Analysis of Maize Planting Mode and Simulation and Optimization of Ridging and Fertilization Components in Arid Area of Northwest China

Abstract

The arid area of Northwest China belongs to the rain-fed agricultural area of the Loess Plateau, and water resources have become one of the important factors limiting agricultural development in this area. This study employed the AquaCrop model to predict the yield advantages and environmental adaptability of maize in Dingxi City from 2016 to 2020 under two cultivation practices: ridge tillage (100% film coverage with double ridge-furrow planting) and flat planting (81.8% film coverage with wide-film planting). The numerical simulation of the tillage and fertilization process of the double-ridge seedbed was carried out by EDEM, and the key components were tested by the Box–Behnken center combination test design principle to obtain the optimal parameter combination. The results showed that ridge planting was more suitable for agricultural planting in rain-fed arid areas in Northwest China. The simulation analysis of ridging and fertilization showed that the forward speed of the combined machine was 0.50 m/s, the rotation speed of the trough wheel of the fertilizer discharger was 39 rmp, and the rotary tillage depth was 150 mm. The qualified rate of seedbed tillage was 93.6%, and the qualified rate of fertilization was 92.1%. The research shows that the whole-film double ridge-furrow sowing technology of maize is more suitable for the rain-fed agricultural area in the arid area of Northwest China. The simulation results of the ridging fertilization device are consistent with the field experiment results. The research results provide a certain technical reference for the optimization of the whole-film double ridge-furrow sowing technology.

1. Introduction

Most of Northwest China belongs to the arid and semi-arid region; the annual rainfall is less than 500 mm, and the cultivated land in the arid area accounts for about 51% of the national cultivated land area [1]. In particular, Gansu Province is a typical loess landform area with a semi-arid continental climate. Although the region is rich in light and heat resources and has considerable climate production potential, the supply of water resources is seriously insufficient. The amount of water resources per hectare accounts for 67% of the global average, and the spatial and temporal distribution is uneven. Agricultural water accounts for 90% of the total water consumption. Rainfall is mainly concentrated in July, August and September, mostly in the form of rainstorms. Water resource utilization is low, soil erosion is severe, and evaporation exceeds 1400 mm, with frequent spring droughts and rain. It is a typical rain-fed agricultural area, which limits the development of agricultural production in Northwest China [2,3,4,5].

With the advancement of agricultural technology, plastic film mulching has been increasingly utilized in agricultural production, highlighting its growing importance [6]. Following seeds, pesticides, and fertilizers, film mulching has become a critical measure for enhancing agricultural yield and an effective strategy for addressing rainfall shortages in the arid regions of Northwest China. There are two main planting patterns of maize in Northwest China: wide-film planting with a film mulching rate of 81.8% and full-film double ridge-furrow planting with a film mulching rate of 100% [7,8,9]. In 2003, scholars in Gansu Province put forward the whole-film double ridge-furrow sowing technology of maize for rain-fed agriculture in the arid area of Northwest China [10]. This technology can realize a surface-mulching film to inhibit surface evaporation; rainwater collection and infiltration on the surface of the film; and sowing in the furrow so as to realize the conversion of ineffective precipitation of less than 5 mm into effective precipitation. Increasing soil temperature helps to improve the activity of organic matter and inhibit the growth of weeds, effectively alleviating the contradiction between the water required for crop growth and the dislocation of rainwater supply and demand in the arid areas of North-west China and improving water use efficiency [11,12,13,14,15]. In recent years, the application area of the full plastic film double ridge-furrow planting technique in Gansu Province has remained stable at approximately 1 million hectares. Maize is China’s most significant grain crop, and ensuring its production is crucial for national food security, promoting the development of the livestock industry, and increasing farmers’ productivity and income.

The implementation of the whole-film double ridge-furrow planting technique involves operations such as rotary tillage, ridge formation, fertilization, film mulching, and soil covering, so the mechanization level of the operation determines the promotion and application of the technology [16]. Ridging and fertilization directly affect the effect of water collection, drought resistance, and yield increase of the whole-film double ridge-furrow sowing technology. If the quality of ridge construction is poor, the effect of rainwater collection will be affected, and the uneven planting base fertilizer will cause seedling burning and other effects on crop yield. Dai et al. [17] used the discrete method to numerically simulate the film edge and transverse covering soil of the whole-film double ridge-furrow and explored the variation law of the velocity, displacement, and covering soil of the vibrating plate with time. Zhang et al. [13] used ABAQUS 2018 software to establish a three-dimensional finite element model of the interaction between the wheel set of the pressing device and the seedbed soil and simulated the dynamic process of the interaction between the soil-engaging parts and the soil during the pressing operation. The three-factor and three-level Box–Behnken experimental design method was used to find the optimal combination of operating parameters for the pressing wheel group of the full-film double-furrow film mulching machine. In order to further improve the construction quality of the whole-film double-furrow seedbed, Shi et al. [18] used CFD-DEM gas–solid coupling technology to analyze the interaction mechanism between soil and air flow in the whole-film double-furrow seedbed under different wind speeds and different directions and optimized the seedbed construction method. Song et al. [16] used the discrete element method to study the effects of different ridging inclination angles and buried depths on the quality of ridges during rotary tillage and ridging.

While extensive research has been conducted on the ridge formation, soil covering, and suppression stages of the full plastic film double ridge-furrow planting system, the analysis and study of the shapes of the ridge plow and fertilizer shovel have been relatively limited. Building on the earlier work of our team, which employed the AquaCrop model to analyze the yield impacts of two maize planting patterns in Gansu Province, this study further utilizes EDEM 2020 software to optimize and analyze the ridge tillage and fertilization components of the full plastic film double ridge-furrow planting system suitable for rain-fed agricultural areas, thereby integrating agronomy with agricultural machinery.

2. Materials and Methods

2.1. Test Site Overview

The experiment was carried out at the Dingxi Drought Experimental Station in Gansu Province from 2016 to 2020. It is located in the central part of Gansu Province (104°62′ E, 35°58′ N), with an altitude of 1894.5 m. It belongs to the typical semi-arid climate of the Loess Plateau. The region has an average annual temperature of 6.7 °C, with an annual precipitation of 386.6 mm and an evaporation rate exceeding 1400 mm. The spring season is characterized by dry conditions with frequent rainfall, and total solar radiation reaches 5923.8 MJ/m². The frost-free period lasts approximately 140 days. The soil is classified as loessal soil, with groundwater depths below 10 m. Additionally, the area experiences significant surface runoff and severe soil erosion, making it a typical rain-fed agricultural zone. The main planting patterns of maize are flat planting and ridge planting, as shown in Figure 1, and the planting pattern parameters are shown in

Table 1. Parameters of four planting patterns.

Planting Pattern	Tillage Method	Plastic Film Coverage Rate	Sowing Method	Row Spacing/mm	Distance between Hills/mm
flat planting mode	flatten culture	81.8%	Sowing in film	400–500	200–300
ridge planting mode	whole-film double furrow	100%	Ridge-furrow sowing	400–500	200–300

.

2.2. Data Sources and the Principle of AquaCrop Model

The meteorological data required for this study are from the National Meteorological Data Network, and the meteorological data interval is 1 day, as shown in Figure 2. Soil data are presented in

Table 2. Soil physical and chemical parameters.

Soil Thickness (cm)	Texture	Bulk Weigh (g/cm3)	Wilting Coefficient (vol%)	Field Water Holding Capacity (vol%)	Saturated Water Content (vol%)	Saturated Hydraulic Conductivity (mm/Day)
0–20	loam	1.08	7.68	26.05	55.25	250
20–100	silt loam	1.23	7.13	26.45	43.61	150

.

AquaCrop is a crop growth model describing the interaction between plant and soil. It separates the actual evapotranspiration (ET) into soil evaporation (E) and crop transpiration (Tr) and separates the final yield (Y) into biomass (B) and harvest index (HI). The core formula of the AquaCrop growth engine is as follows:

$$ET=E+Tr$$

(1)

$$Y=HI\cdot B$$

(2)

$$B=WP\cdot {\displaystyle \sum Tr}$$

(3)

In the formula, Tr is crop transpiration in mm. Wp is the water productivity parameter.

2.3. Simulation Analysis Results

According to the team’s previous research [19], The AquaCrop model was used to simulate the total soil moisture content during the entire growth period of maize under two different planting modes in Dingxi City as a function of rainfall. As shown in Figure 3, the total water content of the ridge soil profile in 2016 and 2017 was more than 90% higher than that of the flat planting mode in the same period. In the wet years of 2018, 2019, and 2020, the soil water content of the ridge planting mode was more than 80% higher than that of the flat planting mode in the same period. In the dry year, the anti-steaming effect of the ridge planting mode was more significant than that in the wet year. From 2016 to 2020, the aboveground biomass, yield, and water productivity of the ridge planting mode were higher than those of the flat planting mode. In dry years, the increase in aboveground biomass and yield was larger, and the increase in water productivity was smaller. In wet years, the increase in aboveground biomass and yield was smaller, and the increase in water productivity was larger. It can be seen that the yield-increasing effect of the whole-film double ridge-furrow planting mode is more significant in dry years, as shown in

Table 3. Simulation results under two planting patterns in 2016~2020.

Project	Planting Pattern	2016	2017	2018	2019	2020
aboveground biomass	flat mode	14.05	15.30	17.28	16.61	16.23
	ridge planting model	18.62	19.44	19.84	19.40	18.82
yield	flat mode	6.32	6.87	7.78	7.48	7.30
	ridge planting model	11.88	12.50	12.70	12.42	12.05
water productivity	flat mode	1.78	1.90	1.90	1.82	1.98
	ridge planting model	3.32	3.47	3.92	3.69	3.96

. It can be seen that the effect of the whole-film double ridge-furrow sowing technology is obviously better than that of the flat planting mode.

3. Parameter Optimization of Full-Film Double Ridge-Furrow Ridging and Fertilizing Machine

Through the above research, the whole-film double ridge-furrow planting technology is more suitable for rain-fed agricultural planting in the arid area of Northwest China. In the previous study, the effect of covering with polyethylene film in the whole-film double ridge-furrow planting technology is more obvious than that of covering with biodegradable film [20]. In order to promote the application of full-film double ridge-furrow sowing technology in a large area, mechanized planting must be carried out. In order to ensure the quality of seedbed construction such as ridging and fertilization, the key components of ridging and fertilization should be optimized.

3.1. The Whole-Machine Mechanism and Working Principle of Whole-Film Double Ridge-Furrow Ridging and Fertilizing

The whole-film double ridge-furrow film mulching combined machine is mainly composed of a main frame, suspension device, rotary blade group, fertilizer discharge device, spraying device, ridging device, film mulching device, soil mulching device, seed metering device, and pressing device. The three-point suspension type can be used to complete the functions of rotary tillage, strip fertilization, ridging and ditching, film mulching and soil mulching, sowing, and pressing at one time [7]. Among them, the double-ridge tillage and fertilization device is mainly composed of a rotary blade group, fertilization shovel, fertilizer shaft, fertilizer discharger, fertilizer guide pipe, soil shovel, and so on. The fertilization shovel is fixed to the front beam of the frame by a U-shaped clamp, and the soil shovel is connected by the beam. The bolt is fixed to the rear beam of the frame. The structure of the combined machine and the double-ridge tillage and fertilization device is shown in Figure 4.

3.2. Simulation Model Establishment

The fertilizer particles are spherical particles with a sphericity of more than 90%. At the same time, in order to improve the simulation efficiency of the model, the soil particles and fertilizer particles of the seedbed are modeled by spherical particles. In this experiment, Stanley compound fertilizer was used as the fertilizer reference (dry non-caking particles). The radius of the single-sphere particles of the soil model was set to 5 mm, and the radius of the single-sphere particles of the fertilizer model was set to 1.65 mm. The rotary blade group, the soil shovel, and the fertilization shovel are all steel materials, and the material of the fertilizer trough wheel is PLA plastic. The Hertz-Mindlin (no-slip) model is used for soil particles and soil particles, fertilizer particles and fertilizer particles, soil particles and fertilizer particles, fertilizer particles and fertilizer discharger, soil particles and rotary blade group, and soil shovel and fertilization shovel. The setting of relevant parameters of the test simulation is shown in

Table 4. Discrete element simulation parameters.

Project	Parameter	Value
soil particle	density	0.3
	shear modulus/Pa	1.0 × 108
	density/(kg/m3)	2680
fertilize particle	Poisson’s ratio	0.25
	shear modulus/Pa	1.0 × 107
	density/(kg/m3)	1861
steel	Poisson’s ratio	0.28
	shear modulus/Pa	3.5 × 1010
	density/(kg/m3)	7850
fertilizing groove wheel	Poisson’s ratio	0.394
	shear modulus/Pa	3.18 × 108
	density/(kg/m3)	1240
soil–soil	coefficient of restitution:	0.3
	coefficient of static friction:	0.5
	coefficient of rolling friction:	0.3
fertilizer–fertilizer	coefficient of restitution:	0.11
	coefficient of static friction:	0.3
	coefficient of rolling friction:	0.1
soil–steel	coefficient of restitution:	0.3
	coefficient of static friction:	0.4
	coefficient of rolling friction:	0.1
soil–fertilizer	coefficient of restitution:	0.3
	coefficient of static friction:	0.5
	coefficient of rolling friction:	0.02
fertilizer—fertilizer groove wheel	coefficient of restitution:	0.41
	coefficient of static friction:	0.32
	coefficient of rolling friction:	0.18

[20,21,22,23].

According to the requirements of full-film double-furrow agronomic cultivation techniques, a soil bin model suitable for double-furrow tillage and fertilization operations was established in EDEM, and its size was set to be 2700 mm (length) × 1200 mm (width) × 400 mm (height). The above models were imported into EDEM software in IGES format for simulation experiments. The double-furrow tillage and fertilization operation model is shown in Figure 5.

3.3. Double-Ridge Seedbed Tillage Fertilization Device Parameter Optimization

3.3.1. Experimental Design and Methods

Combined with the team’s previous research [20], the operating motion parameters and mechanism analysis results of the ridging fertilization device, the driving speed of the ridging fertilization device X₁ (0.50 m/s~1.00 m/s), the rotation speed of the straight groove wheel X₂ (30 rmp~50 rmp), and the depth of rotary tillage X₃ (100 mm~150 mm) are taken as the test influencing factors, and the qualified rate of seedbed tillage Y₁ and the qualified rate of fertilization Y₂ are selected as the numerical simulation indexes of the optimized working parameters. The response surface analysis method was used to analyze and discuss the above influencing factors with three factors and three levels.

Table 5. Factors and horizontal coding.

Level Project	Factors
	Forward Speed of Combined Operation Machine X1/m·s−1	Slot Wheel Speed of Fertilizer Discharger X2/rpm	Working Depth X3/mm
−1	0.50	30	100
0	0.75	40	125
1	1.00	50	150

presents the selected levels for each experimental factor. A total of 17 simulation trials were conducted using response surface methodology, with each trial repeated three times. The average value of the test results under each set of working parameters was taken as the actual response indicator. The average test results under the working parameters of the group were taken as the actual index values, and the Design-Expert 8.0.6 data analysis software was used to analyze and process the data under the simulation.

3.3.2. Establishment and Test of Regression Model

The test results are shown in

Table 6. Response surface analysis results.

Test Number	X1	X2	X3	Y1/%	Y2/%
1	−1	−1	0	85.1	76.8
2	−1	1	0	80.9	73.2
3	0	−1	−1	72.2	70.8
4	−1	0	1	92.4	93.2
5	0	0	0	79.1	85.9
6	0	1	1	90.6	78.6
7	1	−1	0	76.5	71.6
8	0	−1	1	88.6	76.4
9	0	0	0	83.7	86.5
10	0	0	0	78.4	87.3
11	1	1	0	85.7	74.3
12	−1	0	−1	73.8	81.9
13	0	1	−1	69.1	67.5
14	1	0	1	88.9	90.1
15	0	0	0	78.3	86.9
16	1	0	−1	75.8	78.7
17	0	0	0	76.9	85.1

below. The qualified rate of seedbed tillage and fertilization in the operation of the whole-film double ridge-furrow ridging and fertilization device can be achieved, but the stability of the tillage performance of the double-ridge seedbed and the quality of mechanized ridging and fertilization in the seedbed fluctuate greatly during the test.

The test results obtained from the simulation were analyzed and processed by Design-Expert 8.0.6 software, and then the coded values of the test results were obtained. The quadratic regression model (QRM) of the qualified rate of seedbed tillage Y₁ is:

$$\begin{array}{c}\begin{array}{c}{Y}_1=79.28-0.66X_1+0.49X_2+8.70X_3+2.68X_1^2+\\ 0.085X_2^2+0.76X_3^2+3.35X_1{X}_2-1.38X_1{X}_3+1.28X_2{X}_3\end{array}\end{array}$$

(4)

where Y₁ is the qualified rate of seedbed tillage, %; X₁ is the forward speed coding value of the combined operation machine; X₂ is the coding value of the rotation speed of the fertilizer trough wheel; and X₃ is the coding value of rotary tillage depth.

The QRM of the qualified rate of seedbed tillage was obtained by processing the experimental data. The variance analysis and regression coefficient test of the regression model were further carried out by the software. The results are shown in

Table 7. Variance analysis of regression equation.

Variation Source	Quadratic Sum	Degree of Freedom	Mean Square	F	p
Model	704.00	9	78.22	14.76	0.0009 **
X1	3.51	1	3.51	0.66	0.4424
X2	1.90	1	1.90	0.36	0.5680
X3	605.52	1	605.52	114.29	<0.0001 **
X1×2	44.89	1	44.89	8.47	0.0226 *
X1×3	7.56	1	7.56	1.43	0.2711
X2×3	6.50	1	6.50	1.23	0.3045
X12	30.35	1	30.35	5.73	0.0479 *
X22	0.030	1	0.030	0.006	0.9417
X32	2.43	1	2.43	0.46	0.5198
Residual	37.09	7	5.30
Lack of fit	10.12	3	3.37	0.50	0.7021
Pure Error	26.97	4	6.74
Cor Total	741.08	16

Note: * significant (p < 0.05), ** extremely significant (p < 0.01).

.

The test results are shown in Table 7. According to the analysis of variance of the regression equation, R² is 0.82, close to 1, the experimental value and the predicted value have a high degree of fitting, the p-value of the QRM of the qualified rate of seedbed tillage is 0.0009, which is less than 0.01, and the results show that the regression model is extremely significant. The p-value of the loss of fit item was 0.7021, which was greater than 0.05, that is, the loss of fit was not significant, indicating that the QRM equation fitted by the test results was consistent with the actual situation, which could accurately reflect the relationship between the qualified rate of seedbed tillage (Y₁) and the forward speed of the machine (X₁), the speed of fertilizer discharge (X₂), and the depth of rotary tillage (X₃). The model could be used to predict the results of the optimization test, in which the first term—rotary tillage depth (X₃)—of the regression model had a very significant effect, the second term—machine forward speed (X₁₂)—had a very significant effect, and the interaction term for machine forward speed and fertilizer discharge slot wheel speed (X_1×2) had a significant effect. The rest of the items are not significant. From the coefficient of each influencing factor of the model regression equation, it can be seen that the factors affecting the qualified rate of seedbed tillage from large to small are machine forward speed (X₁), rotary tillage depth (X₃), and fertilizer trough wheel speed (X₂).

Through the analysis and processing of the test result data obtained from the simulation, the coding value of the test result is obtained, and the QRM of the fertilization qualification rate Y₂ is:

$$\begin{array}{c}\begin{array}{c}{Y}_2=86.34-1.30X_1-0.25X_2+4.92X_3+0.14X_1^2-\\ 12.51X_2^2-0.51X_3^2+1.57X_1{X}_2+0.025X_1{X}_3+1.37X_2{X}_3\end{array}\end{array}$$

(5)

where Y₂ is the qualified rate of fertilization, %; X₁ is the forward speed coding value of the combined operation machine; X₂ is the coding value of the rotation speed of the fertilizer trough wheel; and X₃ is the coding value of rotary tillage depth.

The QRM of the qualified rate of fertilization was obtained by processing the experimental data. The variance analysis and regression coefficient test of the regression model were further carried out by the software. The results are shown in

Table 8. Variance analysis of regression equation.

Variation Source	Quadratic Sum	Degree of Freedom	Mean Square	F	p
Model	891.40	9	99.04	85.57	<0.0001 **
X1	13.52	1	13.52	11.68	0.0112 *
X2	0.50	1	0.50	0.43	0.5320
X3	194.04	1	194.04	167.65	<0.0001 **
X1×2	9.92	1	9.92	8.57	0.0221 *
X1×3	0.002	1	0.003	0.002	0.9642
X2×3	7.56	1	7.56	6.53	0.0378 *
X12	0.086	1	0.086	0.074	0.7936
X22	658.68	1	658.68	569.09	<0.0001 **
X32	1.08	1	1.08	0.94	0.3653
Residual	8.10	7	1.16
Lack of fit	5.11	3	1.70	2.28	0.2216
Pure Error	2.99	4	0.75
Cor Total	899.50	16

Note: * significant (p < 0.05), ** extremely significant (p < 0.01).

.

The test results are shown in Table 8. Through the analysis of variance of the regression equation, R² is 0.99, close to 1, and the experimental value and the predicted value have a high degree of fitting; it can be seen that the QRM of the fertilization qualification rate is p < 0.01, and the results show that the regression model is extremely significant. The p-value of the loss of fit item was 0.2216, which was greater than 0.05, that is, the loss of fit was not significant, indicating that the QRM equation fitted by the test results was consistent with the actual situation, which could accurately reflect the relationship between the fertilization qualification rate (Y₂) and the forward speed of the machine (X₁), and the rotation speed of the fertilizer (X₂) and the depth of the rotary tillage (X₃). The model could be used as a prediction of the results of the optimization test. Among them, the regression model of the first term—rotary tillage depth (X₃)—had a very significant effect, the second term—fertilizer wheel speed (X₂²)—had a very significant effect, and the interaction term for fertilizer wheel speed and rotary tillage depth (X_2×3) had a significant effect. The influence of the forward speed of the interactive machine and the speed of the fertilizer groove wheel (X_1×2) is more significant, and the rest is not significant. According to the coefficient of each influencing factor in the regression equation of the model, the factors affecting the qualified rate of fertilization from large to small are the rotation speed of the fertilizer groove wheel (X₂), the depth of rotary tillage (X₃), and the forward speed of the machine (X₁).

Figure 6 shows the fourth group of experiments that is shown in Table 6. When the forward speed of the combined machine is 0.5 m/s, the rotation speed of the fertilizer groove wheel is 40 m/s, and the rotary tillage depth is 150 mm, the double-ridge tillage and fertilization device is shown in the double-ridge tillage process, and it is shown from different perspectives in the figure. In the double-ridge tillage process, at this time, the qualified rate of seedbed tillage is 92.4%, and the qualified rate of fertilization is 93.2%.

Figure 7 shows the 13th group test that is shown in Table 6. When the forward speed of the combined machine is 0.75 m/s, the rotation speed of the fertilizer trough wheel is 50 rmp, and the rotary tillage depth is 100 mm, the ridge-forming device is in the double-ridge tillage process, and it is shown from different perspectives in the figure. At this time, the qualified rate of seedbed tillage is 69.1%, and the qualified rate of fertilization is 67.5%.

In the process of the simulation test, it was found that there were some differences in the quality effect of seedbed size ridge and furrow and the quality effect of fertilization after double-ridge seedbed tillage and fertilization under different experimental factors. From the response surface simulation analysis of the test process (Figure 6a–c and Figure 7a–c) and the cross-sectional size distribution of tillage and fertilization in the double-ridge seedbed (Figure 6d and Figure 7d), it can be concluded that tillage depth and the forward speed of the combination machine significantly affect the qualification rate of seedbed preparation and fertilization, consistent with the variance analysis of the regression equation.

Under the condition of constant power for the full plastic film double ridge-furrow planter, forward speed is the key factor affecting the performance of double-ridge tillage, consistent with the variance analysis of the regression equation. Furthermore, at the same forward speed, greater tillage depth of the rotary blade assembly leads to better formation quality of the non-standard double ridges. Therefore, it is essential to identify the optimal working parameters for the ridging device.

3.3.3. Analysis of Model Interaction Terms

According to the QRM, the response surface of the relationship between the factors was made. According to the analysis of the results of Table 6, among the three experimental factors, only the interaction between the forward speed of the full-film double-furrow sowing combined machine (X₁) and the speed of the fertilizer discharger wheel (X₂) had a significant effect on the qualified rate of seedbed tillage, and other interaction factors were not significant. In the qualified rate index of seedbed tillage, the interaction between forward speed and fertilizer discharge speed is shown in Figure 8a. In the range of 30~40 rmp, the qualified rate of seedbed tillage decreased with the increase in the forward speed of the machine. In the range of 40~50 rmp, the qualified rate of seedbed tillage decreased first and then increased.

Through the analysis of simulation results, when the rotary tillage depth is fixed at a certain level, and the advance speed in front of the combined operating machine increases from 0.5 m/s to 1.0 m/s, the qualified rate of seedbed tillage gradually decreases. The main reason is that in the process of the ridging operation, the forward speed of the combined machine is increasing, and the time of cutting, advancing, and follow-up digging of the tillage soil by the rotary blade group, the fertilization shovel body, and the double-wing shovel is shortened. The plasticity of the soil to the soil is weakened, and the soil particles on both sides of the large and small ridges are further caused by the fall of the soil particles on both sides of the large and small ridges. The phenomenon of burying the soil in the furrow further reduces the compliance rate of the double-ridge tillage bed.

According to the results of Table 8, among the three experimental factors, the interaction between the forward speed X₁ of the whole-film double ridge-furrow sowing combined machine and the rotational speed X₂ of the groove wheel of the fertilizer distributor, and the interaction between the rotational speed of the groove wheel of the fertilizer distributor (X₂) and the rotary tillage depth (X₃), had a significant effect on the qualified rate of fertilization, and other interaction factors were not significant. In the fertilization qualification rate index, the interaction between the forward speed and the rotation speed of the fertilizer is shown in Figure 9a. In the range of 30~40 rmp, the fertilization qualification rate increases with the increase in the forward speed of the machine. In the range of 40~50 rmp, the qualified rate of fertilization increased first and then decreased. The interaction between rotary tillage depth and fertilizer rotation speed is shown in Figure 9b. In the range of 30~40 rmp, the qualified rate of fertilization increases with the increase of rotary tillage depth. In the range of 40~50 rmp, the qualified rate of fertilization increased first and then decreased. The interaction between rotary tillage depth and fertilizer rotation speed is shown in Figure 9c. In the range of 30~40 rmp, the qualified rate of fertilization increases with the increase in rotary tillage depth. In the range of 40~50 rmp, the qualified rate of fertilization increased first and then decreased.

Through the analysis of simulation results, when the rotation speed of the fertilizer discharger is fixed at a certain level and when the rotary tillage depth increases from 100 mm to 150 mm, the qualified rate of fertilization gradually increases. The main reason is that in the process of ridging and fertilizing the combined machine, as the depth of rotary tillage continues to decrease, the resistance value of the fertilizing shovel body will become larger and larger, and the time of random follow-up excavation will become shorter. The rear soil lifting parts also increase with the decrease in the depth of rotary tillage, and the plasticity of the soil is weakened. Further, the soil particles fall back to the furrow, which leads to a decrease in the qualified rate of seedbed tillage, so the fertilization operation does not meet the operation requirements and reduces the qualified rate of fertilization.

3.3.4. Optimization of Working Parameters of Double-Ridge Tillage and Fertilization Device

Through the above research and analysis, the qualified rate of seedbed tillage and fertilization is 100% when the ridge fertilization device works, and then the optimal working parameters of the ridge fertilization device are obtained: the forward speed of the combined machine is 0.5 m/s, the speed of the fertilizer discharger is 39 rmp, and the rotary tillage depth is 150 mm.

In order to verify the numerical simulation of the whole-film double-ridge ridging fertilization operation process, as shown in Figure 10a–i, the optimal working parameters were selected, and the simulation time was t = 0.6 s~6.2 s. During the period of double-ridge fertilization, there was a device-specific operation molding effect. In order to better show and observe the interaction between the rotary blade group, the ordinary fertilization shovel, the double-wing soil shovel, and the seedbed soil, and to observe the effect of the straight slot wheel, it is necessary to observe the numerical simulation operation process when the fertilizer is filled and the rotary tillage device is in stable contact with the seedbed soil. Therefore, the numerical simulation of the ridging fertilization device is close to the working condition of the mechanized double-ridge tillage and fertilization operation when t = 0.6 s, as shown in Figure 10a. When t = 0.6 s~2.9 s, under the action of gravity, the fertilizer fills the groove of the groove wheel, and then the groove wheel rotates with the fertilizer axis to drive the fertilizer particles to discharge outward. At the same time, the fertilization shovel follows the rotary blade group to start the deep fertilization operation so that it is deeply applied to form the base fertilizer. The two-wing pick-up shovel excavates the soil above the fertilizer after fertilization with the rotary blade group and the fertilization shovel operation and then forms a ridge. When t = 3.3 s, the fertilizing shovel and the double-wing shovel have fully entered the seedbed soil and excavated the soil particles, which are mixed with the soil particles thrown by the high-speed cutting of the rotary blade group, resulting in a more complex and chaotic soil particle flow field, as shown in Figure 10d. When t = 3.6 s~5.4 s, as shown in Figure 10e–h, the flow field boundary of soil particles produced by the fertilization shovel and the double-wing shovel combined with the high-speed rotating rotary blade group gradually became clear, and the seedbed gradually formed a complete small ridge and a half of the large ridges on both sides. At the same time, the condition and dispersion degree of soil particles scattered by the rotary blade group were significantly higher than those of the fertilization shovel and the double-wing shovel. When t = 6.2 s, the simulation of the mechanized double-ridge tillage and fertilization operation was completed, and the special-shaped double-ridge seedbed and fertilization operation that met the technical requirements of full-film double ridge-furrow sowing agriculture were formed.

As shown in Figure 11, the simulation of the specific operation effect of double-ridge tillage and fertilization is shown. In order to better show the distribution of fertilizer in the furrow, the post-processing Clipping function in EDEM software was used to intercept the bottom operation effect diagram of one side of the furrow. When t = 2.2 s, the fertilizer shovel followed the rotary blade group for fertilization, and at the same time, the groove wheel rotated so that the fertilizer fell into the soil, with the fertilizer shovel acting on the seedbed soil. When t = 4.4 s, further double-wing shovels followed the rotary blade group and fertilization operation to ridge and furrow the soil above the deep-applied fertilizer and ensure that the strip fertilizer was within the range of 60 mm~90 mm from the bottom of the furrow. When t = 6.2 s, the simulation of mechanized double-ridge tillage and fertilization operation was completed. The fertilizer is evenly distributed under the soil at the bottom of the ridge and furrow, which meets the requirements of crop growth, ensures the distance between the fertilizer and the ridge and furrow, and avoids the phenomenon of burning seedlings and burning seeds in the later stage.

Figure 12 shows the tillage process and the distribution of fertilizer in the furrow from different perspectives under the optimal working parameters of the ridge and fertilization device of the whole-film double-ridge and furrow combined machine. The small ridge height h₁ is between 152 mm and 157 mm, the large ridge height h₂ is between 140 mm and 145 mm, and the fertilization depth h₀ is between 73 mm and 86 mm, as shown in Figure 12d.

The simulation results showed that the average qualified rate of seedbed tillage was 93.6%, and the average qualified rate of fertilization was 92.1%, which was significantly higher than that before optimization. The optimized operation parameters can improve the quality of ridging and fertilization, increase the subsequent excavation depth of the furrow, reduce the disturbance to the seedbed soil, improve the tillage quality and fertilization quality of the special-shaped double ridge, and meet the requirements of the agronomic cultivation technology of the whole-film double ridge-furrow sowing. Therefore, the established regression model is reliable.

4. Field Experiment

Through the previous simulation optimization research, the operation performance of the double-ridge tillage and fertilization operation of the whole-film double ridge-furrow ridge planting combined operation machine under the optimal structure device was further verified. The experiment was carried out in the experimental field of Taohe Tractor Manufacturing Co., Ltd., Lintao County, Dingxi City, Gansu Province, as shown in Figure 13. The soil in the test site is loessial soil, with water content of 16.9%, soil bulk density of 1300 kg/m³, and solidity < 0.20 MPa. The field surface is flat and loose, and there are few previous crops. According to the NY/T 986-2006 film mulching machine operation quality [24] and DB62/T 1935-2010 full film double furrow film mulching machine operation rules and operation quality acceptance [25] standard method, the test was carried out. After the completion of the combined machine operation, 15 m was randomly selected for determination, and the area was divided into 5 determination areas, on average. The average value of the determination area was used as the actual test result. The fertilization result is shown in Figure 14. The qualified rate of fertilization was 90.3%, and the qualified rate of seedbed tillage was 91.60%.

5. Conclusions

(1)

In this study, the AquaCrop model driven by water in the early stage of the team was used to simulate the two planting patterns of maize in rain-fed agriculture in the arid area of Northwest China from 2016 to 2020. The results showed that in the dry and wet years, the soil profile water content, yield, aboveground biomass, and water productivity of the ridge planting pattern were significantly higher than those of the flat planting pattern, and the drought resistance of the ridge planting pattern was more significant in the dry year.

(2)

On the basis of the team’s previous research, this study will further optimize the selection of the motion parameters of the combined device. Taking the qualified rate of seedbed tillage and the qualified rate of fertilization as the indexes, and the forward speed of the combined machine, the speed of the groove wheel of the fertilizer discharger, and the depth of rotary tillage as the research objects, the response surface method is used to systematically analyze the three factors. When the forward speed of the combined machine is 0.5 m/s, the speed of the groove wheel of the fertilizer discharger is 40 rmp, and the depth of rotary tillage is 150 mm, the qualified rate of seedbed tillage is the highest at 92.4%, and the qualified rate of fertilization is the highest at 93.2%.

(3)

The key components were tested by the Box–Behnken center combination test design principle, and the optimal parameter combination was obtained. The forward speed of the machine was 0.50 m/s, the rotation speed of the groove wheel of the fertilizer discharger was 39 rmp, and the rotary tillage depth was 150 mm. At this time, the simulation test results showed that the qualified rate of seedbed tillage was 93.6%, and the qualified rate of fertilization was 92.1%. The comparison between the field experiment and the simulation optimization simulation results showed that the average qualified rate of fertilization was 90.3%, which was 1.8% lower than the simulation results, and the average qualified rate of seedbed tillage was 91.6%, which was 2.0% lower than the simulation results. Comparing the simulation results with the actual working conditions, it is found that the results are not much different, which verifies the correctness of the simulation test and the structural model and shows that it is reasonable to carry out the analysis of the double-ridge tillage and fertilization operation process based on the discrete element method.

The AquaCrop model was used to simulate the two planting patterns of maize in the arid region of Northwest China. The analysis showed that the whole-film double ridge-furrow sowing technology had strong adaptability. In order to promote the application of this technology, it is necessary to optimize the parameters of key components of ridge fertilization, provide technical support for the construction of a full-film double ridge-furrow seedbed, realize the combination of agricultural machinery and agronomy, and have certain guidance for the improvement of maize full-film double ridge-furrow sowing agronomy.