Effects of Irrigation Lower Limit and Nitrogen Rate on Productivity, Resource Use Efficiency, and Economic Benefits of Winter Rapeseed in Semi-Arid Conditions

Abstract

Integrated water and nitrogen management plays a crucial role in the sustainable intensification of rapeseed production, particularly in water-limited regions. This two-year field study (2022–2024) evaluated the interactive effects of three irrigation lower limits—W₁ (90% of field capacity, [FC]), W₂ (70% FC), and W₃ (50% FC)—and four nitrogen rates (0, 80, 160, and 240 kg N ha⁻¹; representing N₀, N₁, N₂, N₃, and N₄) on winter rapeseed growth, yield, resource use efficiency, and economic performance under semi-arid conditions. Both irrigation and nitrogen significantly influenced plant growth, photosynthetic performance, biomass accumulation, and yield formation, with pronounced interactive effects observed across most measured parameters. The W₁N₂ treatment achieved optimal performance, producing seed yields of 5131 and 3220 kg ha⁻¹ with superior nitrogen use efficiency. Overall, N₁, N₂, and N₃ increased yield by 38.12%, 79.26%, and 84.85%, respectively, relative to N₀. Compared with W₃N₀, W₁N₂ improved yield by 178%, water use efficiency by 131%, and irrigation water use efficiency by 110%. Relative to W₁N₃, W₁N₂ increased nitrogen agronomic efficiency, physiological efficiency, recovery efficiency, and partial factor productivity by 40.5%, 7.4%, 30.4%, and 45.2%, respectively, while reducing nitrate nitrogen residue by 12%. Entropy-TOPSIS analysis identified W₁N₂ as the top-ranked treatment, indicating that optimized irrigation and nitrogen management offer a sustainable strategy to maximize rapeseed productivity, enhance resource-use efficiency, and improve economic returns under water-limited conditions. For practical application in semi-arid environments, the W₁N₂ treatment is recommended as the optimal management strategy for sustainable winter rapeseed intensification.

1. Introduction

Rapeseed (Brassica napus L.) is the world’s second-largest oilseed crop after soybean and contributes approximately 20% of worldwide oil output [1,2]. Cultivated under diverse climatic conditions across all continents, this economically vital crop serves multiple functions, including premium edible oil for human nutrition, sustainable biodiesel feedstock, and environmental management applications [3,4]. Its oil content ranges from 35 to 50% of dry weight and is particularly valued for its abundance of essential fatty acids and vitamins [5,6,7]. In China, rapeseed is the primary edible oil and ornamental crop [8], with production reaching an average of 13 million tons from 690,000 ha of cultivated area over the past two decades [9,10]. Despite substantial yield improvements, domestic supply continues to fall short of demand, necessitating considerable foreign imports. Abiotic factors such as irrigation and nitrogen are essential for improving rapeseed growth and yield [11,12]. However, external environmental pressures can disrupt the biosynthetic mechanisms in plants [13], making it difficult to achieve optimal oil concentration levels in rapeseed under field production scenarios.

Water stress fundamentally disrupts crop physiology and productivity by inducing significant decreases in chlorophyll content and leaf area index (LAI) in rapeseed plants [11]. Chlorophyll reductions can reach 38% compared to adequately watered plants [14]. Beyond photosynthetic capacity, water deficit significantly impedes nitrogen translocation from soil and adversely affects nitrogen redistribution from various vegetative organs to grain, ultimately impacting nitrogen accumulation and soil nutrient dynamics [15,16,17]. Irrigation remains the principal growth-limiting factor for global agricultural production, particularly in farming systems established in arid and semi-arid zones [17,18]. Recent research indicates that 28–38% of current cropland faces water scarcity, lacking sufficient soil moisture and irrigation options to overcome these deficits [19].

The economic yield of rapeseed is fundamentally determined by cumulative biomass production, assimilate partitioning to pods, and the effective duration of pod filling [20]. During seasons with insufficient or absent rainfall, crops require irrigation support to maintain productive capacity. However, water availability for agricultural irrigation is increasingly constrained due to declining precipitation patterns and escalating demand from industrial, domestic, municipal, and other competing sectors [16]. Determining irrigation lower limits is crucial for crop productivity in water-scarce semi-arid regions. Strategic deficit irrigation, which maintains soil moisture above critical thresholds, enhances seed yield and water use efficiency while minimizing environmental impacts [11,21]. Previous studies have demonstrated that regulated deficit irrigation (60–80%, FC) sustains yield and improves water use efficiency while decreasing nitrate leaching [11,22]. Water-saving strategies, particularly drip fertigation, have been shown to increase yield and enhance both water and nitrogen use efficiency [23,24,25,26]. Therefore, adequate nutrient and water management can improve crop drought resistance [27]. However, fertility adjustments can either enhance or reduce this resistance depending on water–nutrient interactions and fertilizer effects on soil health [28,29].

Nitrogen (N) is a critical macronutrient that fundamentally governs plant growth and yield development, with strategic fertilizer management representing a vital approach for enhancing rapeseed productivity [30,31,32]. In rapeseed cultivation, N application can enhance yields by 1.1–2.4 t ha⁻¹ while simultaneously increasing the protein content and reducing oil concentrations [33,34,35]. However, despite global N fertilizer consumption exceeding 110 million tons annually, widespread excessive application has created a paradox of diminished use efficiency and environmental degradation [36]. In China, the N use efficiency for major field crops averages merely 25%, with substantial losses occurring through leaching, volatilization, and surface runoff, thereby compromising air and water quality [36,37,38]. This inefficiency is compounded by escalating fertilizer costs due to increased natural gas prices and supply chain disruptions, reducing rapeseed producer profitability while exacerbating environmental challenges [37,39]. These dual environmental and economic pressures have positioned N management at the forefront of global ecosystem research, with agronomic practices such as optimized application timing offering promising solutions [40,41,42]. Research demonstrates that synchronizing N availability with plant demand through strategic timing and application rates of 150–180 kg N ha⁻¹ can significantly increase both rapeseed yield and oil production while maintaining high use efficiency [43,44,45]. However, optimal application strategies remain highly site-specific and difficult to predict, depending on complex interactions between local environmental conditions and plant physiological demands [46].

Optimizing integrated water and nitrogen management is essential for sustainable rapeseed intensification under increasing water scarcity in semi-arid regions. While previous studies have demonstrated that optimal nitrogen fertilization enhances yield and resource use efficiency [47], and balanced nitrogen management reduces lodging risk while sustaining productivity [12], the interactive effects of irrigation regimes and nitrogen rates on rapeseed physiological performance, root morphology, yield components, and resource use efficiency remain poorly understood, as comprehensive investigations integrating both factors are limited. This two-year field study evaluated the interaction effects of irrigation and nitrogen management with the following objectives: (1) quantify interactive effects on plant growth, root development, and photosynthetic performance; (2) determine optimal combinations for maximizing seed yield and resource use efficiency; and (3) assess economic viability and environmental sustainability. Understanding these synergistic effects is vital for developing evidence-based strategies that enhance productivity while minimizing environmental impacts in water-limited production systems.

2. Materials and Methods

2.1. Experimental Site

A two-year field experiment was conducted during the consecutive winter rapeseed growing seasons from October 2022 to June 2023 and October 2023 to June 2024 at the irrigation experimental station of the Key Laboratory of Agricultural Water and Soil Engineering, Northwest A&F University. The experimental site, situated under a rain shelter in Yangling, Shaanxi Province, China (108°24′ E, 34°18′ N, 521 m a.s.l.), experiences a semi-humid, drought-prone climate. The mean annual temperature is 12.9 °C, with an annual precipitation of 635 mm, and an annual evaporation of 1500 mm. Rainfall is predominantly concentrated between July and September, with average annual sunshine hours of 2163.8 h. During the experimental periods, total precipitation was 249.3 mm (2022–2023) and 193.7 mm (2023–2024). Detailed rainfall and temperature patterns are presented in Figure 1. The experimental field consists of silty clay loam soil with a bulk density of 1.35 g cm⁻³ (0–60 cm depth) and a field capacity of 0.267 cm³ cm⁻³. Initial soil properties (0–20 cm depth) were as follows: electrical conductivity 1.17 dS m⁻¹, pH 8.17, organic matter 12.02 g kg⁻¹, total nitrogen 0.77 g kg⁻¹, nitrate-N 20.94 mg kg⁻¹, ammonium-N 7.01 mg kg⁻¹, available phosphorus 13.5 mg kg⁻¹, and available potassium 102.3 mg kg⁻¹. The groundwater table was below 50 m, thereby excluding any capillary rise contribution to the root zone water supply.

2.2. Experimental Design and Crop Management

The experiment employed a two-factor randomized complete block design with three replications (36 plots total) using the winter rapeseed cultivar ‘Qin You 1618’. The factors consisted of irrigation regime and nitrogen (N) fertilization rate. Three irrigation treatments were established based on soil moisture depletion thresholds relative to field capacity (θ_f): W₁ (irrigation triggered at 90% θ_f), W₂ (irrigation triggered at 70% θ_f), and W₃ (irrigation triggered at 50% θ_f). In all treatments, soil moisture was restored to 100% θf at each irrigation event. Four N rates were applied: N₀ (0 kg N ha⁻¹, control), N₁ (80 kg N ha⁻¹), N₂ (160 kg N ha⁻¹), and N₃ (240 kg N ha⁻¹). Each experimental plot measured 4.0 m × 4.0 m, with 1.0 m buffer zones surrounding the experimental area and 0.5 m isolation strips between adjacent plots. Rapeseed was planted at row and plant spacings of 50 cm and 14 cm, respectively, following local practices. Plant density was standardized at 140,000 plants ha⁻¹ through post-emergence thinning after true leaves developed.

2.2.1. Fertilization Management

Nutrient management was implemented through an integrated drip fertigation system. Fertilizer sources included urea (46.4% N), superphosphate (16% P₂O₅), and potassium chloride (60% K₂O). Phosphorus (120 kg P₂O₅ ha⁻¹) and potassium (90 kg K₂O ha⁻¹) were applied as basal fertilizers before sowing. Nitrogen was applied through fertigation in four split applications: 30% at the seedling stage, 30% at the bud stage, 20% at the flowering stage, and 20% during pod development. For the N₀ treatment, only phosphorus and potassium were applied.

2.2.2. Irrigation System and Scheduling

A surface drip irrigation (SDI) system was installed with emitters spaced at 10 cm intervals along lateral lines spaced 50 cm apart. The system operated at 0.1 MPa working pressure with an emitter discharge rate of 2.3 L h⁻¹. Polyethylene (PE) pipelines served as the main water carriers adjacent to the experimental area, with individual outlets and water-tight valves controlling irrigation for each subplot. Irrigation volume was measured using flow meters installed at each subplot outlet. Crop irrigation requirement (CIR, mm) was calculated using the soil water balance approach [48,49].

CIR = 10 × γ_bd × D_h × (θ_t − θ_n)

(1)

where γ_bd is soil bulk density (g cm⁻³), D_h is the measurement depth for soil water content (cm), θ_t is the target gravimetric soil water content after irrigation (%), and θ_n is the gravimetric soil water content before irrigation (%). The measurement depth (D_h) varied by growth stage: 30 cm at the bud stage, 40 cm at the flowering stage, and 50 cm from pod formation to maturity. Target soil water content was calculated as

θ_t = θ_max × (θ_tr/100)

(2)

where θ_max is field capacity (%) and θ_tr is the target relative soil water content (set at the respective treatment thresholds of 90%, 70%, or 50% for W₁, W₂, and W₃, respectively). After irrigation, soil moisture was restored to field capacity (100% θ_f) for all treatments.

2.3. Measurements and Calculations

2.3.1. Growth and Physiological Parameters

Plant height (from ground to apex) and stem diameter were measured at six growth stages: budding stage (BS), early flowering stage (EFS), full flowering stage (FFS), last flowering stage (LFS), pod development stage (PDS), and maturity (MT). Data were collected from five representative plants per plot. LAI was measured using an LAI-2200C plant canopy analyzer (Li-Cor, Lincoln, NE, USA) at BS, EFS, FFS, PDS, and MT.

At each growth stage, three representative plants were randomly selected from each plot for destructive sampling to measure aboveground dry matter accumulation (ADMA). Each plant was carefully separated into roots, stems, leaves, and reproductive organs (when present). The samples were initially oven-dried at 105 °C for 30 min to halt metabolic processes, then dried at 75 °C until reaching constant weight. Dry weights were recorded and subsequently converted to kg ha⁻¹ based on the established plant density within each plot. For root morphology analysis at the harvest stage, root samples were collected using a soil corer with a 10 cm inner diameter at two distances from the drip line (10 cm and 20 cm) within the 0–30 cm soil depth. Two soil cores were extracted per plot, and roots were carefully removed from the cores and thoroughly washed to eliminate adhering soil particles. The cleaned root samples were then scanned using a flatbed scanner (Epson Perfection V700, Suwa, Nagano, Japan), and the resulting digital images were analyzed with WinRHIZO Pro version 5.0 software (Regent Instruments Inc., Quebec City, QC, Canada) to quantify key root morphological parameters, including total root length (cm), surface area (cm²), average diameter (mm), and root volume (cm³).

Photosynthetic parameters were measured on the first fully expanded leaf of the upper canopy using a portable photosynthetic system (Li-6800, Li-Cor, USA) between 10:00 and 12:00 a.m. The parameters included net photosynthetic rate (P_n), stomatal conductance (g_s), and transpiration rate (T_r). Chlorophyll fluorescence was measured at the bolting, flowering, and maturity stages using a portable chlorophyll fluorometer (PSI, Drasov, Czech Republic). Leaves were dark-adapted for 20 min before measurement, with three replicates per plot. Measurements avoided leaf veins and retained leaf boundaries. The following fluorescence parameters were derived: maximum photochemical efficiency of PSII (F_v/F_m), effective quantum efficiency of PSII (ΦPSII), photochemical quenching coefficient (qP), and non-photochemical quenching coefficient (NPQ). The calculation formulas are as follows:

F_v/F_m = (F_m − F_o)/F_m

(3)

ΦPSII = (F_m′ − F_t)/F_m′

(4)

qP = (F_m′ − F_t)/(F_m′ − F_o′)

(5)

NPQ = (F_m − F_m′)/F_m′

(6)

where F_m and F_o are the dark-adapted maximum and minimum fluorescence; F_m′ is the light-adapted maximum fluorescence; F_o′ is the light-adapted minimum fluorescence (estimated with far-red light); F_t is the steady-state fluorescence under actinic light; F_v is variable fluorescence (F_m − F_o).

2.3.2. Seed Yield, Quality, and Economic Analysis

At physiological maturity, 20 plants were randomly selected from each plot to determine pods per plant and seeds per pod. The 1000-seed weight was measured by weighing four replicates of 500 seeds per plot and then converting the value. Seeds were harvested from a 2 m² area in the center of each plot to avoid edge effects. After four days of field drying, seeds were threshed, cleaned, and yields were calculated based on 12% moisture content and expressed as kg ha⁻¹. Oil and protein content were determined using Near-Infrared spectroscopy (NYDL-3000; Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China) according to standard protocols.

The economic benefit (EB, CNY ha⁻¹) is calculated as

GP = P × Y

(7)

EB = GP − TC

(8)

where GP is gross profit (CNY ha⁻¹), P is rapeseed unit price (CNY kg⁻¹), Y is grain yield (kg ha⁻¹), EB is economic benefit or net profit (CNY ha⁻¹), and TC is total cost (CNY ha⁻¹).

Total cost included the drip irrigation system (6313 CNY ha⁻¹ with a two-year service life, equivalent to 3156 CNY ha⁻¹ per season), seeds, fertilizers, irrigation water, and miscellaneous expenses (labor, machinery, weeding, and pest control). Input prices during the experimental period were rapeseed 6.51 CNY kg⁻¹, urea 1.85 CNY kg⁻¹, superphosphate 0.90 CNY kg⁻¹, potassium chloride 3.6 CNY kg⁻¹, and irrigation water 0.4 CNY m⁻³.

2.3.3. Soil Nitrate Residual

After crop harvest, soil samples were collected from each plot at the same locations used for soil moisture monitoring. Sampling was conducted at 10 cm intervals to 100 cm depth. Samples were air-dried, ground, and sieved through a 1 mm mesh. For nitrate-N extraction, 5 g of soil was mixed with 50 mL of 2 mol L⁻¹ KCl solution and shaken for 30 min. The filtrate was analyzed for NO₃⁻-N concentration using a continuous flow analyzer (SEAL AA550, SEAL Analytical GmbH, Norderstedt, Germany).

Total soil nitrate-N accumulation (kg N ha⁻¹) in the 0–100 cm profile was calculated as

SNR = Σ(CNO₃-N × h_i × γ_i × 0.1)

(9)

where CNO₃-N is nitrate-N concentration (mg kg⁻¹), h_i is soil layer thickness (cm), γ_i is soil bulk density (g cm⁻³), and 0.1 is the conversion factor.

2.3.4. Evapotranspiration and Water Use Efficiency

Crop evapotranspiration (ET, mm) during the growing season was calculated using the water balance equation

ET = I + P − R − D ± ΔSWS

(10)

where I is irrigation (mm), P is precipitation (mm), R is the surface runoff (mm), D is deep drainage (mm), and ∆SWS is the change in soil water storage within the 0–100 cm soil layer from sowing to harvesting (mm). The groundwater table is approximately 50 m below the surface, resulting in negligible upward flow into the root zone. The field was flat and no runoff was observed; therefore, R and D were disregarded.

Water use efficiency (WUE, kg m⁻³) and irrigation water use efficiency (IWUE, kg m⁻³) are calculated as follows:

WUE = GY/ET

(11)

IWUE = GY/I

(12)

where GY is grain yield (kg ha⁻¹), ET is crop evapotranspiration (mm), and I is total irrigation (mm).

2.3.5. Nitrogen Uptake and Use Efficiency

At maturity, plant samples were separated into different organs (roots, stems, leaves, pods, seeds), dried at 75 °C to constant weight, and ground to pass through a 1 mm sieve. Samples were digested with concentrated H₂SO₄ and H₂O₂, and total N concentration was determined using a continuous flow analyzer (AA5, SEAL Analytical GmbH, Germany).

Crop nitrogen uptake (kg N ha⁻¹) was calculated as:

NU = ΣC_N × DM_i/1000

(13)

where NU is crop nitrogen uptake, C_N is N concentration in each organ (g kg⁻¹), DM is dry matter weight of corresponding organs (kg ha⁻¹), and 1000 is the conversion factor.

The N use efficiency indicators N partial factor productivity (NPFP, kg kg⁻¹), N agronomic efficiency (NAE, kg kg⁻¹), N recovery efficiency (NRE, %), and N physiological efficiency (NPE, kg kg⁻¹) were measured using the equations below [50,51].

NPFP = GY/F_N

(14)

NAE = (GYN − GY0)/F_N

(15)

NRE= [(UN − U0)/FN] × 100

(16)

NPE= NPE = (GYN − GY0)/(UN − U0)

(17)

where GY is grain yield (kg ha⁻¹), FN is N application rate (kg ha⁻¹), GYN and GY0 are seed yields with and without N fertilizer (kg ha⁻¹), and UN and U0 are total aboveground N uptake at harvest with and without N fertilizer (kg ha⁻¹), respectively.

2.4. Data Statistical Analysis

Data were organized using Microsoft Excel 2019 and analyzed using SPSS 27.0 (IBM Corp., Armonk, NY, USA). Two-way analysis of variance (ANOVA) based on a randomized complete black design was conducted to evaluate the main effects of irrigation regime and nitrogen rate, as well as their interaction, with blocks treated as a random factor. When significant effects were detected (p < 0.05), mean comparisons were performed using the least significant difference (LSD) test. To determine indicator weights and obtain a comprehensive performance ranking of the twelve combined treatments, the entropy-based TOPSIS multi-criteria decision-making method was employed [52]. Figures were created using OriginPro 2024 (OriginLab Corporation, Northampton, MA, USA).

3. Results

3.1. Integrated Effects of Iirrigation and Nitrogen on Rapeseed Growth and Physiological Traits

3.1.1. Plant Height and Stem Diameter

Plant height and stem diameter, key indicators of growth and yield potential, were significantly influenced by irrigation and nitrogen (p < 0.01), with significant interactions for stem diameter at most growth stages. Both parameters increased during vegetative and early reproductive stages, reaching maximum values at pod development (plant height: 148.1 cm in 2022–2023; 122.7 cm in 2023–2024) and early flowering (stem diameter: 6.48–18.80 mm in 2022–2023; 6.15–13.37 mm in 2023–2024), then plateauing or declining toward maturity.

Both traits responded positively to increased irrigation and nitrogen, with W₁N₃ consistently producing maximum values comparable to W₁N₂ (Figure S1 and S2). Nitrogen fertilization increased plant height and stem diameter by 12.0–26.4% and 10.3–27.6%, respectively, compared to the control, though N₂ and N₃ showed no significant difference for stem diameter, indicating diminishing returns. Higher irrigation (W₁ and W₂) enhanced plant height by 18.4% and 11.0% and stem diameter by 18.6–21.3% and 9.8–11.5%, respectively, compared to deficit irrigation (W₃). Both parameters were 14.2–30.5% lower in the second season, likely reflecting differing environmental conditions.

3.1.2. Integrated Effects of Irrigation and Nitrogen on Dry Matter Accumulation and Root Characteristics

Aboveground dry matter accumulation (ADMA), a key growth indicator and yield determinant, was significantly influenced by irrigation, nitrogen, and their interaction across both seasons (p < 0.01). ADMA increased gradually to peak at maturity, with the highest accumulation rate occurring between the early and late flowering stages before slowing during pod development. Nitrogen fertilization substantially increased ADMA at maturity by 26.8–80.7% (2022–2023) and 29.3–76.1% (2023–2024) compared to the control, with maximum values at N₃ that were not significantly different from N₂. Similarly, higher irrigation levels (W₁ and W₂) increased ADMA by 50.4–59.4% and 24.7–33.5%, respectively, compared to deficit irrigation (W₃). The W₁N₃ treatment consistently produced the maximum ADMA across both seasons, with no difference compared to W₁N₂ (Figure S3).

Irrigation and nitrogen significantly affected rapeseed root characteristics in the 0–30 cm soil layer at maturity (p < 0.01), with their interaction significantly influencing only root surface area (

Table 1. Interactive effects of irrigation regimes and nitrogen application rates on rapeseed root morphological indicators during 2022–2024.

	2022–2023				2023–2024
Treatment	TRL (cm)	RSA (cm2)	ARD (mm)	RV (cm3)	TRL (cm)	RSA (cm2)	ARD (mm)	RV (cm3)
W1N0	2184.0 g	233.2 h	0.67 c	12.55 g	1610.1 h	162.9 h	0.82 bcd	11.84 h
W1N1	2526.8 fg	267.0 gh	0.77 b	13.93 f	1712.0 h	181.4 gh	0.89 bc	12.18 h
W1N2	3083.5 ef	352.0 ef	0.96 a	15.35 e	2237.8 g	252.5 ef	1.02 a	13.53 fg
W1N3	2941.8 f	312.3 fg	0.93 a	15.00 e	2234.5 g	219.9 fg	1.03 a	13.38 g
W2N0	3550.4 de	282.0 g	0.50 de	15.24 e	2982.6 f	211.1 g	0.59 f	14.52 fg
W2N1	3741.7 d	361.5 de	0.55 d	16.03 d	3328.0 ef	291.7 de	0.78 cde	14.94 ef
W2N2	3947.8 d	411.6 c	0.81 b	17.40 c	3825.7 cd	362.2 c	0.84 bc	15.88 d
W2N3	3910.7 d	399.3 cd	0.80 b	17.15 c	3637.8 de	322.1 d	0.91 b	15.34 e
W3N0	4933.2 c	335.6 ef	0.45 e	17.51 c	4126.3 c	282.4 de	0.49 g	17.18 cd
W3N1	5257.2 bc	417.9 c	0.47 e	18.62 b	4600.4 b	365.5 c	0.68 ef	17.51 bc
W3N2	5996.8 a	650.7 a	0.66 c	19.53 a	5263.4 a	566.1 a	0.72 de	18.65 a
W3N3	5528.1 ab	594.5 b	0.47 e	19.32 a	4928.1 ab	480.3 b	0.72 de	17.82 ab
Significance test
W	**	**	**	**	**	**	**	**
N	**	**	**	**	**	**	**	**
W × N	ns	*	ns	ns	ns	**	ns	ns

Note: TRL, RSA, RAD, and RV denote total root length, root surface area, root average diameter, and root volume, respectively. Different letters within columns indicate significant differences among treatments (LSD test, p < 0.05). ns indicates not significant (p > 0.05); * and ** denote significance at p < 0.05 and p < 0.01, respectively.

). Nitrogen fertilization enhanced all root parameters, with maximum values generally observed at N₂ that were not significantly different from N₃. Across both seasons, nitrogen increased root length by 8.0–29.9%, surface area by 10.6–66.2%, volume by 2.5–15.4%, and diameter by 9.4–47.2% compared to the control. Irrigation showed contrasting effects on root morphology: higher irrigation levels (W₁ and W₂) increased root length (41.1–142.7%), surface area (24.9–142.7%), volume (15.8–39.7%), and diameter (19.8–62.7%) compared to deficit irrigation (W₃). The substantial increases in root development under adequate water and nitrogen supply corresponded with enhanced aboveground growth and yield performance.

3.1.3. Integrated Effects of Irrigation and Nitrogen on Leaf Photosynthesis, Chlorophyll Fluorescence, and Leaf Area Index

Irrigation and nitrogen significantly affected the photosynthetic parameters (P_n, g_s, and T_r) of winter rapeseed across all growth stages (p < 0.01; Figure 2 and Figures S4 and S5). Throughout the budding, full flowering, and maturity stages, all three parameters consistently increased with nitrogen application (N₀ < N₁ < N₂ ≤ N₃), with no significant differences between N₂ and N₃. At maturity, nitrogen fertilization increased P_n by 16.7–55.9%, g_s by 11.5–46.9%, and T_r by 32.6–93.7% compared to the control. Similarly, higher irrigation levels enhanced photosynthetic capacity (W₁ > W₂ > W₃), with W₁ and W₂ increasing P_n by 15.2–31.9% and 9.6–14.4%, g_s by 17.6–32.5% and 11.5–11.7%, and T_r by 37.1–44.3% and 15.4–21.9%, respectively, compared to deficit irrigation (W₃). Among combined treatments, the highest value was observed with W₁N₃, with no difference compared to W₁N₂. These enhanced photosynthetic parameters under optimal water and nitrogen conditions contributed to greater biomass accumulation and yield.

Irrigation and nitrogen application significantly affected (p < 0.01) chlorophyll fluorescence parameters across all developmental stages in both growing seasons (

Table 2. Interactive effects of irrigation regimes and nitrogen application rates on chlorophyll fluorescence indicators of winter rapeseed during 2022–2023.

Treatment	Budding Stage				Flowering Stage				Maturity Stage
	Fv/Fm	φPSII	NPQ	qP	Fv/Fm	φPSII	NPQ	qP	Fv/Fm	φPSII	NPQ	qP
W1N0	0.813 de	0.382 f	0.858 c	0.639 e	0.786 e	0.377 e	0.974 cd	0.585 de	0.770 e	0.368 e	1.070 d	0.522 e
W1N1	0.821 bc	0.432 c	0.800 e	0.656 cd	0.797 c	0.415 c	0.911 e	0.599 c	0.785 c	0.390 c	0.983 ef	0.544 c
W1N2	0.831 a	0.467 a	0.746 g	0.677 ab	0.816 a	0.435 a	0.802 g	0.628 a	0.798 a	0.412 a	0.891 g	0.566 ab
W1N3	0.831 a	0.467 a	0.710 h	0.678 a	0.816 a	0.438 a	0.792 g	0.630 a	0.801 a	0.413 a	0.876 g	0.570 a
W2N0	0.800 f	0.368 gh	0.919 b	0.617 f	0.778 f	0.365 f	1.025 b	0.573 f	0.758 f	0.356 f	1.208 b	0.505 f
W2N1	0.817 cd	0.396 d	0.833 d	0.647 de	0.789 de	0.398 d	0.957 cde	0.590 cd	0.777 d	0.377 d	1.049 d	0.531 de
W2N2	0.824 b	0.447 b	0.779 f	0.666 bc	0.804 b	0.423 bc	0.865 f	0.613 b	0.791 b	0.400 b	0.960 ef	0.557 b
W2N3	0.824 b	0.450 b	0.760 fg	0.667 b	0.806 b	0.426 bc	0.859 f	0.614 b	0.792 b	0.400 b	0.939 f	0.557 b
W3N0	0.792 g	0.360 h	0.946 a	0.604 g	0.772 g	0.355 g	1.110 a	0.561 g	0.740 g	0.340 g	1.345 a	0.492 g
W3N1	0.807 e	0.374 fg	0.909 b	0.627 f	0.781 f	0.369 ef	1.002 bc	0.575 ef	0.763 f	0.360 f	1.135 c	0.511 f
W3N2	0.817 cd	0.409 d	0.831 d	0.649 de	0.790 de	0.405 d	0.933 de	0.590 cd	0.779 d	0.380 d	1.000 e	0.532 de
W3N3	0.818 bcd	0.416 c	0.830 d	0.650 de	0.791 d	0.405 d	0.924 e	0.590 cd	0.781 cd	0.382 d	0.997 e	0.535 cd
Significance test
W	**	**	**	**	**	**	**	**	**	**	**	**
N	**	**	**	**	**	**	**	**	**	**	**	**
W × N	ns	**	*	ns	**	*	ns	ns	ns	ns	**	ns

Note: F_v/F_m, φPSII, NPQ, and qP represent maximum photochemical efficiency of PSII, effective quantum efficiency of PSII, non-photochemical quenching coefficient, and photochemical quenching coefficient, respectively. Different letters within columns indicate significant differences among treatments (LSD test, p < 0.05). ns indicates not significant (p > 0.05); * and ** denote significance at p < 0.05 and p < 0.01, respectively.

and

Table 3. Interactive effects of irrigation regimes and nitrogen application rates on chlorophyll fluorescence indicators of winter rapeseed during 2023–2024.

Treatment	Budding Stage				Flowering Stage				Maturity Stage
	Fv/Fm	φPSII	NPQ	qP	Fv/Fm	φPSII	NPQ	q qP	Fv/Fm	φPSII	NPQ	qP
W1N0	0.796 e	0.373 de	1.305 c	0.562 de	0.781 ef	0.363 ef	1.400 d	0.543 ef	0.763 de	0.286 ef	1.898 c	0.513 de
W1N1	0.810 c	0.388 c	1.078 ef	0.573 c	0.795 c	0.377 c	1.257 e	0.571 cd	0.775 c	0.313 c	1.778 ef	0.530 bc
W1N2	0.824 a	0.410 a	0.999 gh	0.632 a	0.810 a	0.401 a	1.088 f	0.592 ab	0.792 a	0.353 a	1.648 gh	0.558 a
W1N3	0.827 a	0.414 a	0.954 h	0.636 a	0.810 a	0.402 a	0.971 g	0.605 a	0.792 a	0.355 a	1.624 h	0.563 a
W2N0	0.783 fg	0.364 fg	1.388 ab	0.556 e	0.771 g	0.352 gh	1.698 b	0.526 g	0.755 fg	0.277 g	2.049 b	0.494 f
W2N1	0.804 d	0.378 cd	1.230 d	0.567 cd	0.786 de	0.369 de	1.387 d	0.551 e	0.769 cd	0.294 de	1.867 cd	0.521 cd
W2N2	0.816 b	0.399 b	1.064 ef	0.600 b	0.801 b	0.386 b	1.147 f	0.577 bc	0.782 b	0.327 b	1.736 ef	0.540 b
W2N3	0.818 b	0.400 b	1.039 fg	0.604 b	0.803 b	0.388 b	1.109 f	0.583 bc	0.783 b	0.330 b	1.703 fg	0.539 b
W3N0	0.779 g	0.358 g	1.406 a	0.545 f	0.765 h	0.345 h	1.784 a	0.493 h	0.749 g	0.262 h	2.134 a	0.455 g
W3N1	0.788 f	0.368 ef	1.350 bc	0.559 e	0.776 fg	0.357 fg	1.591 c	0.532 fg	0.759 ef	0.280 fg	1.921 c	0.502 ef
W3N2	0.805 cd	0.382 c	1.202 d	0.569 c	0.791 cd	0.373 cd	1.379 d	0.558 de	0.771 c	0.296 d	1.859 cd	0.525 c
W3N3	0.806 cd	0.385 c	1.109 e	0.570 cd	0.792 cd	0.375 cd	1.322 de	0.567 cd	0.772 c	0.296 d	1.801 de	0.527 c
Significance test
W	**	**	**	**	**	**	**	**	**	**	**	**
N	**	**	**	**	**	**	**	**	**	**	**	**
W × N	ns	ns	**	**	ns	ns	*	ns	ns	**	ns	**

Note: Fv/Fm, φPSII, NPQ, and qP represent maximum photochemical efficiency of PSII, effective quantum efficiency of PSII, non-photochemical quenching coefficient, and photochemical quenching coefficient, respectively. Different letters within columns indicate significant differences among treatments (LSD test, p < 0.05). ns indicates not significant (p > 0.05); * and ** denote significance at p < 0.05 and p < 0.01, respectively.

), with parameters consistently declining from budding to maturity. Nitrogen application enhanced photosynthetic efficiency indicators (Fv/Fm, ΦPSII, and qP) while reducing non-photochemical quenching (NPQ), with maximum responses observed at N₂ and diminishing returns at N₃. At the budding stage, N₂ and N₃ increased Fv/Fm by 2.8–4.0%, ΦPSII by 8.9–20.1%, and qP by 7.2–8.9%, while decreasing NPQ by 13.5–24.4% compared to N₀, with similar trends at the flowering and maturity stages. Likewise, adequate irrigation (W₁ and W₂) improved photosynthetic performance relative to deficit irrigation (W₃). Averaged across both years, W₁ and W₂ increased Fv/Fm by 2.45% and 1.3%, ΦPSII by 7.45% and 4.1%, and qP by 6.45% and 3.6%, while decreasing NPQ by 9.35% and 17.35%, respectively. These results demonstrate that both water and nitrogen availability optimize photosystem II efficiency and photochemical energy conversion in winter rapeseed.

Leaf area index (LAI), which reflects crop canopy size and photosynthetic capacity, was significantly influenced by irrigation, nitrogen, and their interaction at most growth stages (p < 0.01). LAI increased from budding to full flowering stage, where it peaked before declining sharply toward maturity (Figure 3). At full flowering, nitrogen fertilization increased the two-year average LAI by 27.3–64.1% compared to the control, with no significant difference between N₂ and N₃. Higher irrigation levels (W₁ and W₂) increased LAI by 38.0% and 20.8%, respectively, compared to deficit irrigation (W₃). The W1N₃ and W₁N₂ treatments produced the highest LAI values, with no significant difference between them.

3.2. Integrated Effects of Irrigation and Nitrogen on Seed Yield and Economic Benefits

Nitrogen, irrigation, and their interaction significantly affected seed yield and its components (p < 0.01;

Table 4. Interactive effects of irrigation regimes and nitrogen application rates on chlorophyll fluorescence indicators of winter rapeseed during 2022–2023 and 2023–2024.

	2022–2023					2023–2024
Treatment	BN	PN	SN	TSW (g)	SY (kg ha−1)	BN	PN	SN	TSW	SY (kg ha−1)
W1N0	8.2 c	347 e	22.3 e	3.70 ef	2576 e	5.5 d	232 e	21.3 e	3.46 de	1726 e
W1N1	8.3 bc	413 c	24.5 c	3.98 c	3427 c	6.2 c	284 c	23.5 c	3.62 bc	2194 c
W1N2	11.3 a	486 a	26.6 a	4.19 ab	5131 a	8.1 a	358 a	25.3 a	3.83 a	3220 a
W1N3	11.3 a	503 a	26.7 a	4.23 a	5234 a	8.5 a	364 a	25.1 ab	3.90 a	3391 a
W2N0	7.3 d	312 f	20.8 f	3.55 gh	2012 f	4.7 ef	189 f	20.0 f	3.36 fg	1417 f
W2N1	8.0 c	371 d	23.0 de	3.80 de	2790 d	5.6 d	248 de	21.9 de	3.52 cd	1856 de
W2N2	8.5 bc	441 b	25.3 b	4.05 c	3703 b	7.1 b	307 b	24.0 c	3.69 b	2387 b
W2N3	8.7 b	447 b	25.8 b	4.10 bc	3813 b	7.3 b	313 b	24.3 bc	3.72 b	2506 b
W3N0	6.7 e	289 g	19.6 g	3.45 h	1771 g	4.4 f	166 g	19.0 g	3.27 g	1236 g
W3N1	6.9 de	324 f	21.4 f	3.60 fg	2138 f	4.9 ef	196 f	20.1 f	3.40 e	1492 f
W3N2	8.0 c	374 d	23.3 d	3.80 d	2873 d	5.6 d	257 d	22.2 d	3.56 cd	1935 d
W3N3	8.5 bc	383 d	23.6 d	3.85 d	2905 d	5.8 cd	263 d	22.2 d	3.56 cd	2000 d
Significance test
W	**	**	**	**	**	**	**	**	**	**
N	**	**	**	**	**	**	**	**	**	**
W × N	**	**	ns	ns	**	**	ns	ns	ns	**

Note: BN, PN, SN, TSW, and SY represent branch number, pod number, seed number, thousand-seed weight, and seed yield, respectively. Different letters within columns indicate significant differences among treatments (LSD test, p < 0.05). ns indicates not significant (p > 0.05) and ** denote significance at p < 0.01, respectively.

). Seed yield peaked at N₃, with no significant difference from N₂, representing increases of 44.6–46.8% and 29.8–30.1% over N₀ and N₁, respectively, across both seasons. Higher irrigation levels substantially enhanced yield, with W₂ and W3 reducing yields by 22.5–24.7% and 36.7–40.8%, respectively, compared to W₁. Branch numbers (6.7–11.3 in 2022–2023; 4.4–8.5 in 2023–2024) and pod numbers per plant followed similar response patterns, maximizing under W₁N₃ or W₁N₂. In contrast, seeds per pod and 1000-seed weight peaked at N₂, showing diminishing or negative returns at N₃, which decreased these parameters by 0.6% and 1.0%, respectively. Across irrigation levels, W₂ and W₃ reduced seeds per pod by 5.2% and 12.3%, and 1000-seed weight by 3.6% and 7.8%, respectively, compared to W₁.

Economic analysis revealed that net income ranged from −1845 to 23,119 CNY ha⁻¹ across both seasons, peaking under W₁N₃ with no significant difference from W₁N₂ (

Table 5. Interactive effects of irrigation regimes and nitrogen application rates on the economic benefits (CNY ha⁻¹) of winter rapeseed during the 1st (2022–2023) and 2nd (2023–2024) years.

Treatments	Output		Irrigation		Seedling	Drip Irrigation Tubes	Fertilizer	Others	Net Income
	1st Year	2nd Year	1st Year	2nd Year	Over Two Years	Over Two Years	Over Two Years	Over Two Years	1st Year	2nd Year
W1N0	16,763 e	11,232 e	778.00	845.00	3828.00	3156.00	1215.00	1000.00	6787 e	1188 d
W1N1	22,305 c	14,280 c	778.00	845.00	3828.00	3156.00	1537.00	1000.00	12,007 c	3913 c
W1N2	33,390 a	20,958 a	778.00	845.00	3828.00	3156.00	1858.00	1000.00	22,770 a	10,270 a
W1N3	34,062 a	22,071 a	778.00	845.00	3828.00	3156.00	2180.00	1000.00	23,119 a	11,062 a
W2N0	13,092 f	9223 f	699.00	778.00	3828.00	3156.00	1215.00	1000.00	3194 f	−754 f
W2N1	18,156 d	12,081 de	699.00	778.00	3828.00	3156.00	1537.00	1000.00	7936 d	1783 d
W2N2	24,099 b	15,533 b	699.00	778.00	3828.00	3156.00	1858.00	1000.00	13,558 b	4912 bc
W2N3	24,817 b	16,310 b	699.00	778.00	3828.00	3156.00	2180.00	1000.00	13,954 b	5368 b
W3N0	11,526 g	8042 g	600.00	688.00	3828.00	3156.00	1215.00	1000.00	1726 g	−1845 g
W3N1	13916 f	9712 f	600.00	688.00	3828.00	3156.00	1537.00	1000.00	3795 f	−497 e
W3N2	18,696 d	12,592 d	600.00	688.00	3828.00	3156.00	1858.00	1000.00	8253 d	2062 d
W3N3	18,903 d	13,018 d	600.00	688.00	3828.00	3156.00	2180.00	1000.00	8139 d	2166 d

Note: Data are expressed as mean ± standard deviation of treatments (n = 3), with different letters representing significant differences (p < 0.05).

). Water stress and inadequate nitrogen (W₂N₀, W₃N₀, W₃N₁) resulted in negative net benefits in 2023–2024. Optimal irrigation and nitrogen management (W₁N₂) increased net income by 220% and 314% compared to suboptimal irrigation and nitrogen combinations W₃N₃ and W₁N₀, respectively. Net income in 2022–2023 was 216% higher than in 2023–2024, reflecting more favorable growing conditions in the first season.

3.3. Integrated Effects of Irrigation and Nitrogen on Nitrogen Absorption and Nitrogen Use Efficiency

Nitrogen, irrigation, and their interaction significantly influenced nitrogen uptake and use efficiency at harvest (p < 0.05; Figure 4,

Table 6. Interactive effects of irrigation regimes and nitrogen application rates on nitrogen use efficiency indicators of winter rapeseed during 2022–2023 and 2023–2024.

Treatment	NAE (kg/kg)		NPE (kg/kg)		NRE%		NPFP (kg/kg)
	2022–2023	2023–2024	2022–2023	2023–2024	2022–2023	2023–2024	2022–2023	2023–2024
W1N0	——	——	——	——	——	——	——	——
W1N1	10.65 b	5.86 bc	21.83 cd	18.80 cd	49.35 b	31.29 b	42.84 a	27.43 a
W1N2	15.97 a	9.34 a	25.83 a	22.54 a	61.96 a	41.27 a	32.07 c	20.13 c
W1N3	11.07 b	6.94 b	24.11 ab	20.93 ab	45.92 b	33.22 b	21.81 f	14.13 e
W2N0	——	——	——	——	——	——	——	——
W2N1	9.73 c	5.49 cd	21.73 cd	18.36 cd	45.14 b	29.81 bcd	34.87 b	23.21 b
W2N2	10.57 b	6.06 bc	23.36 bc	19.52 bc	45.69 c	90.92 bc	23.14 e	14.92 e
W2N3	7.51 d	4.58 d	21.42 cde	17.88 cd	35.19 b	25.55 cd	15.89 h	10.48 g
W3N0	——	——	——	——	——	——	——	——
W3N1	4.59 e	3.21 e	19.55 de	16.85 d	23.44 d	19.41 e	26.72 d	18.66 d
W3N2	6.89 d	4.37 de	20.70 de	17.60 cd	33.44 c	24.83 d	17.95 g	12.09 f
W3N3	4.72 e	3.19 e	19.16 e	16.91 d	24.70 d	18.91 e	12.10 i	8.34 h
Significant test
W	**	**	**	**	**	**	**	**
N	**	**	**	**	**	**	**	**
W × N	**	**	*	*	**	**	**	**

Note: NAE, NPE, NRE, and NPFP represent nitrogen agronomic efficiency, nitrogen physiological use efficiency, nitrogen recovery efficiency, and nitrogen partial factor productivities, respectively. Different letters within columns indicate significant differences among treatments (LSD test, p < 0.05). * and ** denote significance at p < 0.05 and p < 0.01, respectively. “——” indicates the treatment was not applicable.

). Plant nitrogen uptake increased proportionally with nitrogen application, with N₁, N₂, and N₃ increasing the two-year average by 26.1%, 62.7%, and 72.5%, respectively, compared to the control. Higher irrigation levels (W₁ and W₂) further enhanced uptake by 44.3% and 18.0%, respectively, compared to deficit irrigation (W₃). Nitrogen partitioning among organs followed the pattern pod (69.0–75.4%) > stem (18.7–23.0%) > leaf (5.5–7.4%), with pods dominating total nitrogen accumulation.

Nitrogen use efficiency indicators (NAE, NPE, NRE, and NPFP) exhibited distinct response patterns. NAE, NPE, and NRE showed quadratic responses to nitrogen application, with maximum values at N₂. The N₃ treatment reduced the two-year average NPE by 7.1% and NRE by 22.9% compared to N₂, indicating diminishing returns at higher nitrogen rates. In contrast, NPFP peaked at N₁, declining by 32.0–52.4% under N₂ and N₃. Higher irrigation levels consistently enhanced all nitrogen efficiency parameters, with W₁ and W₂ increasing NAE by 62.9% and 121.8%, NPE by 21.0% and 10.4%, and NRE by 46.7% and 81.4%, respectively, compared to W₃. Notably, the W₁N₂ treatment optimized nitrogen use efficiency, increasing NAE, NPE, NRE, and NPFP by 40.5%, 7.4%, 30.4%, and 45.2%, respectively, compared to W₁N₃, demonstrating that moderate nitrogen application under adequate irrigation achieves the best balance between productivity and nitrogen efficiency.

3.4. Integrated Effect of Nitrogen and Irrigation on Water Consumption and Water Use Efficiency

Winter rapeseed evapotranspiration (ET), water use efficiency (WUE), and irrigation water use efficiency (IWUE) were significantly influenced by irrigation, nitrogen, and their interaction (p < 0.01;

Table 7. Interactive effects of irrigation regimes and nitrogen application rates on water consumption (ET), water use efficiency (WUE), and irrigation water use efficiency (IWUE) of winter rapeseed during 2022–2024.

Treatment	ET (mm)		WUE (kg m−3)		IWUE (kg m−3)
	2022–2023	2023–2024	2022–2023	2023–2024	2022–2023	2023–2024
W1N0	370.5 d	363.8 c	7.0 f	4.7 d	9.0 g	5.8 fg
W1N1	381.0 c	375.7 b	9.0 c	5.8 c	11.9 d	7.3 d
W1N2	408.9 b	388.5 a	12.5 a	8.3 a	17.8 a	10.7 a
W1N3	420.8 a	397.4 a	12.4 a	8.5 a	18.2 a	11.3 a
W2N0	357.3 fg	339.9 ef	5.6 h	4.2 de	7.9 h	5.3 g
W2N1	366.7 de	348.4 de	7.6 e	5.3 c	11.0 e	6.9 de
W2N2	370.0 d	356.5 cd	10.0 b	6.7 b	14.5 b	8.8 bc
W2N3	381.5 c	367.0 bc	10.0 b	6.8 b	15.0 b	9.3 b
W3N0	337.1 i	333.5 f	5.3 i	3.7 e	8.3 h	5.3 g
W3N1	346.2 h	339.9 ef	6.2 g	4.4 d	10.0 f	6.4 ef
W3N2	351.2 gh	348.7 de	8.2 d	5.6 c	13.5 c	8.3 c
W3N3	359.7 ef	351.0 de	8.1 d	5.7 c	13.6 c	8.5 c
Significance test
W	**	**	**	**	**	**
N	**	**	**	**	**	**
W × N	**	ns	**	**	**	**

Note: Data are expressed as mean deviation of treatments (n = 3), with different letters representing significant differences (p < 0.05). ** indicates p < 0.01, and ns indicates not significant.

). ET ranged from 337.1 to 420.8 mm (2022–2023) and 333.5 to 397.4 mm (2023–2024), increasing progressively with higher irrigation and nitrogen levels, though no differences existed between N₂ and N₃. WUE (5.3–12.5 kg m⁻³ in 2022–2023; 3.7–8.5 kg m⁻³ in 2023–2024) and IWUE (maximum 18.2 and 11.3 kg m⁻³, respectively) responded positively to both irrigation and nitrogen management. Nitrogen fertilization increased WUE by 23.3–72.3% and IWUE by 29.0–83.2% compared to the control, with maximum values at N2 and N3. Higher irrigation levels (W₁ and W₂) further enhanced WUE by 41.7–47.8% and 19.0–20.1%, and IWUE by 24.7% and 6.6%, respectively, compared to deficit irrigation (W₃). Notably, under zero nitrogen conditions, W₂ and W₃ showed no significant IWUE differences, indicating that irrigation benefits require adequate nitrogen availability. The W₁N₂ treatment optimized water productivity, improving WUE by 131% and IWUE by 110% compared to W₃N₀, underscoring the importance of synchronized water–nitrogen management for maximizing water use efficiency in rapeseed production.

3.5. Integrated Effect of Irrigation and Nitrogen on Soil Nitrate Nitrogen Residue

Soil nitrate nitrogen residual (SNR) at harvest was significantly affected by irrigation and nitrogen management, with 72.9–74.5% concentrated in the upper 0–60 cm soil layer across both seasons (Figure 5). SNR increased with higher nitrogen rates and lower irrigation levels, exhibiting a unimodal distribution with depth. Peak nitrate concentrations shifted to shallower layers under reduced irrigation, occurring at approximately 20, 30, and 40 cm depths under W₁, W₂, and W₃, respectively. The N₃ treatment increased SNR by 9.69–29.2% compared to lower nitrogen rates, while higher irrigation (W₁) reduced SNR by 28.3–38.7% compared to W₂ and W₃, indicating enhanced nitrogen uptake and leaching under adequate water supply. The W₁N₂ treatment achieved optimal nitrogen utilization, reducing SNR by 12% compared to W₁N₃ while maintaining high yield and nitrogen efficiency.

3.6. Integrated Effects of Nitrogen and Irrigation on Seed Protein and Oil Contents

Irrigation and nitrogen significantly influenced seed protein and oil contents (p < 0.01), with significant interactions for oil content in both years and protein content in 2022–2023 (

Table 8. Interactive effects of irrigation regimes and nitrogen application rates on seed quality of winter rapeseed during 2022–2023 and 2023–2024.

Treatment	2022–2023		2023–2024
	Oil Content %	Protein %	Oil Content %	Protein %
W1N0	41.32 cd	28.11 de	45.41 bc	28.84 cde
W1N1	40.79 de	28.65 bc	44.76 cd	28.97 cd
W1N2	40.23 ef	29.09 b	42.34 f	29.72 ab
W1N3	39.71 f	29.84 a	40.95 g	29.94 a
W2N0	42.19 b	27.65 e	46.62 a	28.35 e
W2N1	41.18 cd	28.42 cd	45.38 bc	28.93 cd
W2N2	40.58 de	28.94 b	43.7 de	29.33 bc
W2N3	40.35 ef	29.01 b	43.07 ef	29.37 bc
W3N0	43.98 a	26.80 f	46.64 a	27.00 f
W3N1	41.79 bc	27.81 e	46.00 ab	28.59 de
W3N2	41.00 de	28.44 cd	45.10 bc	29.10 cd
W3N3	40.90 de	28.71 bc	45.06 bc	29.04 cd
Significance test
W	**	**	**	**
N	**	**	**	**
W × N	**	ns	**	*

Note: Data are expressed as mean ± standard deviation of treatments (n = 3), with different letters representing significant differences (p < 0.05). ** indicates p < 0.01, * indicates p < 0.05, and ns indicates not significant.

). Seed oil content (39.71–43.98% in 2022–2023; 40.95–46.64% in 2023–2024) decreased with increasing nitrogen (1.8–6.9% reduction vs. control) and irrigation (W₁ and W₂ reduced oil by 5.1% and 2.0–2.2%, respectively, vs. W₃). Conversely, protein content (26.80–29.84% in 2022–2023; 27.00–29.94% in 2023–2024) increased with nitrogen fertilization (2.7–6.1%) and irrigation (W₁ and W₂ by 3.3–3.5% and 2.0%, respectively). These inverse responses reflect the oil–protein biosynthesis trade-off, where high nitrogen and water availability favor protein synthesis over oil accumulation.

3.7. Comprehensive Evaluation Using TOPSIS Model

The TOPSIS-based comprehensive evaluation, integrating soil nitrate residual (SNR), water use efficiency (WUE), and nitrogen use efficiency (NUE), revealed consistent treatment rankings across both seasons (

Table 9. Euclidean distances and comprehensive evaluation index (CEI) of irrigation-nitrogen treatments determined by entropy-TOPSIS model.

2022–2023					2023–2024
Treatments	D+	D−	CEI	Rank	Treatments	D+	D−	CEI	Rank
W1N0	0.181	0.175	0.492	4	W1N0	0.175	0.174	0.498	4
W1N1	0.130	0.165	0.559	3	W1N1	0.134	0.156	0.537	3
W1N2	0.086	0.244	0.740	1	W1N2	0.087	0.226	0.721	1
W1N3	0.123	0.239	0.661	2	W1N3	0.123	0.230	0.653	2
W2N0	0.223	0.134	0.376	8	W2N0	0.209	0.135	0.392	7
W2N1	0.183	0.112	0.379	7	W2N1	0.178	0.110	0.382	8
W2N2	0.155	0.145	0.483	5	W2N2	0.156	0.134	0.463	5
W2N3	0.182	0.142	0.439	6	W2N3	0.180	0.136	0.430	6
W3N0	0.240	0.123	0.338	9	W3N0	0.231	0.123	0.347	9
W3N1	0.229	0.080	0.260	11	W3N1	0.218	0.081	0.271	12
W3N2	0.203	0.087	0.300	10	W3N2	0.198	0.085	0.301	10
W3N3	0.228	0.080	0.259	12	W3N3	0.220	0.083	0.274	11

). W₁N₂ (90% FC with moderate nitrogen) achieved the highest comprehensive evaluation index (CEI: 0.740 in 2022–2023; 0.721 in 2023–2024) and ranked first in both years, indicating an optimal balance between minimizing soil nitrate residual and maximizing water and nitrogen use efficiencies. W₁N₃ ranked second (CEI: 0.661 and 0.653) and W₁N₁ ranked third (CEI: 0.559 and 0.537), demonstrating that adequate irrigation (90% FC) consistently produced superior performance across different nitrogen levels. In contrast, deficit irrigation treatments (W₃) ranked lowest, with W₃N₃ (CEI: 0.259) and W3N1 (CEI: 0.271) showing the poorest performance in 2022–2023 and 2023–2024, respectively. These results demonstrate that adequate irrigation combined with moderate nitrogen input (W₁N₂) optimizes the trade-offs among environmental sustainability (low SNR) and resource use efficiency (high WUE and NUE), whereas severe water deficit negates nitrogen fertilization effectiveness.

4. Discussion

Winter rapeseed production is highly sensitive to both water and nitrogen availability, making optimization of their interactive effects essential for maximizing seed yield, seed quality, and economic returns in sustainable production systems. This study provides comprehensive evidence of water–nitrogen synergies affecting crop growth, physiological processes, yield formation, resource use efficiency, and environmental sustainability.

4.1. Crop Growth, Physical Performance, and Resource Allocating

4.1.1. Crop Growth and Root Morphology

Plant height and stem diameter serve as readily measurable indicators of crop vigor and developmental status. Our results demonstrated that both parameters increased progressively with nitrogen application up to 160 kg N ha⁻¹, with no significant additional benefits at 240 kg N ha⁻¹, particularly under adequate irrigation conditions (W₁). Similarly, higher irrigation frequency consistently enhanced vegetative growth across all nitrogen rates. These findings align with previous research demonstrating that increasing nitrogen application and irrigation enhance plant stature and stem thickness, though responses plateau beyond certain thresholds [53,54]. The lack of a significant difference between 160 and 240 kg N ha⁻¹ suggests that nitrogen requirements for vegetative growth are satisfied at moderate application rates, with diminishing marginal returns at higher rates, which is an important consideration for both economic efficiency and environmental stewardship.

Root system development is fundamental to crop performance, serving as the primary organ for water and nutrient acquisition. Previous studies demonstrate that nitrogen fertilization (up to 240 kg N ha⁻¹) significantly enhances root length, surface area, volume, and dry weight [12], while irrigation similarly promotes root growth and biomass [55]. In the present study, nitrogen application increased root length, surface area, volume, and diameter, with optimal responses at 160 kg N ha⁻¹, reflecting nitrogen’s essential role in protein synthesis, cell division, and the metabolic processes driving root development [56,57]. Interestingly, reduced irrigation (W₃) increased root length, surface area, and volume compared to W₁. Previous research showed that root length density at 20–40 cm depths increased under water-limited conditions [58], as intensified water competition stimulated deeper root growth to access subsoil moisture [59]. This adaptive strategy demonstrates how plants invest more resources in root proliferation under water stress to enhance water and nutrient foraging capacity, particularly in drought-prone environments.

4.1.2. Biomass Accumulation and Canopy Development

Aboveground dry matter accumulation responded positively to increasing nitrogen levels and higher irrigation frequencies, though no significant difference was observed between 160 and 240 kg N ha⁻¹ treatments. This finding is consistent with previous studies reporting that irrigation and nitrogen fertilization significantly enhance aboveground biomass production [60,61,62]. The underlying mechanisms are well-established: adequate water availability optimizes photosynthetic and cellular processes by maintaining favorable leaf water status and stomatal conductance, while nitrogen is essential for chlorophyll synthesis, protein production, and enzyme activity, all contributing to enhanced vegetative growth and tissue development.

Leaf area index exhibited similar responses, increasing progressively with both nitrogen application (up to 160 kg N ha⁻¹) and irrigation frequency. The W₁N₂ treatment achieved LAI values comparable to W₁N₃, indicating that moderate nitrogen application combined with adequate irrigation supports optimal canopy development [63]. Enhanced LAI directly translates to greater light interception capacity and photosynthetic productivity, establishing the foundation for superior yield potential [64]. The significant water × nitrogen interactions observed for LAI at multiple growth stages (Figure 3) underscore the synergistic nature of these inputs in driving canopy expansion.

4.1.3. Photosynthetic Performance and Chlorophyll Fluorescence

Enhanced photosynthetic capacity is crucial for increasing agricultural productivity [65], though photosynthetic efficiency depends on multiple environmental factors, including soil moisture, temperature, nutrient availability, and stomatal regulation [66,67,68]. In this study, P_n, g_s, and T_r increased significantly with nitrogen application up to 160 kg N ha⁻¹ and with higher irrigation frequency (W₁). These responses reflect the fundamental roles of water and nitrogen in photosynthesis: nitrogen is essential for chlorophyll, Rubisco, and electron transport proteins [69], while adequate water maintains stomatal opening and mesophyll conductance for CO₂ diffusion.

Beyond 160 kg N ha⁻¹, nitrogen availability likely exceeded the crop’s physiological capacity, resulting in saturation, i.e., additional inputs no longer enhanced leaf development or photosynthetic efficiency. This aligns with previous research showing that optimal water and nitrogen application substantially enhances crop leaf area and photosynthetic rate through improved carbon-nitrogen metabolism [70,71]. However, excessive nitrogen may induce osmotic stress or luxury consumption without corresponding photosynthetic gains, explaining the plateau in P_n, g_s, and T_r observed between N₂ and N₃ treatments.

Chlorophyll fluorescence parameters provide sensitive indicators of photosynthetic function and stress responses. Fv/Fm, ΦPSII, and qP increased with nitrogen application up to 160 kg N ha⁻¹ and higher irrigation frequency, while NPQ decreased, indicating reduced heat dissipation and enhanced photochemical efficiency. These findings support previous research showing that supplementary irrigation improved Fv/Fm by 6.57% and qP by 9.14% compared to rainfed conditions [72]. The decline in NPQ under adequate water and nitrogen supply reflects reduced photoinhibition and improved utilization of absorbed light energy for photochemistry rather than thermal dissipation. The interactive effects of irrigation and nitrogen on fluorescence parameters (Table 2 and Table 3) demonstrate that optimal photosynthetic function requires coordinated management of both resources.

4.2. Yield Formation, Seed Quality, and Economic Performance

Nitrogen and irrigation significantly influenced all yield components, with yields ranging from 1771 kg ha⁻¹ (W₃N₀) to 5234 kg ha⁻¹ (W₁N₃) in 2022–2023. Notably, yields at 160 and 240 kg N ha⁻¹ under W₁ irrigation did not differ significantly, suggesting 160 kg N ha⁻¹ represents an economically and environmentally optimal rate with adequate irrigation. These findings align with previous studies showing rapeseed yield increases with higher irrigation while reduced nitrogen decreases yield through reductions in pod number, seeds per pod, and seed weight [11]. The synergistic interaction between irrigation and nitrogen maximizes photosynthetic capacity and final yield [73]. The 27.6% reduction in branch number during 2023–2024 compared to 2022–2023 reflects inter-seasonal climatic variation, particularly 22% lower precipitation, emphasizing the importance of supplementary irrigation for stabilizing production.

Seed quality parameters showed contrasting responses, reflecting the inverse relationship between oil and protein accumulation. Nitrogen application progressively reduced oil content (by up to 5.1%) while increasing protein content (by up to 6.1%), consistent with previous research [47,74]. Higher irrigation similarly decreased oil concentration but enhanced protein accumulation. Conversely, drought stress reduced photosynthetic carbon assimilation through stomatal closure, limiting substrate availability for oil biosynthesis [75]. This irrigation effect contrasts with some reports showing increased oil content under well-watered conditions [76,77], possibly because consistently high soil moisture (W₁) favored vegetative growth and protein synthesis over lipid biosynthesis, while moderate water stress (W₃) prioritized carbon allocation to oil as an energy storage strategy.

Economic analysis revealed net benefits ranging from −1845 to 23,199 CNY ha⁻¹, with several low-input treatments yielding negative returns in 2023–2024, demonstrating that minimum input thresholds are essential for viability. The W₁N₂ treatment achieved net benefits of 22,770 and 10,270 CNY ha⁻¹, only 1.5% and 7.2% lower than W₁N₃ despite reducing nitrogen input by 33%, reflecting diminishing marginal returns beyond 160 kg N ha⁻¹. The 216% higher net income in 2022–2023 versus 2023–2024 underscores the critical role of seasonal rainfall in profitability and the value of flexible irrigation management adjusted to the in-season conditions. These findings align with previous studies showing that optimized nitrogen and irrigation rates maximize crop economic benefits [78,79].

4.3. Resource Use Efficiency and Environmental Sustainability

Water stress limits nitrogen uptake by reducing root activity, transpiration-driven mass flow, and active transport. In this experiment, the W₁ and W₂ treatments increased nitrogen uptake by 44.3% and 18.0% compared to W₃, confirming that an adequate water supply is essential for nitrogen acquisition [80]. Increasing nitrogen application further enhanced uptake by 26.1%, 62.7%, and 72.5% relative to N₀. The highest NPFP values occurred at 80 kg N ha⁻¹ under W1, while NAE, NPE, and NRE declined beyond 160 kg N ha⁻¹ (Table 6). Consistent with our results, previous studies have shown that excessive nitrogen reduces nitrogen use efficiency [81,82], whereas optimal irrigation–nitrogen management improves overall efficiency [83]. High nitrogen rates can lower uptake efficiency through luxury consumption and potential toxicity, while adequate irrigation increases nitrogen solubility and root absorption and reduces losses via leaching and volatilization. In this study, water use efficiency increased with nitrogen application up to 160 kg ha⁻¹ but declined under water-limited conditions (W₃). Overall, balanced water and nitrogen inputs improved nutrient use and photosynthesis, enhancing root-zone infiltration and crop water productivity [60,84].

Soil nitrate residual distribution and magnitude are governed by the interactive effects of irrigation and nitrogen fertilization, with important implications for environmental sustainability. Consistent with previous studies, soil nitrate residual increased with higher N application rates [85,86]; however, its interaction with irrigation revealed a more complex response. Under deficit irrigation (W₃) and contrary to Amare et al. [87], nitrate residual was unexpectedly higher than under W₁ and W₂, likely due to reduced nutrient uptake efficiency. Adequate irrigation (W₁) improved water availability and enhanced plant nitrogen uptake, thereby reducing soil nitrate accumulation [11,22]. In contrast, the water-limited conditions in W₃ constrained plant growth and nitrogen acquisition, resulting in greater residual nitrate despite lower productivity, raising concerns about long-term accumulation and off-season leaching. Most soil nitrate (72.9–74.5%) was concentrated in the 0–60 cm soil layer, indicating limited downward movement under the applied irrigation regimes. Nevertheless, elevated surface-layer nitrate—particularly under high nitrogen inputs—poses environmental risks, including groundwater contamination during rainfall events and increased greenhouse gas emissions via denitrification [88,89,90]. Therefore, coordinated optimization of irrigation and nitrogen management is essential to enhance crop nitrogen uptake, reduce environmental risks, and improve nitrogen use efficiency and agroecosystem sustainability [83,91].

4.4. Trade-Offs and Recommendations

The entropy-TOPSIS comprehensive evaluation identified W₁N₂ (90% FC with 160 kg N ha⁻¹) as the optimal irrigation-nitrogen management strategy for winter rapeseed in semi-arid regions. While W₁N₃ (90% FC with 240 kg N ha⁻¹) achieved maximum yield (5234 and 3391 kg ha⁻¹) and net income (23,119 and 11,062 CNY ha⁻¹) in 2022–2023 and 2023–2024, respectively, this yield-maximizing approach imposed substantial agronomic and environmental costs. W₁N₂ demonstrated markedly superior nitrogen use efficiency (28.6% higher) and substantially reduced residual soil nitrate (12% lower), critical indicators of long-term soil health and groundwater protection. The agronomic trade-off was minimal: only 3.3% yield reduction and 3.4% income loss compared to W₁N₃, while achieving 96.7% of maximum yield with 33.3% less nitrogen input. This strategy proved particularly advantageous given current regulatory pressures on nitrogen pollution and the growing recognition that sustainable intensification requires balancing productivity with environmental stewardship in semi-arid systems.

W₁N₂ represents the most pragmatic management approach by optimizing the balance among yield maximization, nitrogen use efficiency, and economic return. The modest sacrifice in profitability (3.4%) yields substantial environmental gains through improved resource use efficiency and reduced nitrogen loss, positioning this strategy as both economically defensible and environmentally responsible for winter rapeseed cultivation in semi-arid regions.

5. Conclusions

This study demonstrates that synchronized irrigation and nitrogen management are fundamental for optimizing winter rapeseed production under semi-arid conditions. The W₁N₂ treatment achieved optimal seed yield while maximizing nitrogen use efficiency compared to higher nitrogen rates (N₃), representing a superior balance between productivity and resource efficiency. Consistent with the entropy-TOPSIS evaluation, W₁N₂ achieved the highest overall performance among all treatment combinations. This treatment combination enhanced nitrogen uptake and utilization while substantially reducing soil nitrate residual, thereby mitigating potential environmental risks. The findings indicate that maintaining adequate soil moisture (90% FC) enables reduced nitrogen inputs without a yield penalty, as improved water availability enhances nitrogen acquisition efficiency. From a practical perspective, the W₁N₂ strategy offers a sustainable approach for winter rapeseed cultivation in semi-arid regions by achieving the dual objectives of high productivity and environmental stewardship through optimized resource management.