Agronomic Experiments and Analysis of Garlic Mechanization-Friendly Cultivation Patterns in China

Abstract

Given the problem that traditional garlic cultivation patterns in China have difficulty in achieving comprehensive mechanized production, an experimental investigation on mechanization-friendly cultivation agronomy was conducted. In this study, an orthogonal experimental method was used to conduct continuous tracking experiments for three years in three major garlic production regions of China. All the experiments were used to verify the impacts of sprout orientation, planting mode, planting density, and row spacing on garlic bulb yield per hectare. For every impact, nine experiments were processed. The results indicated the following: (1) planting density influenced the garlic bulb yield per hectare extremely significantly, followed by row spacing, planting pattern, and sprout orientation; (2) the combination of sprout orientation (1–45°), planting pattern (large ridge), a planting density (42.75)/10,000 plants per hectare, and row spacing (26 + 10) led to the largest garlic bulb yield per hectare, which means this combination was the best form of cultivation agronomy. This study will provide a valuable reference for China’s farmland suitability for agricultural machinery operation (FSAM) production program.

1. Introduction

Garlic belongs to the onion family, Alliaceae, and is known as Allium sativum botanically. Garlic contains various phytochemicals [1,2]. Garlic has been regarded as a potential therapeutic and medicinal plant throughout most of human civic history [3,4]. According to “Farm Bee: Analysis Report on China’s Garlic Industry in 2025” [5], statistics show that garlic is cultivated in more than 130 countries, with a total area of more than 1.7 million hectares and annual production of more than 28 million tons, and was one of the major vegetable crops in 2023 [3]. The garlic planting area of China accounts for approximately 50% of the world’s total planting area, and its output accounts for about 72% of the world’s total output, enjoying a reputation as “the world’s garlic capital.” Recent data indicate that the planted area of garlic in China is about 0.8 million hectares [2].

However, the technical level of mechanized garlic harvesting in China is low. Garlic is primarily harvested by hand, with mechanized harvest areas of <5%, which restricts the development of the garlic industry in China [3,6]. The main challenges include the following: (1) the inability of existing technologies to meet the stringent agronomic requirements of sowing, with ≥95% of the sprout being upward–oriented [7]; (2) the high planting densities required (26,000–36,000 plants per mu) [8,9]; (3) narrow ridges and ditches, which are incompatible with tractor operations during field management and harvesting; and (4) the inability of harvesting machinery to adapt to dense planting patterns, small ridge–ditch systems, and plastic mulch cultivation practices [10,11].

In recent years, with the aging of garlic farmers in the main garlic-producing areas, the cost of manual work has increased exponentially, and the dilemma of inorganic availability and organic difficulties have ensured that garlic production costs have remained high, hindering the serious sustainable development of the industry [12,13]. To maintain the healthy and orderly development of the garlic sector, it is necessary to carry out regionalization of agro-mechanical and agro-technical integration of the mechanism of production research in order to guarantee the creation of a mechanized garlic production model [14,15]. Research indicates that using the ridge tillage pattern for garlic could facilitate fully mechanized production, while mechanized garlic cultivation could reduce cost and increase farmers’ income. Based on the developmental requirements of mechanized garlic sowing and harvesting, we propose two ridge tillage patterns: narrow-ridge and wide-ridge systems. Leveraging existing mechanization technologies, both patterns have demonstrated the ability to achieve comprehensive mechanization throughout the entire production cycle [16,17].

In conclusion, to solve the problem of the traditional garlic cultivation mode in China having difficulty achieving comprehensive mechanized production, an experimental investigation on mechanization-friendly cultivation agronomy was conducted. First, an orthogonal experimental method was used to conduct continuous tracking experiments for three years in three major garlic production regions of China to verify the impacts of sprout orientation, planting mode, planting density, and row spacing on garlic bulb yield per hectare. Then, we analyzed the effect of garlic shoot orientation, planting pattern, planting density, and planting row spacing on garlic bulb yield per hectare. The results of this paper will provide a reference for the complete mechanized production of garlic.

2. Materials and Methods

2.1. Experimental Sites and Data Sources

Jinxiang County, Jinan City, and Pizhou City in Shandong Province, China, were selected as the experiment sites, since they are the main garlic-producing regions in China. The cultivated areas of Jinxiang County, Jinan City, and Pizhou City are 120,000 hectares, 100,000 hectares, and 150,000 hectares, respectively [18]. All the experiments were conducted at the three experiment sites, and the data were obtained from actual measurements at the three experiment sites. The experiment times were throughout the harvesting seasons in 2022, 2023, and 2024.

2.2. Experimental Materials and Methods

Jinxiang purple skin garlic (Jinxiang County), Jinan barley garlic (Jinan City), and Xu Garlic 917 garlic (Pizhou City) were chosen as the experimental materials, since these cultivars are the main garlic cultivars cultivated in the main garlic–producing areas. We chose row spacing, planting pattern, planting density, and sprout orientation as the factors influencing garlic bulb yield per hectare. The factors and the levels used in this study are listed in

Table 1. Summary of factor levels.

Level	Sprout Orientation	Planting Pattern	Planting Density/10,000 Plants per Hectare	Row Spacing/cm
1	0–45° facing up	Ridge cropping	36.75	18/22 + 14/26 + 10
2	45–90° facing up	Small ridge	39.75	18/22 + 14/26 + 10
3	90°	Large ridge	42.75	18/22 + 14/26 + 10

.

Each planting pattern was implemented with three row spacings: 18 cm, (22 + 14) cm, and (26 + 10) cm. The 18 cm row spacing represents an equidistant row planting pattern, where all row spacing is uniformly spaced 18 cm apart. The (22 + 14) cm and (26 + 10) cm configurations correspond to wide–narrow row planting patterns, with alternating wide and narrow row spacings of 22 cm/14 cm and 26 cm/10 cm, respectively. Figure 1 shows a schematic diagram of row spacing. To ensure the row spacing during the planting, a custom-made furrow divider (similar to a comb) was employed, and the number and the spacing of the furrow could be adjusted according to the actual production demands. The divided created well-defined furrows on the seeding bed while maintaining the specified row spacing configurations throughout the planting process.

Figure 2 shows the sprout orientation, where a is the angle between the line connecting the garlic sprout to the root and the vertical direction of the ground. Here, a = 0° corresponds to vertical sowing (sprout pointing straight upward), while a = 90° corresponds to horizontal sowing (sprout parallel to the ground). When 0° < a < 45°, it indicates that the garlic is sowed nearly vertically, with the sprout facing upwards; when 45° ≤ a < 90°, it indicates that the garlic is tilted upward. All orientations fall within the range of ±90°, and the difference between positive and negative angles is negligible for garlic growth, so we classify angles by their absolute values [19]. Notably, orientations where 90° < a < 180° (sprout facing downward) severely hindered the yield and were excluded from consideration in this study.

The experiment was conducted annually at each experiment site according to the L9(3⁴) orthogonal experimental design. To ensure statistical reliability, the experimental layout was arranged in a randomized block design with three sequential replications. During the experiments, each experiment plot maintained a minimum length of 5 m. The orthogonal experiment design matrix is shown in

Table 2. The complete orthogonal experiment design matrix.

Level	Sprout Orientation	Planting Pattern	Planting Density/10,000 Plants per Hectare	Row Spacing/cm
1	0–45°	Ridge cropping	36.75	18
2	0–45°	Small ridge	39.75	22 + 14
3	0–45°	Large ridge	42.75	26 + 10
4	45–90°	Ridge cropping	39.75	26 + 10
5	45–90°	Small ridge	42.75	18
6	45–90°	Large ridge	36.75	22 + 14
7	90°	Ridge cropping	42.75	22 + 14
8	90°	Small ridge	36.75	26 + 10
9	90°	Large ridge	39.75	18

.

2.3. Cultivation Mode

The ridge planting pattern is shown in Figure 3. For precise field preparation, a tractor with a navigation system (navigation accuracy: ±2.5 cm/km) was employed to tow the machinery for building ridges or digging ditches to form the bed.

The small ridge planting pattern is shown in Figure 4.

The big ridge pattern of planting is shown in Figure 5.

The planting density can be described as follows:

$$\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{d}\mathrm{e}\mathrm{n}\mathrm{s}\mathrm{i}\mathrm{t}\mathrm{y}={\displaystyle \frac{\mathrm{n}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{r}\mathrm{o}\mathrm{w}\mathrm{s} (\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{i}\mathrm{n} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{w}\mathrm{i}\mathrm{d}\mathrm{t}\mathrm{h} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{b}\mathrm{o}\mathrm{r}\mathrm{d}\mathrm{e}\mathrm{r} \mathrm{A}) \times \mathrm{10,000}}{\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t} \mathrm{s}\mathrm{p}\mathrm{a}\mathrm{c}\mathrm{i}\mathrm{n}\mathrm{g} \times \mathrm{A}}}$$

(1)

where the plant spacing is m.

2.4. Experimental Indicators

Garlic bulb yield per hectare served as the evaluation indicator. The measurement procedure was as follows. (1) We identified three representative districts exhibiting uniform growth patterns and ensured selected areas reflected overall field conditions; (2) 1 m² in each selected district was positioned as sampling to measure and calculate the garlic bulb yield per hectare.

2.5. Statistical Product and Service Solutions (SPSS)

Experimental data were analyzed using IBM SPSS Statistics 22, and the p value was used to evaluate the significance of the influencing factors on the garlic bulb yield per hectare. We assumed the following: (1) p < 0.01 means the influencing factors affected the experiment indicator highly significantly; (2) 0.01 < p < 0.05 means the influencing factors affected the experiment indicator significance; and (3) p > 0.05 means the experiment indicator was insignificant to the influencing factors.

3. Results and Discussion

The complete experimental results from the field trials conducted in Jinxiang County (2021–2024), Jinan City (2021–2024), and Pizhou City (2021–2024) are shown in Appendix A: Dataset. The orthogonal experimental design employed the K value and R value as two key parameters for evaluation of the results. In Appendix A, numeric codes 1, 2, and 3 correspond to the predefined factor levels detailed in Table 1; the K₁, K₂, and K₃ values are the sum of the experimental outcomes for all trials at each respective level; the $\overline{K_1}$, $\overline{K_2}$, and $\overline{K_3}$ values represent the average of the K₁, K₂, and K₃ values, respectively; and the R value quantifies the dispersion of a factor’s effects across its tested levels, that is, the difference between the corresponding maximum $\overline{K}$ value and the minimum $\overline{K}$ value of that factor. The R value quantitatively characterizes the magnitude of effect variation induced by the given factor across its tested levels in the experimental system.

3.1. Analysis Results of the Importance of Four Factors

As determined from all nine experiments, the relative importance of the four influencing factors is shown in Figure 6.

The results presented in Figure 6 demonstrate that among the four experimental factors, planting density exerted the most significant influence of all the nine experiments, followed by row spacing, planting pattern, and sprout orientation. To optimize cultivation agronomy for mechanized farming, the primary emphasis should be placed on controlling planting density and row spacing, while sprout orientation and planting pattern may be considered secondary factors.

Based on the dataset provided in Appendix A, experimental results from eight trials revealed significant variations in garlic bulb yield per hectare across different practices. The largest garlic bulb yield per hectare was achieved with serial no 3, characterized by sprout orientation (0–45°), planting pattern (large ridge), planting density (42.75)/10,000 plants per hectare, and row spacing (26 + 10). The combination consistently outperformed other treatments, indicating its superiority as an optimal cultivation strategy for maximizing garlic production. Conversely, the lowest yield was observed with serial no 6, which featured sprout orientation (45–90°), planting pattern (large ridge), planting density (36.75)/10,000 plants per hectare, and row spacing (22 + 14). These findings suggest that this particular combination represents the least favorable agronomic approach among the tested variables.

3.2. Jinxiang County Experimental Results and Discussion

(1) The analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2021–2022) are shown in

Table 3. The analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2021–2022).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected Model	7,708,459.852a	8	963,557.481	5.780	<0.01
Intercept	15,205,234,823.148	1	15,205,234,823.148	91,215.416	<0.01
Sprout orientation	708,344.963	2	354,172.481	2.125	0.148
Planting pattern	582,156.074	2	291,078.037	1.746	0.203
Planting density	516,3701.407	2	2,581,850.704	15.488	<0.01
Row spacing	1,254,257.407	2	627,128.704	3.762	0.043
Error	3,000,526.000	18	166,695.889
Total	15,215,943,809.000	27
Corrected Total	10,708,985.852	26

. The results reveal that the planting density exerted a highly significant effect on the garlic bulb yield per hectare (p < 0.01), and the row spacing demonstrated a significant effect on the garlic bulb yield per hectare (p < 0.05). In contrast, neither sprout orientation nor planting pattern was shown significantly influence to garlic bulb yield per hectare (p > 0.05).

(2) The analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2022–2023) are shown in

Table 4. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2022–2023).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	12,290,970.667a	8	1,536,371.333	17.882	<0.01
Intercept	16,080,283,681.333	1	16,080,283,681.333	187,158.980	<0.01
Sprout orientation	103,0496.222	2	515,248.111	5.997	<0.01
Planting pattern	1,790,267.556	2	895,133.778	10.418	<0.01
Planting density	7,694,392.889	2	3,847,196.444	44.778	<0.01
Row spacing	1,775,814.000	2	887,907.000	10.334	<0.01
Error	1,546,520.000	18	85,917.778
Total	16,094,121,172.000	27
Corrected total	13,837,490.667	26

. The results indicate that all four examined factors (planting density, row spacing, planting pattern, and sprout orientation) exerted highly significant effects on garlic bulb yield per hectare (p < 0.01).

(3) The analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2023–2024) are shown in

Table 5. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinxiang County (2023–2024).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	9,420,364.000a	8	1,177,545.500	8.668	<0.01
Intercept	15,864,013,445.333	1	15,864,013,445.333	116,782.322	<0.01
Sprout orientation	767,968.222	2	383,984.111	2.827	0.086
Planting pattern	306,148.667	2	153,074.333	1.127	0.346
Planting density	7,443,396.222	2	3,721,698.111	27.397	<0.01
Row spacing	902,850.889	2	451,425.444	3.323	0.059
Error	2,445,166.667	18	135,842.593
Total	15,875,878,976.000	27
Corrected total	11,865,530.667	26

. The results show that planting density significantly influenced the garlic bulb yield per hectare (p < 0.01). In contrast, row spacing, garlic shoot orientation, and planting pattern had no significant influence on yield (p > 0.05).

3.3. Jinan City Experimental Results and Analysis

(1)

Table 6. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinan City (2021–2022).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	8,315,554.000a	8	1,039,444.250	13.755	<0.01
Intercept	12,499,849,301.333	1	12,499,849,301.333	165,411.127	<0.01
Sprout orientation	95,293.556	2	47,646.778	0.631	0.544
Planting pattern	944,256.889	2	472,128.444	6.248	<0.01
Planting density	6,495,209.556	2	3,247,604.778	42.976	<0.01
Row spacing	780,794.000	2	390,397.000	5.166	0.017
Error	1,360,230.667	18	75,568.370
Total	12,509,525,086.000	27
Corrected total	9,675,784.667	26

presents the analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinang City (2021–2022). The results revealed significant variations in the response of garlic bulb yield per hectare to different cultivation factors. Specifically, both planting density and planting pattern demonstrated highly significant effects on garlic bulb yield per hectare (p < 0.01), while row spacing had a significant impact (p < 0.05). In contrast, the sprout orientation had no significant influence (p > 0.05).

(2)

Table 7. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinan City (2022–2023).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	7,466,365.852a	8	933,295.731	14.726	<0.01
Intercept	12,530,248,981.481	1	12,530,248,981.481	197,705.446	<0.01
Sprout orientation	813,223.185	2	406,611.593	6.416	<0.01
Planting pattern	463,902.741	2	231,951.370	3.660	0.046
Planting density	4,891,137.185	2	2,445,568.593	38.587	<0.01
Row spacing	1,298,102.741	2	649,051.370	10.241	<0.01
Error	1,140,810.667	18	63,378.370
Total	12,538,856,158.000	27
Corrected total	8,607,176.519	26

presents the analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinan City (2022–2023). The results reveal that sprout orientation, planting density, and row spacing all exerted highly significant effects on garlic bulb yield per hectare (p < 0.01). In comparison, the planting pattern had no significant effect on the garlic bulb yield per hectare (p < 0.05).

(3)

Table 8. Analysis of variance (ANOVA) results from the orthogonal experiments conducted in Jinan City (2023–2024).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	8,840,942.667a	8	1,105,117.833	10.837	<0.01
Intercept	12,368,130,208.333	1	12,368,130,208.333	121,281.809	<0.01
Sprout orientation	505,397.556	2	252,698.778	2.478	0.112
Planting pattern	960,678.222	2	480,339.111	4.710	0.023
Planting density	5,918,358.222	2	2,959,179.111	29.018	<0.01
Row spacing	1,456,508.667	2	728,254.333	7.141	<0.01
Error	1,835,612.000	18	101,978.444
Total	12,378,806,763.000	27
Corrected total	10,676,554.667	26

presents the analysis of variance (ANOVA) results from the orthogonal experiment conducted in Jinan City (2023–2024). The results show that the planting density and row spacing exhibited highly significant effects on the garlic bulb yield per hectare (p < 0.01); the planting pattern had a significant effect on the garlic bulb yield per hectare (p < 0.05), and sprout orientation did not demonstrate any significant impact on yield (p > 0.05).

3.4. Pizhou Experimental Results and Analysis

(1) ANOVA results from the Pizhou City (2021–2022) orthogonal experiment (

Table 9. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Pizhou City (2021–2022).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected Model	7,696,790.074a	8	962,098.759	18.723	<0.01
Intercept	14,280,746,088.926	1	14,280,746,088.926	277,908.218	<0.01
Sprout orientation	396,583.185	2	198,291.593	3.859	0.040
Planting pattern	611,642.296	2	305,821.148	5.951	<0.01
Planting density	5,522,556.963	2	2,761,278.481	53.735	<0.01
Row spacing	1,166,007.630	2	583,003.815	11.345	<0.01
Error	924,958.000	18	51,386.556
Total	14,289,367,837.000	27
Corrected Total	8,621,748.074	26

) demonstrate the highly significant effects of planting density, planting pattern, and row spacing on the yield of garlic hectare (p < 0.01), with the sprout orientation showing no significant influence on the garlic bulb yield per hectare (p < 0.05).

(2) The ANOVA results of the Pizhou City (2022–2023) orthogonal experiment (

Table 10. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Pizhou City (2022–2023).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	10,214,468.667a	8	1,276,808.583	16.879	<0.01
Intercept	14,143,685,381.333	1	14,143,685,381.333	186,978.885	<0.01
Sprout orientation	273,200.667	2	136,600.333	1.806	0.193
Planting pattern	289,860.222	2	144,930.111	1.916	0.176
Planting density	8,065,174.222	2	4,032,587.111	53.311	<0.01
Row spacing	1,586,233.556	2	793,116.778	10.485	<0.01
Error	1,361,578.000	18	75,643.222
Total	14,155,261,428.000	27
Corrected total	11,576,046.667	26

) identified planting density and row spacing as highly significant determinants of the garlic bulb yield per hectare (p < 0.01), while planting pattern and sprout orientation had insignificant effects on garlic bulb yield per hectare (p > 0.05).

(3) The ANOVA results of the Pizhou City (2023–2024) orthogonal experiment (

Table 11. Analysis of variance (ANOVA) results from the orthogonal experiment conducted in Pizhou City (2023–2024).

Source	Type III Sum of Squares	df	Mean Square	F-Value	p Value
Corrected model	8,099,293.333a	8	1,012,411.667	13.488	<0.01
Intercept	14,141,213,633.333	1	14,141,213,633.333	188,404.467	<0.01
Sprout orientation	99,220.667	2	49,610.333	0.661	0.528
Planting pattern	1,528,297.556	2	764,148.778	10.181	<0.01
Planting density	5,729,548.222	2	2,864,774.111	38.168	<0.01
Row spacing	742,226.889	2	371,113.444	4.944	0.019
Error	1,351,039.333	18	75,057.741
Total	14,150,663,966.000	27
Corrected total	9,450,332.667	26

) demonstrate the highly significant effects of planting density and planting pattern on garlic bulb yield per hectare (p < 0.01), with row spacing showing a significant effect on the garlic bulb yield per hectare (p < 0.05). In comparison, the sprout orientation had no significant effect (p > 0.05).

4. Conclusions

This study employed an orthogonal experimental design to systematically evaluate the effects of four key cultivation factors: sprout orientation, planting mode, planting density, and row spacing, on garlic bulb yield per hectare. We reached the following conclusions.

(1) Among the investigated factors, planting density exerted an extremely significant effect on the garlic bulb yield per hectare, followed by row spacing, planting pattern, and sprout orientation, in descending order of statistical significance.

(2) The highest garlic bulb yield per hectare was achieved under the following conditions: sprout orientation (0–45°), planting pattern (large ridge), planting density (42.75)/10,000 plants per hectare, and row spacing (26 + 10). This combination represents the most effective form of cultivation agronomy for maximizing garlic production.

(3) The lowest garlic bulb yield per hectare resulted from sprout orientation (45–90°), planting pattern (large ridge), planting density (36.75)/10,000 plants per hectare, and row spacing (22 + 14), and this combination led to the worst form of cultivation agronomy. These parameters should be avoided in commercial garlic cultivation.

(4) For mechanized garlic cultivation, maintaining adequate sowing density is essential. The ridge row spacing pattern demonstrates superior performance and should be preferentially adopted. Additionally, the practice of upward-oriented garlic bud sowing should be avoided in mechanized systems.