Appropriate Water-Nitrogen Regulation Mode to Improve Productivity of Mixed-Sowing Grassland of Bromus inermis and Alfalfa

Abstract

Scientific selection of appropriate herbage planting management mode is an important guarantee to promote artificial grassland development and grassland productivity. In this study, three-year-old alfalfa (Medicago sativa L.) and bromus inermis were applied to analyze the effects of planting patterns (bromus inermis and alfalfa mixed-sowing D1, bromus inermis mono-sowing D2), nitrogen application (pure nitrogen) level (N1: 60 kg·ha⁻¹, N2: 120 kg·ha⁻¹), and water regulation (upper and lower limits of irrigation are calculated as a percentage of field capacity θ_f, W1: slight water deficit 65~85% θ_f, W2: moderate water deficit 55~85% θ_f, W3: serious water deficit 45~85% θ_f) on herbage growth and water-nitrogen use efficiency. This research applied the principal component analysis, the TOPSIS model, and the combination evaluation to evaluate each treatment. Results demonstrated that (1) the plant height, leaf area index, and yield of mixed-sowing herbage were 81.63%, 119.52%, and 111.51%, higher than the mono-sowing herbage. Increasing the amount of irrigation and nitrogen application could enhance herbage yield. The herbage yield with the W1N2 treatment was the highest. In this treatment, the mixed-sowing herbage yield was 26,050.73 kg·ha⁻¹, and the mono-sowing herbage yield was 12,186.10 kg·ha⁻¹. (2) The crude protein content of mixed-sowing herbage increased by 41.44%, higher than mono-sowing herbage, and the relative feeding value decreased by 16.34%. Increasing irrigation and nitrogen application could improve the quality of herbage. Meanwhile, the quality of herbage treated with W1N2 was the best. (3) The water use efficiency (WUE), irrigation water use efficiency (IWUE), partial factor productivity of nitrogen (PFP_N), and crude protein water use efficiency (CP_WUE) of mixed-sowing herbage were significantly higher than mono-sowing herbage. The PFP_N and the CP_WUE of herbage improved with increasing irrigation amount. Meanwhile, the WUE, the IWUE, and the CP_WUE of herbage also improved with increasing nitrogen application amount. The results showed that mixed-sowing of alfalfa and bromus inermis with slight water deficit (upper and lower limit of irrigation was 65~85% θ_f) and nitrogen application (120 kg·ha⁻¹) could have the best comprehensive production effect. At the same time, it was a planting and management mode of high yield, high quality, and high efficiency of artificial herbage in the oasis-desert interlacing area of Hexi, Gansu Province, China, and areas with similar climates.

1. Introduction

Herbage is the material basis of animal husbandry development [1]. In recent years, degradation, desertification, and salinization of natural grassland have been prominent due to overgrazing, climate change, and other factors. The contradiction between the supply and demand of herbage and livestock was increasingly prominent, seriously restricting the sustainable development of modern animal husbandry [2]. Planting artificial grassland could relieve the pressure on natural grassland, make natural grassland recuperate, and coordinate the imbalance of grassland utilization in time and space. According to statistics, China’s artificial herbage was still mainly dependent on imports. In 2020, China imported 1.694 million tons of hay, accounting for about 15% of the total demand [3,4]. Alfalfa (Medicago sativa L.) and bromus inermis are perennial herbages, the dominant herbage species in arid and semi-arid areas. Alfalfa has strong resistance, wide distribution, and high economic value. Bromus inermis has cold solid and drought resistance and a long utilization period [5,6]. Mixed-sowing of alfalfa and bromus inermis could significantly increase herbage yield and compensate for the deficiency of nutritional components in monoculture. Furthermore, it could prevent livestock from eating single-legume herbages to develop bloating disease or poisoning and low protein content of mono-sowing herbages [7]. Therefore, the mixed-sowing of alfalfa and bromus inermis is a dominant planting pattern in areas with scarce water or poor soil, but the limited water and fertilizer resources have also become key problems for the long-term stability of its productivity.

In recent years, scholars have carried out a series of research on the efficient utilization of water and fertilizer resources in alfalfa or bromus inermis [8]. Results showed that irrigation and fertilization could significantly improve the yield and quality of herbage. The effect showed a trend of first increasing and then decreasing with the increase of irrigation or fertilizer amount [9], and there was a certain threshold. The threshold value of water and fertilizer varies with regional climatic characteristics, natural geographical conditions, soil types, field management, and irrigation and fertilization methods. In terms of irrigation management of alfalfa or bromus inermis, the lower limit of irrigation for high yield, high quality, and water saving of alfalfa in the northwest arid region of China was 60%, 60% and 70% field water capacity (θ_f) in early branching stage, branching stage and bud stage, respectively [10]. In California, USA [11], the eastern state of New Mexico, USA [12], France [13], and cold-arid desert areas, China [14], the irrigation amounts of alfalfa with high yield were 67.0~87.5% of conventional irrigation, 400~500 mm, 75% potential evapotranspiration, and 6450 m³·ha⁻¹, respectively. In terms of fertilization management of alfalfa or bromus inermis, the optimal fertilization pattern for high yield and quality of alfalfa in France [15], Southwest Missouri, USA [16], Utah, USA [17], Sweden [18], Beijing, China [19], and northern China [20] were 90 kg·ha⁻¹ (nitrogen), 75 kg·ha⁻¹ (phosphorus) + 140 kg·ha⁻¹ (potassium), 101~142 kg·ha⁻¹ (nitrogen), 200~400 kg·ha⁻¹ (nitrogen), 106 mg·ha⁻¹ (nitrogen) + 53.86 kg·ha⁻¹ (phosphorus) + 39.82 kg·ha⁻¹ (potassium), 106 mg·kg⁻¹ (phosphorus), and 300 kg·ha⁻¹ (organic and inorganic compound fertilizer), respectively. In terms of irrigation and fertilizer management of alfalfa or bromus inermis, the optimal irrigation and fertilizer amounts were 896 mm + 30 kg·ha⁻¹ (phosphorus), 620 mm + 120 kg·ha⁻¹ (nitrogen), and 1560 m³·ha⁻¹ + 40~80 kg·ha⁻¹ (nitrogen), respectively, in Mediterranean region [21], Ningxia [22], and Hexi Corridor of Gansu in China [9]. The irrigation and fertilizer management to obtain the highest yield of bromus inermis was 1000 m³·ha⁻¹ + 450 kg·ha⁻¹ (nitrogen) + 200 kg·ha⁻¹ (phosphorus) + 75 kg·ha⁻¹ (potash), and 552.1 mm + 152.3 kg·ha⁻¹, respectively, in Horqin Sandy Land and Hexi Corridor of Gansu in China [23,24]. It can be seen that the existing studies mostly focus on the irrigation and fertilization pattern with high yield and quality of alfalfa or bromus inermis, and most of them are alfalfa. However, there are few studies on the mixed-sowing of alfalfa and bromus inermis. In particular, there are few types of research on promoting high yield, quality, and efficiency of mixed-sowing of alfalfa and bromus inermis through the synergistic effect of water, fertilizer, and herbage allocation.

The current evaluation of the production effect on artificial grassland is mainly carried out from the evaluation objective, index system, evaluation method, and evaluation content. Wherein the evaluation objective concludes high yield, high quality, and suitability [23]. The index system contains yield, quality, community stability, and interspecific compatibility [25]. The evaluation method involves principal component analysis, factor analysis, entropy value method, fuzzy evaluation method, grey correlation analysis, TOPSIS model, and hierarchical analysis [26,27]. The evaluation content covers mixed-sowing proportion, mixed-sowing herbage species, planting pattern, cutting period, stubble height, and fertilization management [28,29]. Compared with the evaluation results obtained through a single method, a variety of methods combined for evaluation can synthesize multiple evaluation results to reduce the difference and make the evaluation results reasonable.

Researchers can obtain a scientific and reasonable water-nitrogen supply strategy for the mixed-sowing of alfalfa and bromus inermis through the comprehensive evaluation of different water-nitrogen regulation patterns. In the oasis-desert interlacing area of Hexi, Gansu Province, China, the main artificial grassland planting method is bromus inermis mono-sowing. Hence, this paper systematically analyzed the effects of water and nitrogen regulation on herbage growth, yield, quality, and water-nitrogen use efficiency, under bromus inermis mono-sowing and the mixed-sowing of bromus inermis and alfalfa, aiming to diversify the single planting pattern and improve the local grassland productivity. In addition, principal component analysis, TOPSIS comprehensive evaluation, and combined evaluation methods were applied to comprehensively evaluate the production effect of herbage under different planting managements. Therefore, the objectives of this study were: (1) quantify the responses of herbage growth, yield, quality, and water-nitrogen use efficiency to planting patterns and water-nitrogen regulations; (2) obtain a management mode of artificial grassland planting with high productivity and resource-use efficiency in the oasis-desert interlacing area of northwest China.

2. Materials and Methods

2.1. Description of the Experimental Site

The experiment was conducted in Minghua Township Test Station (38°40′ N, 98°4′ E, altitude 1368 m), Sunan Yugu Autonomous County, Zhangye, Gansu Province, China, from April to October 2020. The average annual precipitation, evaporation, temperature, frost-free period, and sunshine hours of the test site are 90 mm, 1731 mm, 7.3 °C, 131 d, and 3034 h. The soil properties are shown in

Table 1. The properties of the soil.

Soil Properties	Index Value
Soil Texture	Sandy Loam
Bulk Density (g·cm−3)	1.44
Field Capacity (% Volumetric Moisture)	33.0
pH	7.4
Total Nitrogen (g·kg−1)	0.21
Available Phosphorus (mg·kg−1)	3.16
Available Potassium (g·kg−1)	0.17

. The meteorological data (Figure 1) was measured by a small intelligent agrometeorological station (Tianqi WSTQ). The precipitation during the growth period of herbage was 51.4 mm, and the average temperature was 20.6 °C.

2.2. Experimental Design and Field Management

The variety of the tested alfalfa was Qingshui alfalfa, and the variety of bromus inermis was Carlton bromus inermis. Both were provided by the Pratacultural College of Gansu Agricultural University. The experiment was conducted in a completely randomized block design, with 3 factors [30,31], including planting mode, water regulation, and nitrogen-application level (

Table 2. Experimental design.

Treatments	Planting Patterns	Low Irrigation Limit of Squaring and Initial Flowering Stage/%θf	Nitrogen Application Rate/(kg·ha−1)
D1W1N1	D1	65~85 (W1)	60 (N1)
D1W1N2			120N2)
D1W2N1		55~85 (W2)	60 (N1)
D1W2N2			120 (N2)
D1W3N1		45~85 (W3)	60 (N1)
D1W3N2			120 (N2)
D2W1N1	D2	65~85 (W1)	60 (N1)
D2W1N2			120 (N2)
D2W2N1		55~85 (W2)	60 (N1)
D2W2N2			120 (N2)
D2W3N1		45~85 (W3)	60 (N1)
D2W3N2			120 (N2)

). The planting mode was the mixed-sowing of alfalfa and bromus inermis (D1, sowing ratio was 1:1, sowing amount was 15 kg·ha⁻¹), and the mono-sowing of bromus inermis (D2, 30 kg·ha⁻¹). Water regulation was carried out at the budding stage and early flowering stage of alfalfa (alfalfa and bromus inermis had different growth periods, subject to alfalfa), indicated as the percentage θ_f of the controlled soil volumetric water content (the planned depth of wet layer was 80 cm) to the field moisture capacity. The lower limit of irrigation was 65% θ_f (W1, slight water deficit), 55% θ_f (W2, moderate water deficit), and 45% θ_f (W3, severe water deficit). Meanwhile, the upper limit of irrigation was 85% θ_f. The rest of the growth period was sufficient irrigation (75~85% θ_f), The level (pure nitrogen) of nitrogen application (urea, N mass fraction was 46.4%) was low nitrogen, 60 kg·ha⁻¹ (N1), and high nitrogen, 120 kg·ha⁻¹ (N2). The first cut was applied at the branching stage, and the second and third cuts were applied after the previous cutting. The application ratio of the third cut was 5:3:2. There were 12 treatments, 3 replicates, and 36 plots. Moreover, the test plot area was 25 m² with a 1m wide protective row between the plots.

Sprinkler irrigation was adopted (the irrigation amount was controlled by the water meter on the branch pipe of each community). The sprinkler head (provided by DaYu Water-saving Co., Ltd., Jiuquan, Gansu, China.) was butterfly-shaped with a spraying radius of 2~3 m and a sprinkler flow of 0.2 m³·h⁻¹, arranged in the center of the community. Alfalfa and bromus inermis were conducted as drill sowing in May 2018 (sowing depth: 2 cm. row space: 31 cm. 17 rows of herbage were planted in each plot). The cutting time of herbage should be based on the initial flowering period of alfalfa in mixed-sowing. The three cutting times were 11 June, 2 August, and 23 September 2020, which were at the booting to initial flowering, booting, and jointing stages of bromus inermis. The field management measures such as weed control and pest control should be consistent with the local artificial grassland.

2.3. Indicators and Methods for Measurement

2.3.1. Soil Moisture Content (%)

A 1.5 m long polyester probe pipe was randomly arranged 2 m away from the sprinkler head. The soil volume moisture content in the 0–120 cm soil layer (at an interval of 20 cm) was measured with a portable soil profile moisture rapid meter TDR (PICO-BT, IMKO GMBH, Ettlingen, Germany) every 7 days. Additional measurements were conducted before and after irrigation and after rainfall. In addition, the drying method was applied for calibration every 20 days.

2.3.2. Water Consumption (mm)

$$E{T}_a=I+P+S-\Delta W-D$$

(1)

where ET_a is water consumption (mm), I is total irrigation (mm), P is effective precipitation (mm), S is groundwater recharge (ignored, mm), ∆W is soil water storage change (mm), and D is deep leakage (ignored).

2.3.3. Plant Height (PH, cm)

The plant height of herbage was measured at the first flowering stage (10 June, 31 July, and 22 September) of alfalfa. 10 alfalfa and bromus inermis with regular growth were randomly selected from each plot of the mixed-sowing grassland. In the meantime, 10 bromus inermis with regular growth were randomly selected from the mono-sowing grassland for marking. The plant height was measured with tape, and the average value of three cuts was taken.

2.3.4. Leaf Area Index (LAI)

When the solar zenith angle was lower than 60° at noon during the first flowering period of alfalfa, the LAI of herbage was measured with the plant canopy analyzer (AccuPAR-LP80, METER Co., Washington, DC, USA). Furthermore, the average value of the three cuts was taken.

2.3.5. Yield (Y, kg·ha⁻¹)

At the first flowering stage of alfalfa, 1 m² of the sample was randomly selected in each plot and mowed at a distance of 5 cm from the ground. The sample was put in the oven to green at 105 °C for 0.5 h and dry at 75 °C for 48 h to constant weight. After cooling, the dry weight (the total dry weight of alfalfa and bromus inermis for mixed-sowing) was weighed, and the hay yield was calculated. The total yield was the sum of the three cuts.

2.3.6. Quality

Each cut of dried herbage sample was crushed and passed through the 0.4 mm sieve. After that, 0.50 g of herbage sample was weighed to determine the content of CP, acid detergent fiber (ADF), and neutral detergent fiber (NDF). Finally, the average of the three cuts was taken.

(1)

CP content (%)

According to the national standard GB/T 6432-94, the H₂SO₄ digestion was applied. The Kjeldahl nitrogen determination instrument was applied to determine. The yield of crude protein (Y_CP, kg·ha⁻¹) was calculated by:

$$Y_{CP}=Y\times CP$$

(2)

(2)

Relative feeding value (RFV)

RFV was calculated from the content of ADF (%) and NDF (%) of herbage. ADF and NDF were measured by Goering and Van Soest methods with a semi-automatic fiber analyzer.

$$RFV=\left(DDM\times DMI\right)/1.29$$

(3)

$$DDM=88.9-0.799\times ADF$$

(4)

$$DMI=120/NDF$$

(5)

where DDM is digestible dry matter, and DMI is dry matter intake.

2.3.7. Water-Nitrogen Use Efficiency

(1)

WUE (kg·m⁻³)

$$WUE=Y/E{T}_a$$

(6)

(2)

Irrigation water use efficiency (IWUE, kg·m⁻³)

$$IWUE=Y/I$$

(7)

(3)

PFP_N (kg·kg⁻¹)

$$PFPN=Y/F$$

(8)

where F is the nitrogen application rate, kg·ha⁻¹.

(4)

Water use efficiency of crude protein (CP_WUE, kg·m⁻³)

$$C{P}_{WUE}=Y_{CP}/E{T}_a$$

(9)

2.4. Evaluation Methods

2.4.1. Principal Component Analysis (PCA) [32,33]

(1)

Data Standardization

$$y_{ij}^{\ast }=\frac{y_i-min\left(y_i,\cdots ,y_n\right)}{max\left(y_i,\cdots ,y_n\right)-min\left(y_i,\cdots ,y_n\right)}$$

(10)

where $y_{ij}^{\ast }$ is the normalized value, y_i is the raw value, i =1, 2, 3, ……, n, n = 12.

(2)

Calculating the correlation coefficient matrix;

(3)

Calculating factor loads for principal component analysis, eigenvalue, and variance contribution rate;

(4)

Calculating the composite scores and sorting them by composite scores.

2.4.2. TOPSIS

(1)

Calculating the matrix M_ij of each evaluation index under different water and nitrogen regulations [34];

$$M_{ij}=\frac{X_{ij}}{\sqrt{{\displaystyle \sum {\left(X_{ij}\right)}^2}}}$$

(11)

where X_ij is the value of the selected indicator; i is different water and nitrogen treatments under the same index, i = 1, 2, 3… 12; j is different evaluation indexes under the same water and nitrogen treatment, j = 1, 2, 3… 9.

(2)

Calculating the best set M_i⁺ and the worst set M_i⁻, calculating the distance between different indicators and the optimal and worst values according to M_ij, M_i⁺, and M_i⁻;

$$D_i^{+}=\sqrt{{\displaystyle \sum {\left(M_{ij}-M_i^{+}\right)}^2}}$$

(12)

$$D_i^{-}=\sqrt{{\displaystyle \sum {\left(M_{ij}-M_i^{-}\right)}^2}}$$

(13)

(3)

Calculating the relative proximity C_i and performing a comprehensive sort according to the C_i value (the closer the C_i value is to 1, the higher the comprehensive ranking).

$$C_{\mathrm{i}}=\frac{D_{\mathrm{i}}^{-}}{D_{\mathrm{i}}^{+}+D_{\mathrm{i}}^{+}}$$

(14)

2.4.3. The Combined Evaluation

The combined evaluation was to reevaluate the evaluation results obtained by various evaluation methods [35,36]. Common combination evaluation methods contain the fuzzy Borde method, average value method, Copeland method, etc. In this study, the fuzzy Borde method was used for combination evaluation [37].

(1)

The Spearman rank correlation coefficient was used for the consistency test to obtain the R-value;

$$R=1-\frac{6{\displaystyle \sum D_i^2}}{m\left(m^2-1\right)}$$

(15)

where the value range of R is [0, 1], the larger the R, the better the correlation, D_i is the deviation degree of evaluation results, and m is the number of treatments (m = 12 in this study).

(2)

The results obtained by principal component analysis and TOPSIS comprehensive evaluation were calculated for membership degree (U_ij);

$$U_{ij}=\frac{A_{ij}-Mi{n}_i\left(A_{ij}\right)}{Ma{x}_i\left(A_{ij}\right)-Mi{n}_i\left(A_{ij}\right)}\times 0.9+0.1$$

(16)

where A_ij is the score of item i in method j.

(3)

The fuzzy frequencies, P_hi and W_hi, were calculated;

$$P_{hi}={\displaystyle \sum _{j=1}^2{V}_{hi}{U}_{ij}}$$

(17)

$$W_{hi}=\frac{P_{hi}}{{\displaystyle \sum P_{hi}}}$$

(18)

where if item i is in position h, then V_hi = 1; otherwise, V_hi = 1.

(4)

The ranking was converted into a score Q_hi, and the score Bi was calculated using the fuzzy Borda method and ranked according to the score value.

$$Q_{hi}=0.5\times \left(12-h\right)\left(12-h+1\right)$$

(19)

$$B_{hi}={{\displaystyle \sum W_{hi}Q}}_{hi}$$

(20)

2.5. Data Analysis

Microsoft Excel 2019 (Microsoft Crop., Raymond, WA, USA) was applied to calculate the TOPSIS model and analysis combination evaluation. IBM SPSS Statistics 24 (IBM Inc., New York, NY, USA) was used for the statistical analysis of the data and PCA. Meanwhile, General linear model ANOVA was used to test the effects of irrigation, nitrogen, and their interactions on plant height, stem thickness, leaf area index, yield, quality, and water and nitrogen use efficiency in herbage (p < 0.05). Origin 2019 (Originlab Corp., Northampton, MA, USA) was applied to draw figures.

3. Results

3.1. Herbage Growth

3.1.1. Plant Height, Leaf Area Index, and Yield

The effects of water-nitrogen regulation on plant height, leaf area index, and herbage yield are shown in Figure 2. In this figure, the plant height, leaf area index, and yield of mixed-sowing herbage were significantly higher than mono-sowing herbage, with an average increase of 81.63%, 119.52%, and 111.51%. The plant height, leaf area index, and herbage yield increased with the increasing irrigation and nitrogen. According to these three indexes, the herbage with the W1N2 treatment had the best growth. At the same irrigation level, these three indexes of the W1N2 herbage were 10.87%, 9.32%, and 11.42%, higher than the W1N1 group. Under the same nitrogen application, the plant height, leaf area index, and yield with the W1N2 treatment increased by 4.74%, 17.95%, and 9.27% compared with the W2N2 treatment. Meanwhile, the plant height, leaf area index, and yield of the herbage with the W1N2 treatment were 17.43%, 40.53%, and 21.81%, higher than the herbage with the W3N2 treatment. Therefore, the production effect of mixed-sowing herbage was better than mono-sowing herbage, indicating that increasing irrigation and nitrogen could improve the growth of herbage, especially the mixed-sowing herbage.

3.1.2. Quality

CP and RFV are important indicators to measure the nutritional performance of herbage. The impact of water-nitrogen regulation on CP content and RFV of herbage is shown in Figure 3. According to the figure, the CP content of the mixed-sowing herbage significantly increased by 41.44% compared with the mono-sowing herbage. Meanwhile, the RFV of the mixed-sowing herbage was reduced by 16.34% compared with the mono-sowing group. CP content and RFV increased with the increasing irrigation and nitrogen, and both CP content and RFV were better in the group with the W1N2 treatment. At the same irrigation level, the CP content and RFV of the W1N2 group were 15.58% and 12.28%, higher than the W1N1 group. Under the same nitrogen application, the CP content and RFV of the group with the W1N2 treatment increased by 13.50% and 18.20% compared with the W2N2 group. Compared with the W3N2 group, the CP content and RFV of W1N2 increased by 12.88% and 35.90%. Therefore, the mixed-sowing herbage could increase CP content but reduce RFV, showing that increasing irrigation and nitrogen application could improve herbage quality.

3.1.3. Water-Nitrogen Use Efficiency

The impact of water-nitrogen regulation on the water-nitrogen use efficiency of the herbage is shown in

Table 3. Effects of water and nitrogen regulation on water and nitrogen utilization efficiency of herbage.

Planting Patterns	Treatment	Water Use Efficiency (WUE, kg·m−3)	Irrigation Water Use Efficiency (IWUE, kg·m−3)	Nitrogen Partial Factor Productivity (PFPN, kg·kg−1)	Water Use Efficiency of Crude Protein, (CPWUE, kg·m−3)
Alfalfa and bromus inermis mixed-sowing	D1W1N1	4.29ab	5.14b	388.03a	0.81ab
	D1W1N2	4.05c	4.82c	217.09d	0.85a
	D1W2N1	4.38ab	5.66a	369.74b	0.76ab
	D1W2N2	4.17bc	5.26ab	198.11e	0.81ab
	D1W3N1	4.48a	5.16b	305.41c	0.70c
	D1W3N2	4.41ab	5.37ab	176.69f	0.73c
	W	*	**	**	**
	N	*	ns	**	*
	W × N	ns	*	**	ns
Bromus inermis mono-sowing	D2W1N1	2.18b	2.74ab	183.94a	0.30bc
	D2W1N2	2.21ab	2.86ab	101.55d	0.36a
	D2W2N1	2.23ab	2.69b	166.69b	0.26de
	D2W2N2	2.34a	2.84ab	93.49e	0.33ab
	D2W3N1	2.33ab	2.75ab	146.54c	0.24e
	D2W3N2	2.38a	2.89a	84.90f	0.28cd
	W	ns	ns	**	**
	N	*	*	**	**
	W × N	ns	ns	**	ns

Note: Different lowercase letters indicate significant difference among treatments (p < 0.05). ** indicates an extremely significant difference (p < 0.01); * indicates a significant difference (p < 0.05); ns indicates no significant difference (p > 0.05).

. In the table, WUE, IWUE, PFP_N, and CP_WUE of mixed-sowing herbage are significantly greater than the mono-sowing herbage. Compared with the mono-sowing herbage, these indexes increase by 88.59%, 87.30%, 112.98%, and 163.28%. According to the comprehensive analysis of the water-nitrogen use efficiency of herbage, WUE and IWUE decreased with increasing irrigation and increased with increasing nitrogen. The PFP_N of herbage decreased with increasing nitrogen. However, increasing irrigation increased the PFP_N, with maximum values of 388.03 kg·kg⁻¹ (D1) and 183.94 kg·kg⁻¹ (D2). The increasing irrigation and nitrogen increased the CP_WUE, with maximum values of 0.85 kg·m⁻³ (D1) and 0.36 kg·m⁻³ (D2). In summary, the treatments of D1W3N1, D1W2N1, D1W1N1, and D1W1N2 could significantly improve the herbage’s WUE, IWUE, PFP_N, and CP_WUE, respectively.

3.2. Comprehensive Evaluation

3.2.1. Principal Component Analysis (PCA)

(1)

Correlation coefficient matrix

According to Figure 4, most of the correlation coefficients are above 0.600, indicating that the selected indicators have a strong correlation. So, it is reasonable to conduct a comprehensive evaluation of the selected variables with the principal component analysis (PCA) approach.

(2)

Factor load, eigenvalue, and variance contribution rate of principal component analysis

The factor load, eigenvalue, and variance contribution of the PCA are shown in

Table 4. Principal component factor load and variance contribution rate.

Component	Load Factor
	Principal Component 1	Principal Component 2
PH	0.978	0.163
LAI	0.976	0.205
Y	0.982	0.141
CP	0.886	0.462
RFV	−0.428	0.877
WUE	0.966	−0.220
IWUE	0.972	−0.174
PFPN	0.762	−0.265
CPWUE	0.996	0.052
Eigenvalue	7.292	1.223
Variance contribution rate /%	81.026	13.593
Accumulating contribution rate /%	81.026	94.618

. After the dimension reduction, two principal components with eigenvalue > 1 were obtained. Their cumulative contribution was 94.618%, indicating that these two principal components contained the main information of nine indicators. Principal component 1 contained 81.026% of the total variation information, reflecting the influence of PH, LAI, Y, WUE, IWUE, and CP_WUE. Principal component 2 interpreted 13.593% of the original information, showing the influence of RFV.

(3)

Comprehensive score.

According to the comprehensive score and comprehensive ranking of principal components (

Table 5. Comprehensive score and ranking of forage under different water and nitrogen regulations.

Treatment	Score	Ranking	Treatment	Score	Ranking
D1W1N1	0.3790	2	D2W1N1	−0.2102	9
D1W1N2	0.5381	1	D2W1N2	0.0006	7
D1W2N1	0.2503	4	D2W2N1	−0.3707	10
D1W2N2	0.3580	3	D2W2N2	−0.2097	8
D1W3N1	0.0326	6	D2W3N1	−0.5206	12
D1W3N2	0.1404	5	D2W3N2	−0.3879	11

), the comprehensive score of D1 is greater than D2 under different planting modes. On the other hand, the comprehensive score of W1 was higher than W2 and W3 under different water control. Under different nitrogen application levels, the comprehensive score of N2 was higher than N1. In the comprehensive score of all treatments, D1W1N2 was the highest, and D2W3N1 was the lowest.

3.2.2. TOPSIS Comprehensive Evaluation

The matrix of M_ij was obtained by dimensionless calculation of the nine selected evaluation indicators according to Equation (11) (

Table 6. Calculation matrix M_ij for each evaluation indicator under different water and nitrogen regulations.

Treatment	PH	LAI	Y	CP	RFV	WUE	IWUE	PFPN	CPWUE
D1W1N1	0.344	0.405	0.382	0.343	0.287	0.360	0.353	0.498	0.397
D1W1N2	0.376	0.443	0.428	0.386	0.307	0.340	0.331	0.279	0.416
D1W2N1	0.341	0.357	0.353	0.321	0.249	0.367	0.389	0.474	0.372
D1W2N2	0.360	0.385	0.390	0.351	0.262	0.350	0.361	0.254	0.397
D1W3N1	0.300	0.308	0.301	0.282	0.220	0.376	0.355	0.392	0.343
D1W3N2	0.317	0.331	0.348	0.304	0.233	0.370	0.369	0.227	0.358
D2W1N1	0.222	0.186	0.181	0.248	0.334	0.183	0.188	0.236	0.147
D2W1N2	0.246	0.212	0.200	0.296	0.389	0.185	0.197	0.130	0.176
D2W2N1	0.223	0.151	0.164	0.215	0.283	0.187	0.185	0.214	0.127
D2W2N2	0.234	0.166	0.184	0.250	0.327	0.196	0.195	0.120	0.162
D2W3N1	0.200	0.111	0.144	0.186	0.250	0.195	0.189	0.188	0.118
D2W3N2	0.221	0.132	0.167	0.210	0.279	0.200	0.199	0.109	0.137

).

Table 7. Approximation (C_i) and comprehensive ranking under different water and nitrogen regulations.

Treatment	Di+	Di−	Ci	Comprehensive Ranking
D1W1N1	0.1375	0.6939	0.8346	1
D1W1N2	0.2441	0.6579	0.7294	3
D1W2N1	0.2018	0.6458	0.7619	2
D1W2N2	0.2892	0.5901	0.6711	4
D1W3N1	0.3121	0.5284	0.6287	5
D1W3N2	0.3613	0.5079	0.5841	6
D2W1N1	0.6254	0.2030	0.2451	8
D2W1N2	0.6294	0.2454	0.2805	7
D2W2N1	0.6783	0.1358	0.1668	10
D2W2N2	0.6753	0.1537	0.1854	9
D2W3N1	0.7339	0.0854	0.1042	12
D2W3N2	0.7226	0.0793	0.0784	11

shows that the comprehensive score of D1 was higher than D2 under different planting modes. The comprehensive score of W1 was higher than W2 and W3 under different water control. Under different nitrogen application levels, the comprehensive score of N1 was higher than N2. In all treatments, D1W1N1 ranked first, and D2W3N1 ranked last.

3.2.3. Combination Evaluation

According to the combined evaluation of the results obtained by the PCA and TOPSIS comprehensive evaluation method (

Table 8. Comprehensive score and ranking of combination evaluation method under different water and nitrogen regulations.

Treatment	Score	Ranking	Treatment	Score	Ranking
D1W1N1	14.9106	2	D2W1N1	0.8298	9
D1W1N2	15.8187	1	D2W1N2	3.7014	7
D1W2N1	9.7953	3	D2W2N1	0.3516	10
D1W2N2	9.7760	4	D2W2N2	0.8307	8
D1W3N1	3.9825	6	D2W3N1	0.0143	12
D1W3N2	4.6218	5	D2W3N2	0.0303	11

), the highest comprehensive score of D1W1N2 treatment was 15.8187. Meanwhile, the comprehensive ranking of mixed sowing, slight water deficit, and high nitrogen application treatment was at the forefront.

4. Discussion

4.1. Effects of the Water-Nitrogen Regulation on Growth, Yield, and Quality of Herbage

Nitrogen and water are critical factors for the growth of herbage. Only the full absorption and use of nitrogen and timely water compensation during the critical growth period can produce more yield and better quality per unit of nitrogen and water. The results showed that the plant height, leaf area index, and herbage yield could improve with increasing water and nitrogen. This is similar to the research results of Saeed and EI Nadi [38] that large and infrequent irrigation could reduce alfalfa plant height, leaf area index, dry matter accumulation, and WUE. Meanwhile, the study of Wang et al. [39] also provided evidence. According to his research, increasing proper water content and nitrogen application could improve height, thereby increasing plant dry and fresh weight. However, Qiu et al. [40] found that the dry matter yield of herbage changed in a parabola with increasing irrigation water volume (about 163~321 mm for two cuts). This finding was different from the result that adding irrigation water volume could enhance herbage in this study. The possible affecting factor was that the maximum lower irrigation limit in this study was 65% of the field capacity. In addition, this study was also different from the study of Li et al. [41] in Hulunbeier that the maximum yield of the mixed-sowing alfalfa and bromus inermis under the condition of no water supplement and low nitrogen because of climate difference. The annual precipitation in Hulunbeier is 250~400 mm. Nevertheless, the average annual precipitation in this study area is only 90 mm, and the precipitation during the growth period of herbage in 2020 was only 51.4 mm.

CP and RFV are important indexes to measure herbage quality. The results showed that adding irrigation and nitrogen application could increase the CP and RFV of herbage, which was similar to the research results of Bi et al. [42] and Rostamza et al. [43]. In the study of Bi, high irrigation and nitrogen application could improve the quality of alfalfa. The study of Rostamza verified that reasonable water and nitrogen application could obtain high-quality bromus inermis. Moreover, this study found that the RFV of mono-sowing bromus inermis was higher than mixed-sowing alfalfa and bromus inermis, which was similar to the results of Wallsten et al. [44]. The possible impacting factor was that the stem of alfalfa was more developed than bromus inermis, and the stem-leaf ratio was also significantly higher than bromus inermis. Therefore, the fiber content of alfalfa was higher than bromus inermis, leading to the low RFV calculated by acid and neutral detergent fiber content in the mixed-sowing group.

4.2. Effects of the Water-Nitrogen Regulation on the Water-Nitrogen Use Efficiency of Herbage

Water and nitrogen affect not only the yield and quality of herbage but also the IWUE, WUE, PFP_N,and CP_WUE. The water-nitrogen use efficiency is an important index to measure the management of herbage planting. Making full use of limited water and fertilizer is an effective way to improve the water-nitrogen use efficiency of herbage. This study showed that adding irrigation water increased the PFP_N of herbage but decreased IWUE and WUE, which was consistent with the results of Ayars et al. [45]. Meanwhile, the study of Yin et al. [46] in the semi-arid area of western Liaoning Province found that water and nitrogen had significant interaction on spring wheat WUE. This result was different from our result in that water and nitrogen interaction had no significant effect on herbage WUE in this study. The main possible factors affecting this difference were the experimental period and the range of nitrogen application. The cumulative effect of a longer experiment could better show the coupling effect of water and nitrogen on crop growth. In this study, the range of nitrogen fertilizer application was limited (only 60 kg·ha⁻¹ and 120 kg·ha⁻¹), and the coupling of WUE was not well realized. At the same time, this study found that the amount of irrigation and nitrogen, as well as their interaction, had a significant impact on the PFP_N of herbage because PFP_N was the yield-nitrogen ratio. The effect of nitrogen application amount between the two treatments on PFP_N was far greater than the water-nitrogen supply on yield. In other literature, nitrogen application could make the yield and the CP of herbage maize achieve coordinated growth [47], indicating that nitrogen application was conducive to the improvement of CP_WUE when the irrigation level was the same. This finding was similar to the result that the nitrogen application was beneficial to improving the herbage CP_WUE in this study. In addition, nitrogen addition was beneficial to the formation of crop yield, which partly improved crop yield and IWUE but significantly reduced PFP_N [48,49]. This research finding was similar to that the higher nitrogen application rate obtained in this study could improve herbage WUE and reduce PFP_N. In conclusion, a high nitrogen application rate could significantly reduce PFP_N, resulting in a serious waste of nitrogen resources.

4.3. Water-Nitrogen Regulation and Planting Pattern for Herbage Growth

Multi-index can be applied to evaluate the effect of different water-nitrogen supply and planting modes on herbage production more intuitively and accurately. The combination evaluation method can eliminate the possibility that different evaluation methods have inconsistent evaluation results, making the evaluation results more accurate. In this paper, nine representative indicators, such as plant height, leaf area index, yield, CP content, and water-nitrogen use efficiency, were selected from the physiological growth, yield, quality, and water-nitrogen use of herbage for comprehensive evaluation. According to these findings, the mixed-sowing mode with slight water deficit and high nitrogen application (D1W1N2, lower irrigation limit: 65% θ_f. Nitrogen application: 120 kg·ha⁻¹) was a suitable planting and management mode for herbage in the northwest inland arid region of China. Similar to the results of this study, Ma et al. [50] found that the optimal water and fertilizer scheme in the northwest arid desert area was 65.33~71.11% of the relative soil water content, 138~172 kg·ha⁻¹ of nitrogen and 82.09~117.91 kg·ha⁻¹ of phosphorus through the water-fertilizer coupling regression model. Tang et al. [24] applied regression prediction to obtain that the suitable range of water and nitrogen for bromus inermis in Hexi Corridor was 546~552 mm and 136~152 kg·ha⁻¹. Liu et al. [51] found that the yield of tall wheatgrass was the highest when the irrigation gradient was 60% of the field capacity and nitrogen application was 180 kg·ha⁻¹. In addition to the water-nitrogen regulation, reasonable planting mode was also an effective way to improve herbage yield and quality and the water-nitrogen use efficiency. Shen [52] found that the mixed-sowing alfalfa and bromus inermis could improve the stability of the artificial grassland ecosystem compared with the mono-sowing. In the meantime, the herbage yield and quality were better, which was consistent with the conclusion that the mixed-sowing mode of alfalfa and bromus inermis had the best comprehensive effect. Due to the above-ground and underground parts of alfalfa and bromus inermis having more reasonable spatial configuration after the mixed-sowing, they could absorb the required water and nutrients from different soil layers. In addition, bromus inermis could also use the nitrogen produced by the nitrogen fixation of the alfalfa root system to promote its growth and development. Therefore, the complementation of both sides of each other is an ideal mixed-sowing combination.

5. Conclusions

Appropriate irrigation and nitrogen application could promote the coupling effect of water and fertilizer, improve herbage growth, enhance quality, and increase water and nitrogen use efficiency. The height, leaf area index, and yield of bromus inermis and alfalfa mixed-sowing increased by 81.63%, 119.52%, and 111.51%, respectively, compared to bromus inermis mono-sowing. The CP content of bromus inermis and alfalfa mixed-sowing increased by 41.44%, while RFV decreased by 16.34% compared to bromus inermis mono-sowing. The WUE, IWUE, PFP_N, and CP_WUE of bromus inermis and alfalfa mixed-sowing were on average 88.59%, 87.30%, 112.98%, and 163.28% higher, respectively, than those of mono-sowing. Increasing irrigation amount could improve PFP_N and CP_WUE, while increasing nitrogen application could improve WUE, IWUE, and CP_WUE of herbage. Through principal component analysis, TOPSIS comprehensive evaluation, and combination evaluation method, the evaluation of the herbage production effect under different planting management was obtained. The bromus inermis and alfalfa mixed-sowing combined with mild water shortage (irrigation lower limit: 65% θ_f) and high nitrogen application (120 kg·ha⁻¹) had the best comprehensive evaluation and is the suitable artificial grassland planting management mode in the oasis-desert interlacing area of Hexi, Gansu Province, China, and areas with a similar climate.