Effect of Different Potassium Fertilizer Application Rates on the Yield and Potassium Utilization Efficiency of Maize in Xinjiang, China

Abstract

Potassium (K) is crucial for global maize (Zea mays L.) production, yet the issue of “high K fertilizer input but low utilization efficiency” in K-rich soils of Xinjiang remains underexplored. A three-year field experiment (2020, 2021, 2024) in Xinjiang evaluated the effects of reduced K application on maize growth, grain yield (GY), and K-use efficiency. Five treatments were tested: K100 (136.0 kg K₂O·ha⁻¹), K60 (83.5 kg K₂O·ha⁻¹), K40 (55.6 kg K₂O·ha⁻¹), K0 (no K), and CK (no fertilizer). The research shows that K60 significantly outperforms K100 in terms of physiological parameters (plant height + 2.7–34.7%, leaf area index (LAI) + 6.3–26.8%, dry matter + 22.0–28.8%); GY and thousand kernel weight (TKW) improved by 6.9–15.1% and 9.3–30.3%, respectively. The potassium fertilizer productivity (PFP_K) and potassium fertilizer agronomic efficiency (AE_K) increased by 78–112.3% and 176.4–2085% compared to the K100. During the three-year period, the maximum net income of K60 reached 28,206 CNY·ha⁻¹, which was 18.9–20.7% higher than that of K100. Regression analysis identified an optimal K rate of 82.2–85 kg·ha⁻¹ for maximum yield. Least squares structural equation mode (PLS-SEM) and correlation analyses revealed that moderate K reduction enhanced vegetative growth and optimized yield structure, indirectly boosting yield, thereby directly driving net income. Thus, reducing K input can achieve “lower input with higher efficiency”, offering a practical basis for optimizing K management in arid-region maize systems.

1. Introduction

Potassium (K) is one of the three primary macronutrients essential for crop growth and plays a critical physiological role in agricultural production [1,2,3]. Maize (Zea mays L.) is a K-demanding crop whose growth and development are heavily dependent on adequate K supply [4,5,6]. K activates key enzymes such as starch synthase, facilitating the translocation of photosynthates to developing grains, thereby significantly influencing thousand kernel weight (TKW) and final yield [5,7,8]. Moreover, sufficient K nutrition enhances stem mechanical strength and reduces lodging risk, particularly during the jointing to grain-filling stages [9]. However, in current agricultural practice, K fertilizer is often applied excessively in pursuit of high yields [10,11,12]. Such over-application not only wastes finite K resources but also triggers a range of ecological and agronomic problems [13]. For instance, long-term application of K fertilizer at rates exceeding 62.5 kg·ha⁻¹ in North China has been shown to decrease crop yield, reduce K use efficiency, and deplete soil available K and organic matter [14]. To address these challenges, modern technologies such as drip irrigation combined with fertilization offer effective strategies to improve resource use efficiency [15,16]. Qu et al. [17]. reported that drip irrigation can increase K fertilizer use efficiency by 14.2% compared to conventional irrigation methods. By adopting such precision nutrient management approaches, we are able to substantially reduce fertilizer waste, mitigate environmental pollution, and lower production costs in maize cultivation.

However, with the development of drip irrigation technology, many farmers still adhere to traditional fertilization concepts and fail to adjust the application rate of K fertilizer in accordance with the crop growth [15,16,18,19]. This contradiction is particularly prominent in regions such as Xinjiang, where the soil background value of K content is relatively high (1.99% in the 0–20 cm depth) [20]. In this region, the previously applied K rate often exceeds the actual needs of crops. This continuous excessive fertilization exacerbates the waste of resources and the adverse impact on soil; for instance, the excessively applied K fertilizer could be fixed by soil colloids or lost via leaching [21,22,23]. Moreover, it inhibits the absorption of other nutrients by crops through mechanisms such as ion antagonism, ultimately affecting the normal growth and yield formation of maize [2]. Additionally, there is ample research on reducing the application of nitrogen and phosphorus [24,25,26,27], but scarce research exists on the optimal rate of K fertilizer in the drip irrigation system of maize in Xinjiang. Therefore, clarifying the effect of decreasing K fertilizer application in this area is of great theoretical and practical significance for achieving the goal of “reducing fertilizer application without reducing yield” in this maize production area.

This study proposes the hypothesis that a moderate reduction in the use of K fertilizer will not significantly affect plant growth and maize yield. To test this hypothesis, we conducted a three-year replicated field experiment: (1) to explore the effects of different degrees of K fertilizer reduction on maize growth, yield components, and K fertilizer utilization efficiency; (2) to determine the optimal application threshold of K fertilizer using the yield-economic benefit model in Xinjiang, and to provide a quantitative basis for the formulation of precise fertilizer management strategies in this arid region.

2. Materials and Methods

2.1. Study Site

Field experiments were conducted in 2020, 2021, and 2024. In 2020 and 2021, the experiments were located in the Xinjiang Agricultural Reclamation Academy’s Crop Water Use Efficiency Research Station (45°38′ N, 86°09′ E) in Shihezi City, on a piedmont alluvial plain at the northern foot of the Tianshan Mountains, with a typical temperate continental climate. In 2024, the experiment was conducted in the Cocodala of Ili River Valley (80°61′ E, 43°75′ N), which is also characterized by a temperate continental climate similar to that of Shihezi. The specific climatic conditions and soil properties of both sites are presented in Table 1.

Table 1. Climatic conditions and soil properties of experiment sites in Shihezi and Cocodala.

Experiment Sites	Temp (°C)	Rainfall (mm)	ET (mm)	pH	OM (g·kg−1)	AP (mg·kg−1)	AK (mg·kg−1)	AN (mg·kg−1)
Shihezi	7.2	115	1942	8.73	7.14	12.20	130.50	34.30
Cocodala	10.0	200	2250	8.81	5.50	13.03	291.75	21.32

Note: Temp represented temperature, ET represented evapotranspiration, OM represented volume weight of soil, AP represented rapid available phosphorus, AK represented rapidly available potassium, AN represented available nitrogen.

2.2. Materials

The maize variety of this experiment was ZD985 (green maize), which was provided by Beijing Denong Seed Technology Co., Ltd. (Beijing, China). The used commercial fertilizers including: urea (N ≥ 46.4%, granular; Xinjiang Xinlianxin Co., Ltd., Changji, China), monoammonium phosphate (N ≥ 12%, P₂O₅ ≥ 61%, powder; Guizhou Kai Phosphorus Group Co., Ltd., Guizhou, China), and potassium sulfate (K₂O ≥ 51%, granular; Xinjiang Lop Nur Potassium Salt Co., Ltd., Ürümqi, China).

The source of the irrigation water was a deep well with a depth of 100 m; the salinity of the water was 0.2–0.3 g·L⁻¹. The type of drip irrigation belt was a single-wing labyrinth drip irrigation belt (WDF16/2.6–100) produced by Xinjiang Tianye Company (Shihezi, China). The wall thickness was 0.18 mm, inner diameter of 16 mm, drip hole spacing of 300 mm, rated flow of 2.0 L·h⁻¹, and the working pressure of 0.1–0.15 MPa. The pressure differential fertilizer applicator was produced by Laiwu Fenghuaxingnong Water-saving Irrigation Equipment Co., Ltd. (Jinan, China).

2.3. Experimental Design

In this experiment, both sites in Shihezi and Cocodala employed a randomized complete block design with three replications. The five K fertilizer treatments were as follows: 100% K (136.0 kg K₂O·ha⁻¹, K100, this implies the conventional K application rate by local farmers), 60% K (83.5 kg K₂O·ha⁻¹, K60), 40% K (55.6 kg K₂O·ha⁻¹, K40), 0% K (K0) and no fertilizer (Control, CK). Except for CK, the application rates of the other treatments (including K0) were the same, at 419.3 kg·ha⁻¹ for N and 166.3 kg·ha⁻¹ for P₂O₅. The 15 plots were separated from adjacent plots by 2.2 m-wide isolation strips, and each plot (110 m²) was 20 m long and 5.5 m wide. The irrigation and fertilization levels in each growth period are shown in Table 2. Maize sowing, harvesting, and sampling time are shown in Table 3.

Table 2. The irrigation volume and fertilization rate of experiment sites during maize growth stages.

Treatment		VE	V6	V8	V12	VT	R1	R2	R3	R6	Total
N (kg·ha−1)		0	65.7	71.2	75.4	71.2	54.6	44.8	36.4	0	419.3
P2O5 (kg·ha−1)		0	27.8	33.2	33.2	33.2	16.7	11.1	11.1	0	166.3
K2O (kg·ha−1)	K100	0	15.5	23.1	23.1	27.8	19.4	15.5	11.6	0	136.0
	K60	0	9.3	13.9	13.9	18.6	11.6	9.3	6.9	0	83.5
	K40	0	6.2	9.2	9.2	12.4	7.8	6.2	4.6	0	55.6
	K0	0	0	0	0	0	0	0	0	0	0
Irrigation Volume (m3·ha−1)		310	580	580	580	580	580	580	520	490	4800

Note: VE represented maize emergence stage, V6 represented maize sixth leaf stage, V8 represented maize eighth leaf stage, V12 represented maize twelfth leaf stage, VT represented maize tasseling stage, R1 represented maize silking stage, R2 represented maize silking stage, R3 represented maize milk stage, R6 represented maize physiological maturity stage.

Table 3. Maize sowing, harvesting, and sampling time.

Years	Sowing Date	Harvest Date	Flowering Stage	Maturity Stage
2020	26th April	1st October	15th July	2nd September
2021	7th May	24th September	19th July	27th August
2024	9th April	23rd September	6th July	23rd August

This experiment used the subsurface drip irrigation method. A combined seeder performed three synchronized operations: (1) laying drip tapes, (2) applying plastic film mulch, and (3) sowing maize seeds. Drip tapes were spaced 110 cm apart, and each plot had independent water meters and fertilizer tanks for precise irrigation and fertilization control. Maize was planted in alternating wide–narrow rows (80 cm wide, 30 cm narrow), achieving a target density of 1.26 × 10⁵ plants·ha⁻¹ with a within-row spacing of 14.4 cm (Figure 1).

Figure 1. Schematic diagram of cultivation mode for maize.

2.4. Data Collection

2.4.1. Plant Height

During the flowering stage of maize, the height of 10 maize plants was measured from the soil surface to the top of the male inflorescence, and then which were calculated the average value of plant height [28].

2.4.2. Leaf Area Index (LAI)

During the flowering stage, the 10 maize plants with consistent growth conditions were selected in each plot and the lengths and widths of their leaves were measured. The related parameters were calculated as follows [29]:

LA_P = ∑ (L × B) × 0.75

(1)

LAI = LA_P × N ÷ A_land

(2)

where ∑ represents the sum of leaf areas, L is leaf length, B is leaf width, LA_P is leaf area per plant, N is number of plants per unit area, A_land is unit land area.

2.4.3. Dry Matter

Aboveground biomass (leaves, stems, and reproductive organs) was harvested at the flowering and maturity stages. The samples were dried in an oven at 105 °C for 30 min and then at 75 °C until they reached a constant weight, and were weighed and recorded on a balance with an accuracy of 0.01 [30].

2.4.4. Yield and Yield Composition

Yield was measured on 5 October 2020, 6 October 2021. and 3 October 2024, respectively. For each plot, 20 ears were randomly selected, weighed for fresh weight, then dried to constant weight and reweighed. Yield per unit area was calculated based on a standard moisture content of 14%. Meanwhile, the following yield-related traits were recorded: (1) Ear length: measured along the grain axis from the ear base to the tip using a vernier caliper; (2) Ear width: measured at the thickest part of the middle ear, perpendicular to the grain axis; (3) Rows per ear: counted as the total number of complete grain rows per ear; (4) Kernel number per row: counted as the number of complete grains from the base to the top of 2–3 randomly selected representative complete rows per ear, with the average value taken; (5) Thousand Kernel Weight (TKW): Three random sets of 1000 grains from this mixture were weighed. The mean value of these three measurements represented the plot’s TKW. Subsequently, the yield-determining factors were analyzed [31].

2.4.5. Fertilizer Agronomy Efficiency and Fertilizer Specific Productivity

The calculation formulas of fertilizer agronomic efficiency and fertilizer specific productivity were as follows [32]:

PFP_K = Y/KA

(3)

AE_K = (Y − Y0)/KA

(4)

where FPF_K represents the agronomic efficiency of K fertilizer, AE_K represents the partial productivity of K fertilizer, Y represents the grain yield of the K fertilizer application treatment, and Y0 represents the grain yield of the non- K fertilizer application plot. KA indicates the amount of K fertilizer applied per unit area.

2.4.6. Economic Benefit

The economic benefits of maize production were calculated as follows [33]:

GR = GY × P_g

(5)

SR = SW × P_S

(6)

NER = (GR + SR) − TC

(7)

where GR is grain revenue, GY is grain yield, Pg is grain price, SR is straw revenue, SW is straw fresh weight, Ps is straw price, NER is net economic return, TC is total production cost. Yuan stands for Currency of a country.

The grain price is 1.5 CNY·kg⁻¹ (average of three markets). Straw is priced at 0.35 CNY·kg⁻¹. Fertilizer N costs 2.2 CNY·kg⁻¹, fertilizer P costs 6.8 CNY·kg⁻¹, and fertilizer K costs 4.6 CNY·kg⁻¹. Other production costs, excluding fertilizers, are 11,850 CNY·ha⁻¹.

2.5. Data Analysis

A one-way ANOVA using IBM SPSS Statistics 27 was conducted to assess the significant impact levels of fertilizer application rates on yield components and growth indicators. The LSD test was used to examine the significance of mean values under each treatment at p < 0.05. Image mapping, data fitting, and calculation of the Spearman’s rank correlation coefficient (r) were performed using Origin Pro 2025. The potential relationships among fertilization, growth shape, yield and economy were identified using the Partial Least Squares Structural Equation Model (PLS-SEM) constructed by the “plspm” R package (R v3.4.0). Given the significant differences in climatic conditions and soil properties among the experimental sites in different years (Table 1), year was treated as a repeated validation factor in the statistical analysis to verify the consistency and stability of the effects of different potassium fertilizer application rates.

3. Results

3.1. Effects of Reduced K Fertilizer on Maize Growth Parameters

During a three-year trial period, both the plant height and leaf area index (LAI) of maize showed a trend of “first increase then decrease” as the amount of K fertilizer decreased (Figure 2). The K60 treatment showed the best growth performance in all treatments and experimental years. In 2020 and 2021, there was not any significant difference in the maize growth parameters (plant height and LAI) between the K60 and the K100 treatment. In 2024, these growth parameters in the K60 treatment were markedly higher than those of the K100, K40, K0 and CK treatments (p < 0.05). Specifically, in 2024, the plant height of K60 treatment (269.5 cm) was 19.7% higher than that of K100 treatment (212.1 cm), and the LAI of K60 treatment (6.0) was 20% higher than that of K100 treatment (4.8). The LAI in 2024 was the lowest of all the treatments in three years. Compared to the CK treatment in 2024, the relative increase in LAI was 82.1% in the K60 treatment and 43.6% in the K100 treatment; and similarly, compared with CK treatment in 2020 and 2021, the relative increase of LAI was 19.7–49.1% in the K60 treatment and 7.4–38.1% in the K100 treatment. These results indicate that, compared with CK treatment, the relative increase in the K60 treatment was significantly higher than that in the K100 treatment, and the 2024 K100 value was also significantly higher than in the previous two years (2020 and 2021). This experiment demonstrated that relative to conventional K application method (K100 treatment), moderate reduction in K fertilization rate could enhance the maize growth, and the reduced amount of 83.5 kg·ha⁻¹ (K60 treatment) may be the appropriate K fertilization rate.

Figure 2. Effect of potassium application rate on (a) plant height, and (b) leaf area index (LAI) of maize. Note: The error bars represent the standard error (SE), and different lowercase letters indicate significant differences among the various treatment methods for each indicator within the same year. All comparisons were determined to be significant at the p < 0.05 level by the LSD test.

3.2. Effect of Reduced K Fertilizer Application on the Accumulation and Distribution of Dry Matter in Maize

Dry matter (DM) is a critical indicator for assessing crop growth status and yield potential, and it is closely correlated with final economic yield. With decreasing K fertilizer application, the DM accumulation in the experimental field exhibited a parabolic trend, which was characterized by an initial increase followed by a decline (Figure 3). The application of K fertilizer has a significant impact on the accumulation and distribution of DM at each growth stage. At the flowering stage in 2020, K60 treatment totally accumulated 18,890 kg·ha⁻¹ of DM, which was 18.5% higher than that of the K100 treatment (p < 0.05). The DM of leaf and stem, respectively, reached 8174 kg·ha⁻¹ and 11,716 kg·ha⁻¹, and the sum accumulation of leaf and stem DM was significantly higher than other treatments. These results demonstrated that moderate reduction in K fertilizer may enhance the assimilation and accumulation of DM in vegetative organs.

Figure 3. Effect of potassium application rate on (a) 2020, (b) 2021, and (c) 2024 dry matter of maize. Note: different lowercase letters indicate significant differences between treatments for each index within the same growth period. All comparisons were considered significant at p < 0.05 in the LSD test unless noted.

At maturity, the total DM for the K60 treatment was 35,603 kg·ha⁻¹, with ear DM at 15,857 kg·ha⁻¹ (44.5% of the total), 28.8% higher than that of the K100 treatment. The K60 treatment thus showed a pronounced advantage in partitioning DM into reproductive organs, thus laying the foundation for high yield. The results of DM in 2020 were similar to those in 2021. In 2024, the total DM of K60 treatment reached 14,176 kg·ha⁻¹ at the flowering period, which was significantly increased by 64% compared to the K100 treatment. Additionally, the total DM of K60 treatment was 34,640 kg·ha⁻¹ at maturity, which was 25.9% higher than that of the K100 treatment.

In summary, the K60 treatment demonstrated a significant advantage over the K100 treatment in terms of DM accumulation. During the flowering stage, it significantly promoted the accumulation of photosynthetic products in leaves and stems, and it was more effective at translocating DM to the ear during the maturity stage.

3.3. Yield and Its Components

Over the three-year experiment, TKW and GY consistently ranked highest among all treatments (Table 4). In the Shihezi region in 2020, the K60 treatment achieved a TKW of 445.0 g, which was 13.3% higher than that of K100 (392.7 g), corresponding to a yield increase of 9.3% compared to K100. In 2021, the TKW of K60 in the same region reached 406.0 g, marking a 15.1% increase over K100 (352.8 g), with a synchronized yield increase of 16.2%. In 2024, in the Cocodala region, the K60 treatment recorded a TKW of 591.8 g, 6.9% higher than that of K100 (553.3 g), and the yield showed a significant increase of 30.3% compared to K100.

Table 4. Changes in maize yield and yield components under different K fertilizer treatments.

Area	Years	Treatment	Ear Length (cm)	Spike Width (cm)	Kernel Number Per Row	Row Number Per Ear	Thousand Kernel Weight (TKW) (g)	Grain Yield (kg·ha−1)
Shihezi	2020	CK	14.6 c	4.8 b	31.8 ab	15.1 ab	371.1 c	14,073 c
		K100	15.9 b	4.8 b	32.2 a	15.1 ab	392.7 bc	16,779 b
		K60	17.4 a	5.0 a	33.9 a	15.7 a	445.0 a	18,338 a
		K40	15.3 bc	4.8 b	33.0 a	14.9 ab	413.2 ab	16,645 b
		K0	14.7 c	4.7 b	29.5 b	14.2 b	374.1 c	14,534 c
	2021	CK	14.6 a	4.3 b	30.8 ab	13.8 a	352.8 b	10,799 b
		K100	14.9 a	4.5 ab	32.5 a	13.8 a	352.8 b	13,106 ab
		K60	15.7 a	4.6 a	32.5 a	14.3 a	406 a	15,205 a
		K40	14.9 a	4.6 a	31.5 ab	14.1 a	362.3 ab	12,946 b
		K0	14.2 a	4.5 a	30.6 b	14.2 a	365.3 ab	11,658 b
Cocodala	2024	CK	19.8 a	4.7 c	31.3 b	14.1 c	492.2 b	10,697 b
		K100	18.7 a	4.9 b	33.2 ab	15.1 ab	553.3 ab	11,171 b
		K60	19.4 a	5.1 a	33.1 a	15.6 a	591.8 a	14,551 a
		K40	20.6 a	4.8 b	34.4 a	15.4 a	542.4 ab	12,658 ab
		K0	16.6 b	4.8 b	29.6 b	14.3 bc	532.5 ab	10,894 b

Note: Different letters within the same year but among different treatments indicate significant differences in each indicator. All comparisons were considered significant at p < 0.05 in the LSD test. Moreover, due to significant differences in weather and soil conditions across different years and locations (Table 1), the data for each year are presented separately and no average value is taken.

A quadratic model was fitted to the relationship between maize yield (y, kg·ha⁻¹) and K fertilizer application rate (x, kg·ha⁻¹) across the three-year study (Table 5). The model showed that maize yield peaked at 15,971.7 kg·ha⁻¹ when the K application rate was 82.2 kg·ha⁻¹.

Table 5. Establishment of K fertilizer application rate equation and analysis of yield estimation results.

Year	y = ax2 + bx + c
	a	b	c	R2
2020	−0.4054	73.4779	14,415.0480	0.895
2021	−0.3736	64.3433	11,470.8454	0.705
2024	−0.5753	83.0128	10,717.0113	0.798
Mean	−0.5170	84.9845	12,479.0710	0.833

Note: a, b, and c represent the quadratic coefficient, linear coefficient, and constant coefficient, respectively; R² is the coefficient of determination which indicates the goodness of fit.

3.4. K Fertilizer Utilization Efficiency

There were significant differences (p < 0.05) in K fertilizer utilization efficiency among the K reduction treatments. A three-year pooled analysis showed that partial factor productivity (PFP_K) increased monotonically as K application declined. The K60 regime consistently outperformed K100, registering gains of 78.0%, 88.9% and 112.5% in 2020, 2021 and 2024, respectively (Table 6). The K fertilizer agronomic efficiency (AE_K) followed the same pattern, with K60 exceeding K100 by 176.4%, 300.9% and 2085% in 2020, 2021, and 2024; all differences were statistically significant. Therefore, under the experimental conditions of this study, the K60 treatment simultaneously increased PFP_K and AE_K, achieving higher K-use efficiency.

Table 6. Potassium fertilizer productivity and agronomic efficiency under different K fertilizer treatments.

Area	Years	Treatment	Potassium Fertilizer Productivity (PFPK) (kg·kg−1)	Potassium Fertilizer Agronomic Efficiency (AEK) (kg·kg−1)
Shihezi	2020	K100	123.4 c	16.5 b
		K60	219.6 b	45.6 a
		K40	299.4 a	38.0 a
	2021	K100	96.4 c	10.6 c
		K60	182.1 b	42.5 a
		K40	232.8 a	23.2 b
Cocodala	2024	K100	82.1 c	2.0 c
		K60	174.3 b	43.7 a
		K40	227.7 a	31.7 b

Note: Different letters within the same year but among different treatments indicate significant differences in each indicator. All comparisons were considered significant at p < 0.05 in the LSD test. Moreover, due to significant differences in weather and soil conditions across different years and locations (Table 1), the data for each year is presented separately and no average value is taken.

3.5. Economic Benefits

Across the three-year trial, net income exhibited a unimodal response to decreasing K rates, peaking under the K60 regime (Table 7). Net income for K60 was 28,206 CNY·ha⁻¹ in 2020, 22,916 CNY·ha⁻¹ in 2021 and 19,129 CNY·ha⁻¹ in 2024, representing 20.7–23.6% increases over the K100 treatment. Furthermore, this indicates that excessive application of K fertilizer does not guarantee an increase in final yield. Moderate reduction in K fertilizer thereby enhanced net income for farmers in arid and semi-arid regions.

Table 7. Economic benefits analysis under different K fertilizer treatments.

Area	Years	Treatment	Fertilizer Cost (CNY·ha−1)	Other Costs (CNY·ha−1)	Grain Value (CNY·ha−1)	Output Value of Feed (CNY·ha−1)	Net Income (CNY·ha−1)
Shihezi	2020	CK	0	11,850	21,110	9033	18,293
		K100	2609	11,850	25,168	12,658	23,367
		K60	2414	11,850	27,507	14,963	28,206
		K40	2209	11,850	24,967	13,781	24,689
		K0	2004	11,850	22,456	9608	18,210
	2021	CK	0	11,850	16,198	9098	13,446
		K100	2609	11,850	19,658	13,346	18,545
		K60	2414	11,850	22,807	14,373	22,916
		K40	2209	11,850	19,418	13,623	18,982
		K0	2004	11,850	17,487	9228	12,861
Cocodala	2024	CK	0	11,850	16,044	7848	12,042
		K100	2609	11,850	16,757	10,811	15,718
		K60	2414	11,850	21,767	11,626	19,129
		K40	2209	11,850	18,987	12,010	16,938
		K0	2004	11,850	16,341	10,553	13,040

Note: Due to significant differences in weather and soil conditions across different years and locations (Table 1), the data for each year is presented separately and no average value is taken.

Based on the quadratic regression model of the average economic benefits over three years, y = −1.0784x² + 183.2441x + 14,480.3748 (R² = 0.930), when the K fertilizer application rate x is 85.0 kg·ha⁻¹, the net income peaks at 22,261 CNY·ha⁻¹. Therefore, applying an appropriate amount of K fertilizer is the key to improving the economic benefits of maize in Xinjiang.

3.6. Partial Least Squares Structural Equation Model Analysis

The partial least squares structural equation model (PLS-SEM) revealed the key pathways and driving mechanisms of maize growth and yield formation under different K application levels (Figure 4). The results show that the efficiency of K fertilizer utilization has a significant positive effect on both vegetative growth and yield structure, and the path coefficients are 0.47 (p < 0.001) and 0.27 (p < 0.01), respectively, indicating that improving the efficiency of K fertilizer utilization can enhance plant growth vigor, promote the synthesis and accumulation of photosynthetic products, and facilitate the redistribution of DM to the reproductive organs, thereby optimizing yield composition. Additionally, yield structure had a significant positive impact on final yield, with a path coefficient of 0.28 (p < 0.01), suggesting that yield formation was directly driven by the grain filling capacity and grain weight. The model also indicated that yield was the most critical factor for economic benefit improvement, with a path coefficient of 0.73 (p < 0.001), indicating that changes in yield can directly determine production income.

Figure 4. Partial least squares structural equation modeling showing the pathways through which K fertilizer use efficiency influences vegetative growth, yield structure, grain yield, and economic benefit. Ellipses denote latent variables, and arrows indicate standardized path coefficients. Significance levels: ** p < 0.01, *** p < 0.001. Model fit: Gof = 0.43.

3.7. Spearman Correlation Between Maize Yield and Key Growth Parameters

The Spearman correlation analysis further verified the close relationship between maize growth indicators and yield factors at the statistical correlation level (Figure 5). The results showed that maize yield was significantly positively correlated with total biomass (TB), TKW, plant height, and LAI. Among them, the correlation between TKW and yield was the highest (r = 0.99, p < 0.01), indicating that the grain filling capacity had the most direct impact on the final yield, and showing that sufficient growth potential and DM accumulation is the basis for high yield formation. Furthermore, both plant height and leaf area index showed a highly significant positive correlation with yield (r = 0.93, p < 0.01). This indicates that appropriate K application can enhance the photosynthetic area of plants and increase photosynthetic efficiency, thereby promoting the accumulation of DM and increasing yield. The overall correlation results are highly consistent with the path model of PLS-SEM: enhancing growth potential, expanding photosynthetic area and increasing DM accumulation are the core processes for achieving high yield. TKW was the most crucial factor determining yield. Reasonable K application is an effective way to improve these indicators.

Figure 5. The relationship between maize yield and key growth parameters. Note: TB: total biomass; EL: ear length; SW: spike width; KN: kernel number; RN: row number; TKW: thousand kernel weight; GY: grain yield. Each circle represents the correlation between two variables. The color of the circle indicates the direction of the relationship, while the size of the circle reflects the strength of the correlation. Statistical significance levels are indicated by asterisks.

4. Discussion

4.1. Effect of Reduced K Fertilizer Application on the Growth Characteristics of Maize

Appropriate reduction in K fertilizer application can significantly promote the growth of maize. K is one of the three major nutrients essential for plant growth [34]. Its supply significantly impacts various physiological processes and overall development [35,36]. Our research has revealed that as the amount of K applied decreased, the plant height, LAI and aboveground DM of maize all showed a trend of first increasing and then decreasing. Specifically, the K60 treatment increased plant height, LAI, and aboveground DM by 2.7–19.7%, 6.9–20% and 18.5–25.9%, respectively, compared to the K100 treatment. This indicates that although K application is beneficial to maize growth, excessive application of K does not provide additional benefit and may even have an inhibitory effect. This finding aligns with the earlier research results of Wang et al. [37], whose study indicates that excessive K application reduces K fertilizer utilization efficiency and yield, leading to K surplus in the soil. This may be because excessive K application strongly inhibits root absorption and root-shoot transport of magnesium, leading to magnesium deficiency, which in turn disrupts key physiological processes such as photosynthesis, carbohydrate distribution, and nitrogen metabolism, ultimately reducing plant biomass and yield [2].

Notably, LAI differed between the two study regions. The LAI of maize in Cocodala is generally lower than that in Shihezi (Figure 2b). The research conducted by Alfaro et al. [38] indicates that an increase in precipitation can enhance soil drainage flow, strengthen the priority flow and large-pore flow processes, accelerate the migration of soluble K and exchangeable K in the soil, and thereby promote the leaching loss of K. The research conducted by Xu et al. [8] revealed that in areas with intense leaching, only when the K fertilizer input reaches the compensation threshold can it effectively promote leaf expansion and biomass accumulation. Therefore, in K-rich areas of Xinjiang, appropriately reducing the amount of K fertilizer not only does not inhibit growth but also promotes the accumulation of DM in maize.

4.2. Effect of Reducing K Fertilizer Usage on Yield, K Utilization Efficiency, and Economic Benefits

Beyond growth traits, the impact of K reduction on yield and resource economics is equally critical. Wang et al. [39] indicated that an appropriate application rate of K fertilizer can better achieve a synergistic balance between maize yield and K use efficiency. In this study, the K60 treatment not only achieved the highest grain yield but also had significantly higher PFP_k and AE_k than the conventional high-rate K application (K100), indicating that moderate reduction in application did not sacrifice yield but instead improved resource utilization efficiency. This result is consistent with that of Niu et al. [40]: they observed that when K input exceeded the maximum demand threshold of the crop, yield no longer increased, and K utilization efficiency significantly decreased. Similarly, Liu et al. [41] also reported in their experiments that as the application rate increased, yield showed a trend of increasing initially and then decreasing, while fertilizer utilization rate continuously decreased. The main reason for this phenomenon is that excessive application of K can reduce the effectiveness of nitrogen and phosphorus through ion competition and interfere with the absorption of calcium, magnesium, and other cations through antagonistic effects, ultimately leading to a simultaneous decline in nutrient utilization efficiency and yield [42,43]. It is worth noting that this study further found that excessive application of K (K100) not only failed to increase yield but instead led to a 6.9–15.1% decrease in yield compared to the K60 treatment, which is consistent with the trend of Yang et al.’s [44] results on winter wheat.

4.3. Analysis of the Production Mechanism Based on PLS-SEM and Spearman Correlation

To unravel the underlying mechanisms linking K efficiency to yield, we employed PLS-SEM and correlation analyses. This study further clarified the physiological and ecological pathways through which the utilization efficiency of K fertilizer affects the formation of maize yield: K use efficiency does not directly drive yield but indirectly enhances it by regulating vegetative growth and yield structure. Coskun et al. [45] proposed that K indirectly affects the grain filling process of cereal crops by regulating the distribution of photosynthetic products and the carbon-nitrogen metabolic balance. The results of this study are consistent with this mechanism: the PLS-SEM model shows that the utilization efficiency of K fertilizer significantly promotes vegetative growth (such as plant height and LAI) and optimizes the yield structure (such as TKW), thereby indirectly enhancing the final yield. At the same time, the Spearman’s analysis indicates that the correlation coefficient between TKW and yield was as high as 0.99, and the correlation coefficient between total biomass and yield was 0.98, further supporting the decisive role of efficient dry matter transport during the grain-filling period in the formation of yield. This discovery also supports the conclusion of Yang et al. [46] that K increases LAI and extends the photosynthetic functional period, increasing total biomass accumulation and optimizing harvest index. It is worth noting that under drip irrigation conditions in the arid region of Xinjiang, the K60 treatment can maintain or even enhance these physiological processes while reducing inputs, indicating that moderate K reduction does not weaken the physiological regulatory function of K, but achieves the coordinated optimization of resources and yield by improving utilization efficiency.

5. Conclusions

Optimizing the K application rate can effectively enhance maize growth, DM, GY, and net income. In maize production in high-K areas of Xinjiang, the K fertilizer application rate is strongly recommended to be 82.2–85 kg·ha⁻¹. Compared with the local conventional fertilization, this optimal rate reduces the K application rate by 35.7–37.8%. Additionally, the integration of PLS-SEM and Spearman’s correlation analysis revealed that enhancing K use efficiency boosts grain yield primarily by promoting vegetative growth and optimizing yield-related traits such as TKW and total DM. In the high-K areas of Xinjiang, reducing the application of K fertilizer can minimize resource waste, enhance the efficiency of K fertilizer utilization, and provide strong technical support for precise fertilization of maize in the arid regions of Xinjiang.