-year average shows that, compared with the SS, DD, SD1, SD2, and SD4 treatments, the average WUE in the SD3 treatment significantly increased by 34.3%, 67.4%, 14.9%, 9.1%, and 13.8%, respectively (Table 1). The 3-year average indicates that the WUE_CPY of the SD3 treatment was significantly higher by 59.1%, 45.2%, and 34.0% of the average values of the SS, DD, SD1, SD2, and SD4 treatments (Table 1; p < 0.05). The 3-year average shows that, the WUE_I in the SD3 treatment exhibited significantly higher values, which were 42.1% (136.46 kg·ha⁻¹·mm⁻¹), 35.8% (92.61 kg·ha⁻¹·mm⁻¹), and 33.0% (113.24 kg·ha⁻¹·mm⁻¹) higher compared with the SS (Table 1; p < 0.05).

3.3. Leaf Area Index and Radiation Use Efficiency

The leaf area index (LAI) was significantly affected by the treatment. In 2020, the LAI in the SD3 and SD4 treatments had significantly higher values, which were 7.12 and 6.91, respectively, resulting in an increase of 25.8% and 22.1% compared with the SS, and an increase of 34.2% and 32.1% compared with the DD (Figure 5A). In 2021 and 2022, there was no difference in the LAI between the SD2, SD3, and SD4 treatments, but were on average significantly 6.9%, 14.3%, and 12.8% higher than that of the SS, and significantly 24.9%, 29.6%, and 28.8% higher compared to the DD (Figure 5B,C; p < 0.05).

The intercepted photosynthetically active radiation (IPAR) and radiation use efficiency (RUE) were significantly affected by year, treatment, and year × treatment interaction (Figure 5D–I). In 2020, 2021, and 2022, there was no difference in the IPAR between the SD3 and SD4 treatments; however, it was significantly higher than SD1, SD2, SS, and DD (Figure 5D). The IPAR of the mixed treatments was significantly greater than that of the monoculture treatments, with an average increase of 6.9%, 4.7%, and 2.0%, respectively, in the mixed treatments compared with the monoculture treatments. In addition, in 2020, 2021, and 2022, the RUE in the SD3 treatment had significantly higher values, which were 2.75, 2.42, and 2.31 g·MJ⁻¹, respectively, and increased by 22.7%, 24.7%, and 20.3% compared with the average values of SS, DD, SD1, SD2, and SD4 treatments (Figure 5G–I; p < 0.05), respectively.

3.4. Dry Matter Production

The lablab bean dry matter (DM), forage sorghum DM, and systems DM were significantly affected by year, treatment, and their interaction (

Table 2. Effect of mixed cropping patterns on forage yield during 2020–2022.

Year	Treatment	Lablab Bean Yield (t·ha−1)	Forage Sorghum Yield (t·ha−1)	Total Yield (t·ha−1)	Crude Protein Yield (t·ha−1)
2020	SS	-	25.0 ± 0.99 c	24.9 ± 0.99 d	2.3 ± 0.06 cd
	DD	13.5 ± 0.50 a	-	13.5 ± 0.50 e	2.0 ± 0.08 d
	SD1	4.6 ± 0.08 bc	25.6 ± 0.62 c	30.1 ± 0.65 cd	3.2 ± 0.08 c
	SD2	5.4 ± 0.16 b	27.8 ± 0.68 b	33.2 ± 0.54 b	3.7 ± 0.02 b
	SD3	4.5 ± 0.12 c	31.0 ± 0.37 a	35.5 ± 0.24 a	4.1 ± 0.06 a
	SD4	4.6 ± 0.17 bc	27.4 ± 0.57 bc	32.0 ± 0.74 bc	4.0 ± 0.09 a
2021	SS	-	22.5 ± 0.74 c	22.5 ± 0.74 d	2.1 ± 0.04 d
	DD	11.5 ± 0.31 a	-	11.5 ± 0.31 e	1.6 ± 0.04 e
	SD1	3.0 ± 0.26 b	23.6 ± 0.86 bc	26.6 ± 0.71 c	2.8 ± 0.10 c
	SD2	3.1 ± 0.15 b	26.0 ± 0.51 ab	29.1 ± 0.41 ab	3.3 ± 0.14 b
	SD3	2.4 ± 0.14 b	28.2 ± 0.89 a	30.6 ± 0.77 a	3.6 ± 0.06 a
	SD4	2.5 ± 0.25 b	24.7 ± 0.71 bc	27.2 ± 0.96 bc	3.3 ± 0.08 ab
2022	SS	-	22.1 ± 0.22 d	22.1 ± 0.22 c	2.0 ± 0.02 d
	DD	12.8 ± 0.76 a	-	12.8 ± 0.76 d	1.8 ± 0.11 d
	SD1	2.2 ± 0.07 c	23.1 ± 0.45 cd	25.3 ± 0.38 b	2.7 ± 0.03 c
	SD2	3.0 ± 0.05 bc	25.2 ± 0.37 ab	28.2 ± 0.34 a	3.1 ± 0.07 b
	SD3	3.4 ± 0.24 b	26.0 ± 0.21 a	29.4 ± 0.32 a	3.3 ± 0.22 ab
	SD4	4.0 ± 0.03 b	24.1 ± 0.46 bc	28.0 ± 0.44 a	3.5 ± 0.10 a
Variation source
Year		**	**	**	**
Treatment		**	**	**	**
Year × Treatment		**	*	**	**

Different letters represent significant differences among all treatments (p < 0.05). **, p < 0.01; *, p < 0.05.

). The lablab bean DM in DD increased by 60.2–67.1%, 73.3–79.5%, and 69.0–83.0% in 2020, 2021, and 2022, respectively, compared with the lablab bean component of the SD1, SD2, SD3, and SD4 treatments (Table 2). The forage sorghum DM was the highest in the SD3 treatment (13.06% in 2020, 16.46% in 2021, and 10.36% in 2022) and significantly higher compared with the average values of the SD1, SD2, SD3, and SD4 treatments (Table 2; p < 0.05). In 2020, 2021, and 2022, the SD3 treatment exhibited the highest system DM values and was higher by 17.9%, 15.9%, and 13.8% than the average values of the SS, SD1, SD2, and SD4 treatments (Table 2).

The crude protein yield (CPY) was significantly affected by year, treatment, and their interaction (Table 2). In 2020, the highest CPY of 4.13 kg·ha⁻¹ was obtained in the SD3 treatment, which was greater by 43.8%, 52.5%, 22.3%, and 10.4% compared with those obtained in the SS, DD, SD1 and SD2 treatments (p < 0.05, Table 2). In 2021 and 2022, there was no difference among the CPY of the SD3 and SD4 treatments, but both were significantly higher than that of the SS treatment by 39.8% and 43.1%, respectively.

3.5. Nutritional Value

The crude protein (CP) differed among treatments (

Table 3. Effect of mixed cropping patterns on crude protein, neutral detergent fiber, acid detergent fiber, and relative feeding quality from 2020 to 2022.

Year	Treatment	Crude Protein (%)	Neutral Detergent Fiber (%)	Acid Detergent Fiber (%)	Relative Feeding Quality
2020	SS	9.3 ± 0.13 f	59.4 ± 0.43 d	32.6 ± 1.56 b	95.0 ± 1.19 d
	DD	14.5 ± 0.20 a	469.0 ± 0.55 a	29.5 ± 0.76 ab	125.3 ± 2.25 a
	SD1	10.7 ± 0.09 e	56.4 ± 0.69 bc	32.9 ± 0.89 b	99.8 ± 2.16 c
	SD2	11.2 ± 0.15 d	58.5 ± 0.55 cd	32.3 ± 1.52 b	97.0 ± 0.21 c
	SD3	11.7 ± 0.12 c	52.5 ± 0.97 b	31.9 ± 1.21 b	112.0 ± 2.71 bc
	SD4	12.4 ± 0.14 b	54.3 ± 0.69 bc	26.7 ± 0.87 a	108.6 ± 2.65 bc
2021	SS	9.2 ± 0.18 e	59.4 ± 1.23 c	33.4 ± 0.84 d	94.1 ± 3.25 d
	DD	14.1 ± 0.10 a	46.1 ± 0.42 a	28.1 ± 0.56 ab	129.6 ± 2.31 a
	SD1	10.6 ± 0.14 d	55.3 ± 0.25 bc	31.2 ± 0.25 bc	104.1 ± 3.68 c
	SD2	11.2 ± 0.32 cd	58.0 ± 0.55 bc	30.4 ± 0.98 b	100.2 ± 4.56 c
	SD3	11.7 ± 0.13 bc	53.1 ± 0.98 b	32.1 ± 0.5 c	112.2 ± 5.68 c
	SD4	12.2 ± 0.51 b	54.1 ± 0.65 b	26.9 ± 0.34 a	107.0 ± 6.78 bc
2022	SS	8.8 ± 0.05 d	60.0 ± 1.11 c	33.1 ± 0.91 c	93.5 ± 2.12 d
	DD	14.3 ± 0.06 a	46.0 ± 0.34 a	28.0 ± 0.76 a	130.1 ± 3.13 a
	SD1	10.6 ± 0.07 c	56.1 ± 0.43 bc	30.0 ± 0.52 ab	104.0 ± 1.12 c
	SD2	11.1 ± 0.12 c	56.7 ± 0.55 bc	30.2 ± 0.76 ab	102.7 ± 2.26 c
	SD3	11.3 ± 0.68 c	53.5 ± 0.48 b	31.9 ± 0.66 b	110.9 ± 1.14 c
	SD4	12.5 ± 0.22 b	54.5 ± 0.36 b	27.1 ± 0.82 a	106.6 ± 2.23 bc
Variation source
Year		NS	NS	NS	NS
Treatment		**	**	**	**
Year × Treatment		NS	NS	NS	NS

Different letters represent significant differences among all treatments (p < 0.05). NS, not significant. **, p < 0.01.

). In 2020, the highest CP was obtained under the DD treatment, which increased by 35.8%, 26.5%, 22.9%, 19.6%, and 14.3% compared with the SS, SD1, SD2, SD3, and SD4 treatments, respectively (Table 3). In 2021, the CP in the DD, SD1, SD2, SD3, and SD4 treatments was significantly higher than that in the SS treatment by 52.0%, 14.4%, 20.8%, 25.6%, and 31.3%, respectively. In 2022, the CP of the DD treatment was 31.4% higher than the average value of that in the SS, SD1, SD2, SD3, and SD4 treatments (p < 0.05).

Neutral detergent fiber (NDF), acid detergent fiber (ADF), and relative feed quality (RFQ) had the same ANOVA results as CP (Table 3), with significant differences between treatments. In all three cropping years, forage sorghum blended with lablab bean exhibited smaller values of NDF and ADF and greater RFQ than monoculture forage sorghum. Overall, the blends significantly increased RFV in SD1, SD2, SD3, and SD4, with 3-year means of 8.2%, 5.7%, 12.3%, and 15.4%, respectively (p < 0.05), compared with monoculture forage sorghum.

3.6. Relationship between Yield and WUE, LAI, IPAR, RUE

Regression analysis indicates that in the mixed cropping system of forage sorghum and lablab bean, WUE is linearly correlated with dry matter yield (R² = 0.9023–0.9082, p < 0.01) (Figure 6A). Under the same conditions, the relationship between LAI, IPAR, RUE, and dry matter yield show similar results. Among them, the relationship between RUE and dry matter yield is the strongest (R² = 0.8713–0.9553, p < 0.01) (Figure 6D), indicating that improving canopy structure and RUE in the mixed cropping system are effective ways to increase dry matter yield.

4. Discussion

4.1. Competition Indices

The land equivalent ratio (LER) is used to evaluate the land use efficiency advantages in the mixed cropping system. Tao et al. [8] reported that mixed cropping has an average LER of 1.18–1.23 compared with monoculture. Similarly, we found that the 3-year average LER of the mixed cropping system ranged from 1.32 to 1.38, relative to the sole system, indicating that 32–38% more farmland would be required by sole forage sorghum and sole lablab bean to equate the yields of forage sorghum and lablab bean in mixed cropping. In addition, the LER in the mixed cropping system was the highest in the SD3 treatment, which was 13.2% and 6.9% higher than those in the SD1 and SD4 treatments, respectively (Figure 3A–C). These findings agree with those of Raza et al. [26] and Chen et al. [27] who reported a mixed stand advantage with soybean and maize mixtures, which was different at different growth stages. In addition, this was mainly attributed to the appropriate canopy structure of the SD3 system and high radiation RUE (Figure 5G–I), which improves forage productivity (Figure 6D), ultimately enabling the SD3 treatment to have maximum land use efficiency.

The aggressivity (A) and competition ratio (CR) are based on dry matter yields and more accurately reflects the competition between and within component crops [28]. Ghosh et al. [29] reported that sorghum is the dominant crop in sorghum/soybean mixed cropping systems. The findings of this study were similar, as shown by the CR_S and CR_D competitive indicators, suggesting that forage sorghum was the dominant species. Furthermore, this study found that A values of all mixed cropping treatments in forage sorghum were positive in the 3 years (0.23–0.90, Figure 3A–C), while the A of all mixed cropping treatments in lablab bean were negative except for that of the SD1 treatment in 2020 (0.13). This indicates that forage sorghum has a mixed cropping advantage, while lablab bean has a mixed cropping disadvantage in the forage sorghum/lablab bean mixed cropping system.

4.2. Soil Water Content and Water Use Efficiency

Soil moisture is the main driver in a semiarid cropping system [30]. Herein, we observed that soil moisture in the 0–40 cm soil layer under mixed cropping was 14.3% higher than that under monoculture. Conversely, the trend was reversed below 40–200 cm, which could be attributed to the following reasons: (1) Integrating lablab bean into mixed cropping increases the amount of vegetation per unit area, thereby reducing surface exposure. This results in increased rainfall collection, which increases soil moisture content in the 0–40 cm layer, as observed in the maize/pea mixed cropping systems [31]. (2) There is a spatial complementarity in the root distribution between forage sorghum and lablab bean, with lablab bean roots mainly distributed in the soil surface layer (0–40 cm), while forage sorghum roots can reach depths of <60 cm. This results in lower soil moisture content compared with that in the soil where in forage sorghum is grown alone, which is consistent with the findings of Gong et al. [15] for millet intercropped with mung beans. Enhancing the efficiency of water usage plays a vital role in improving the sustainable advancement of agricultural production [30]. Our study showed that water use efficiency (WUE) was significantly higher by 22.7–34.3% (p < 0.05) in the mixed cropping system compared with that in the forage sorghum monoculture system (Table 1). In addition, WUE_CPY and WUE_I were 25.8–48.2% and 15.2–27.2% higher, respectively, than the monoculture system. This indicated that mixed cropping increased the forage yield by improving water utilization. Meanwhile, we have also modeled the relationship between dry matter yield and WUE for these 3 years and showed a significant positive correlation between the two (Figure 6A). This study showed that the SD3 cropping pattern was suitable for forage sorghum and lablab bean, with the highest WUE for symbiotic growth. The mixed cropping system improved the WUE and water-uptake capacity of the plants, which is favorable in arid ecosystems, suggesting that forage sorghum/lablab bean mixed cropping is favorable in the arid regions of northwest China.

4.3. Leaf Area Index and Radiation Use Efficiency

The system light environment can be changed by cropping patterns, such as mixed cropping [27]. Mixed cropping systems often result in a higher leaf area index (LAI) and can intercept more photosynthetically active radiation (PAR). Research has shown that a mixed cropping of maize with legumes can result in a 28% increase in intercepted PAR compared with maize sole cropping [3]. In this study, intercepted PAR was higher in the mixed cropping system than in the monoculture system, and the SD3 treatment was the highest. This was mainly due to the LAI of the mixed cropping system, which was higher than that of the monoculture system. The canopy closure of the mixed cropping system was earlier than that of the monoculture system (Figure 5A–C), and the intercepted PAR was higher (Figure 5D–F). Meanwhile, we found that the LAI of the SD1, SD2, SD3, and SD4 mixed cropping systems increased by 3.61, 6.24, 15.24, and 13.63%, respectively, compared with the LAI of the sole forage sorghum. This result further confirmed the positive correlation between IPAR and LAI, and that LAI is beneficial in changing the distribution and use of PAR within the plant canopy [32]. The RUE of the mixed cropping system was 32.7% higher than that of the monoculture system, which was related to the increased forage productivity and higher IPAR of the mixed cropping system compared with the monoculture system [29], where the maximum forage yield and IPAR of the SD3 treatment also led to the maximum RUE of the system, which was significantly higher than that of the SS monoculture by 17.95%. Correspondingly, the mean values of radiation use efficiency (RUE) for SD1, SD2, SD3, and SD4 were 1.12, 1.18, 1.22, and 1.12 times that of sole forage sorghum, respectively. Higher RUE efficiently used the intercepted light and thus produced more forage yield [33], which is consistent with the results of our study where there was a significant positive correlation between IPAR, RUE, and forage yield (Figure 5B–D). Therefore, a well-structured canopy optimizes leaf distribution, which affects LAI, and in turn IPAR, effectively accumulating more forage productivity, which is reflected in RUE.

4.4. Forage Yield

Many studies have reported that the mixed cropping of legumes and cereals is an effective way to improve the forage yield. For example, Zhang et al. [33] reported that mixing maize, alfalfa, and rye increased dry matter and crude protein yield (CPY) by 34.81% and 16.74%, respectively, compared with monoculture. Similar results were found in our experiment: The total dry matter and CPY of the mixed cropping system increased by 34.5–43.8% and 32.7–46.8% compared with the average values of sole forage sorghum and lablab bean, respectively (Table 2). This result was due to the significant positive correlation between hay yield and WUE, LAI, IPAR, and RUE (Figure 6A–D), which were significantly higher in the mixed cropping system than in the monoculture system [11,34,35]. In addition, the incorporation of lablab bean into the mixed cropping system was an important factor that ultimately increased CPY. However, Armstrong et al. [36] reported that the dry matter yield of velvet bean–maize and scarlet runner–maize mixtures was reduced by 11.5% and 5.8%, respectively, compared with maize monoculture. This phenomenon could be due to the planting density of maize and the sowing period of legumes in the experiment. Herein, mixing lablab bean with forage sorghum did not reduce yield, with the SD3 pattern achieving the highest forage yield. Therefore, lablab bean mixed with forage sorghum is an efficient production practice and SD3 treatment is the best cropping pattern. In addition, rainfall distribution in the arid regions shows a large intraseasonal and interannual variation [37]. The results of this study showed that forage yield in 2020 was higher than those in 2021 and 2022, which could be attributed to higher rainfall in 2020 than in 2021 and 2022.

4.5. Forage Quality

Crude protein (CP) is a crucial index for evaluating forage quality, and CP concentration in mixed cropping systems depends on legume density [38]. Herein, CP content increased with increasing lablab bean density in all the mixed cropping systems (Table 3). The highest CP content was recorded in monoculture lablab bean (14.31%) followed by the SD4 treatment (12.38%). On the contrary, the monoculture of forage sorghum had the lowest CP (9.11%). These results agree with those reported by Angadi et al. [39] in studies on forage sorghum + lima bean and sorghum + pole bean. The combination of forage sorghum and lablab bean increased the CP concentration in the mixed cropping system, but the level depended on the density of lablab bean in the system. Relative feed quality (RFQ) is used to determine forage intake and energy value, and RFQ was derived from neutral detergent fiber (NDF) and acid detergent fiber (ADF). Forages with RFQ values of >151 are considered to be of high quality [40]. Herein, RFQ values were lower than 151 for all the treatments, and the highest value of 128.3 was obtained under the lablab bean monoculture, which was consistent with the variation in CP content, mainly due to the fact that the lablab bean monoculture had the lowest NDF and ADF contents (Table 3). The nutritional content of forage was significantly higher in the SD4 treatment, with the CP content increased by 35.9% compared with that in the forage sorghum monoculture, but the difference was not significant with the SD3 treatment. This finding is important for farmers to develop legume-based mixed cropping systems with low inputs and high nutrients.

5. Conclusions

The results of this study support the conclusion that mixed cropping has the advantage of increasing forage yield by mitigating soil water depletion and optimizing canopy structure in the arid region of China. Specifically, the SD3 treatment was an efficient management practice that increased system dry matter yield by 32.6–67.5%, crude protein yield by 12.5–15.1%, WUE by 9.2–67.4%, and RUE by 39.6–38.2% compared to other treatments. Meanwhile, forage sorghum mixed with lablab bean improved forage quality. The LER was greater than that when forage sorghum was mixed with lablab bean, with the SD3 treatment having a better performance. In addition, forage sorghum was the dominant crop and had higher aggressiveness (0.65) and competitive ratios (3.44) than lablab bean. Therefore, the SD3 mixed cropping system is proposed to be used to alleviate forage shortage and improve forage quality in the arid region of China.