Elevated Nitrogen Fertilization Compromises Lodging Resistance in High-Quality, Late-Season Indica Rice Grown in Southern China

Abstract

While nitrogen is essential for rice production, excessive application promotes lodging, threatening yield stability. In this study, we evaluated the impact of three nitrogen application rates (105, 165, and 225 kg ha⁻¹) on yield formation and lodging resistance in two elite late-season indica rice varieties—Meixiangzhan 2 (MXZ2) and Taiyou 871 (TY871). Our findings demonstrate that (1) elevated nitrogen increased productive panicle number but reduced grains per panicle and percentage of filled grains. (2) High nitrogen inputs substantially elevated the lodging risk, with the lodging index increasing by 20.4% and 45.7% in MXZ2, and by 15.4% and 38.3% in TY871, at 165 and 225 kg ha⁻¹, respectively. (3) Reduced mechanical strength—associated with impaired morphological structure (e.g., increased plant height and height of gravity center), diminished structural carbohydrate content in sheaths and culms, and expanded pith cavity area—collectively contributed to the increased lodging susceptibility with elevated nitrogen. (4) MXZ2, though lower-yielding, exhibited greater lodging resistance than TY871, owing to its superior culm anatomy and sheath strength. (5) Interannual climate variation—particularly low temperature and light intensity in 2020—amplified the negative effects of high nitrogen. Our results provide insights into nitrogen-driven trade-offs between yield and lodging, supporting tailored nitrogen management strategies for indica rice under varying environmental conditions.

1. Introduction

Rice stands as one of the three principal cereal crops, accounting for the dietary foundation of over 50% of world’s population [1]. In recent years, growing consumer emphasis on culinary quality has driven a consistent expansion in the planting of premium rice varieties [2]. Nevertheless, lodging represents a critical constraint in high-quality rice production, severely limiting yield potential [3]. Beyond incurring yield losses of 20–30%, lodging also detrimentally affects grain quality and diminishes mechanized harvesting efficiency [4]. Consequently, developing agronomic strategies to mitigate lodging in superior rice genotypes has become an urgent priority.

Lodging is defined as the permanent displacement of crop culms from their upright position. It is generally categorized into two distinct types: culm lodging and root lodging [5]. In rice production, culm lodging occurs more frequently, primarily due to structural weaknesses in the lower internodes—such as reduced culm diameter and underdeveloped mechanical tissues—that compromise culm strength [6]. The fundamental predisposition to lodging is governed by genotype, though its expression is significantly modulated by environmental conditions and agronomic practices.

The genetic characteristics of a variety (i.e., its genotype) are closely associated with culm mechanical strength [6]. Susceptible varieties are typically characterized by poor filling of the culm and sheath, as well as thin and weak culms. Significant genotypic variation exists in lodging-related traits such as breaking resistance, wall thickness, lodging index, culm diameter, and culm material properties [7]. Key criteria for breeding lodging-resistant varieties include high culm material strength, appropriate plant height, greater culm coarseness, and shortened basal internode length [8].

As a key agronomic practice, excessive nitrogen application exacerbates lodging in rice, posing a significant challenge to production [9]. Nitrogen substantially affects lodging-related traits: studies show that higher nitrogen reduces modulus of elasticity and breaking strength, increasing the lodging index [4]. Research showed that central rows exhibit enhanced culm stiffness—reducing lodging in wheat—though no significant difference was found between low and high nitrogen treatments [10]. Breaking resistance comprises bending stress and section modulus. Low nitrogen raises bending stress, improving culm material strength, while nitrogen manipulation alters section modulus in hybrid indica rice, affecting basal internode strength [11]. Moderately reducing nitrogen also enhances lodging resistance in japonica rice [12]. Mechanisms underlying nitrogen-driven lodging variation depend strongly on ecological conditions, necessitating context-specific nitrogen management strategies.

Nitrogen application significantly affects rice culm morphology [13]. Excessive nitrogen promotes overcrowding and weakens basal internodes, reducing culm thickness and filling degree, and consequently lowering breaking resistance [14]. Studies indicate that avoiding basal nitrogen fertilizer and optimizing planting density can shorten basal internodes and improve lodging resistance in tall varieties [8]. Responses to nitrogen vary regionally: in Liaoning, high nitrogen increases plant height and elevates the center of gravity [15], while reducing wall thickness and culm diameter. In high-yield zones, it primarily decreases filling degree of basal culms and sheaths [16].

Nitrogen critically regulates crop lodging resistance through multiple mechanisms. In rice, moderate nitrogen reduction strengthens stems by enhancing mechanical tissue thickness and vascular bundle development [17]. Conversely, maize under high nitrogen shows weakened sclerenchyma and expanded pith with thinner walls [18]. Nitrogen management significantly affects stem filling-reduced nitrogen with potassium elevates soluble sugars and optimizes C/N ratio [19], boosting both yield and lodging resistance. However, excess nitrogen reduces lignification in oats and lignin in wheat, while decreasing cellulose and starch contents, collectively increasing lodging risk [4]. Research reveals an optimal nitrogen range: stem C/N ratio, cellulose content and lodging resistance initially improve then decline with increasing nitrogen, consistently correlating with mechanical strength [4]. However, no consistent correlation between carbohydrate content and lodging index was found in wheat under varying nitrogen.

In summary, the effect of nitrogen application rates on lodging resistance in different high-quality late-season indica rice varieties remains insufficiently explored and poorly understood at a syntagmatic level. This study aims to (1) investigate the effects of nitrogen application rates on the lodging resistance by evaluating rice agronomic, morphological, and biochemical characteristics under the humid subtropical monsoon climate in southern China; and (2) develop variety-specific nitrogen management strategies that optimize the trade-off between grain yield and lodging risk in this predominant rice-growing region.

2. Materials and Methods

2.1. Experimental Design

Field experiments were conducted in Zengjia Village, Shanggao County, Jiangxi Province (115°09′ E, 28°31′ N) during the rice growing seasons of 2019 and 2020. The region experiences a humid subtropical monsoon climate, with a mean annual temperature of 17.5 °C, precipitation of 1650 mm, sunshine duration of 1500 h, and a frost-free period of 270 days. Monthly precipitation as well as maximum and minimum temperatures from April 2019 to November 2020 are presented in Figure S1. The experimental soil was classified as sandy clay loam. Soil physicochemical properties in the 0–20 cm layer were as follows: In 2019, pH 6.04 (soil:water = 1:2.5), organic matter 41.4 g kg⁻¹, available phosphorus 19.8 mg kg⁻¹, available potassium 124.0 mg kg⁻¹, alkali-hydrolyzable nitrogen 196.0 mg kg⁻¹, total nitrogen 2.35 g kg⁻¹. In 2020, pH 5.85 (soil:water = 1:2.5), organic matter 41.0 g kg⁻¹, available phosphorus 19.8 mg kg⁻¹, available potassium 125.1 mg kg⁻¹, alkali-hydrolyzable nitrogen 214.2 mg kg⁻¹, total nitrogen 2.86 g kg⁻¹.

Two late-season indica rice varieties with contrasting lodging resistance were selected: Meixiangzhan 2 (MXZ2, low lodging index) and Taiyou 871 (TY871, high lodging index). Three nitrogen (N) application rates were tested: 105 (N1), 165 (N2), and 225 (N3) kg ha⁻¹. The experiment followed a randomized complete block design with three replications, resulting in a total of 18 plots. Each plot measured 30 m² (5 m × 6 m). Adjacent plots were separated by 50 cm-wide, 40 cm-high ridges covered with plastic film to prevent water and nutrient exchange, ensuring independent irrigation and drainage for each plot. Nitrogen was applied in a split ratio of 5:2:3 as basal, tillering, and panicle fertilizers. Fertilizers used were urea (46.4% N), calcium superphosphate (12% P₂O₅), and potassium chloride (60% K₂O). Phosphorus (P₂O₅) was applied at 82.5 kg·ha⁻² entirely as basal fertilizer, while potassium (K₂O) was applied at 165 kg·ha⁻² in a basal: panicle = 5:5 split. Basal fertilizer was applied one day before transplanting, tillering fertilizer at 7 days after transplanting, and panicle fertilizer at stage IV of young panicle differentiation. Seeding was conducted on 20 June 2019, and 24 June 2020, with manual transplanting on 17 July and 20 July, respectively. Planting density was maintained at 14 cm × 25 cm spacing, with three seedlings per hill for MXZ2 and two for TY871. All other field management practices followed local high-yielding cultivation protocols.

2.2. Sampling and Measurements

2.2.1. Yield and Yield Components

At maturity, three samples of 100 hills per plot were randomly selected for yield determination. After threshing and air-drying, grain yield was adjusted to a moisture content of 13.5% to represent the actual yield. Prior to harvest, 90 hills per plot were sampled to determine the number of productive panicles. Based on the average panicle number, five representative hills were selected to measure grains per panicle, percentage of filled grains, and 1000-grain weight.

2.2.2. Mechanical Properties

Lodging-related mechanical traits and morphological parameters were measured 20 days after full heading. In total, 10 main culms were randomly selected from each plot. The following parameters were determined: length above breaking point (SL), fresh weight above breaking point (FW), bending moment (WP), breaking bending moment (M), section modulus (SM), bending stress (BS), and lodging index (LI). The fourth internode from the top was identified and placed on a culm strength tester (YYD-1, Top Instrument Co., Hangzhou, China) with two supports spaced 5 cm apart. A force (F) was applied at the midpoint until fracture occurred. The broken internode was then cut at the fracture point, and its inner and outer diameters along the major and minor axes were measured using a vernier caliper. Mechanical parameters were calculated according to the method described by [20].

$$\mathrm{W}\mathrm{P}=\mathrm{S}\mathrm{L}\times \mathrm{F}\mathrm{W}$$

WP: Bending moment (g·cm). SL: Length above breaking point (cm). FW: Fresh weight above breaking point (g).

$$\mathrm{M}=\mathrm{L}\times {\displaystyle \frac{F}{4}}$$

M (g·cm): Breaking bending moment, indicating the magnitude of breaking resistance. F (kg): Force applied at the fracture point of the basal internode segment. L (cm): Length between the two supporting points.

$$SM={\displaystyle \frac{{a1}^{3}b1-{a2}^{3}b2}{4}}$$

SM (mm³): Section modulus, representing the cross-sectional size of the measured internode. a₁ (mm): Outer diameter along the minor axis. a₂ (mm): Inner diameter along the minor axis. b₁ (mm): Outer diameter along the major axis. b₂ (mm): Inner diameter along the major axis.

$$BS={\displaystyle \frac{M}{SM}}$$

BS (g·mm⁻²): Bending stress, indicating the material strength of the culm.

$$LI={\displaystyle \frac{WP}{M}}$$

LI (%): Lodging index (higher values indicate greater lodging risk).

Biomechanical parameters were calculated for both sheathed and non-sheathed samples using the methods described above. For non-sheathed samples, the contribution rate of the sheath to mechanical properties (%) was calculated as follows:

$$Contributionrate\left(\%\right)={\displaystyle \frac{(Valuewithsheath-Valuewithnon-sheathed)}{Valuewithsheath}}\times 100.$$

A positive contribution rate indicates a strengthening effect of the sheath on the mechanical property, with higher positive values reflecting greater contribution. Conversely, a negative value suggests a weakening effect of the sheath, where greater negative values (lower absolute value) correspond to a stronger adverse impact.

2.2.3. Morphological Traits

At 20 days after full heading, 15 representative main culms with uniform growth were selected from each plot. The following traits were measured: flag leaf angle, second top leaf angle, and third top leaf angle; culm diameter, internode length, plant height, and height of the center of gravity. The center of gravity was determined as the vertical distance from the base of the culm to the balance point of the entire plant (including leaves, sheaths, and panicles). Plant height and individual internode lengths were measured using a ruler. Internodes were designated from top to bottom as IN1 (first top internode), IN2 (second top internode), IN3 (third top internode), IN4 (fourth internode from the top), and IN5 (fifth internode from the top). Upper internodes refer to IN1, IN2, and IN3, while lower internodes refer to IN4 and IN5. The proportional length of upper and lower internodes was calculated as follows:

$$Proportionofupperinternodelength\left(\%\right)={\displaystyle \frac{IN1+IN2+IN3}{IN1+IN2+IN3+IN4+IN5}}\times 100\mathrm{\%}.$$

Culm diameter was measured at the midpoint of the fourth internode (IN4) using a digital caliper with an accuracy of 0.001 mm. The panicle-culm diameter ratio was calculated as follows:

$$Panicle-culmdiameterratio\left(\mathrm{g}\mathrm{c}{\mathrm{m}}^{-1}\right)={\displaystyle \frac{Panicledryweight\left(\mathrm{g}\right)}{Culmdiameter\left(\mathrm{c}\mathrm{m}\right)}},$$

$$Panicleweightperunitculmdiameterandplantheight\left(\mathrm{g}\mathrm{c}{\mathrm{m}}^{-2}\right)={\displaystyle \frac{[Panicle-CulmDiameterRatio(\mathrm{g}\mathrm{c}{\mathrm{m}}^{-2})}{PlantHeight\left(\mathrm{c}\mathrm{m}\right)}}.$$

2.2.4. Carbohydrate and Dry Matter Determination

The fourth internode from the top (IN4) was separated into culm and sheath components. Additionally, the entire plant was divided into culm, leaf, and panicle parts. All samples were placed in an oven at 105 °C for 30 min for deactivation, followed by drying at 75 °C until constant weight was achieved. The dry weights of culm, leaf, and panicle were recorded. The proportional dry matter allocation was calculated for each organ. For example, the culm dry matter proportion was determined as follows:

$$Culmdrymatterproportion\left(\%\right)={\displaystyle \frac{Culmdryweight}{Culmdryweight+Leafdryweight+Panicledryweight}}\times 100.$$

The filling degree of the fourth internode from the top (IN4) was calculated as follows:

$$Internodefillingdegree\left(\mathrm{g}\mathrm{c}{\mathrm{m}}^{-1}\right)={\displaystyle \frac{Dryweight}{internodelength}}.$$

Cellulose content was determined using the anthrone colorimetric method by [21]. The dried samples of the fourth internode (IN4) culm and sheath were ground and passed through an 80-mesh sieve. Approximately 0.1 g of the powdered sample was placed in a test tube, mixed with 5 mL of acetic/nitric acid reagent, and boiled at 100 °C for 30 min. The mixture was then centrifuged at 5000 r/min for 15 min, and the supernatant was discarded. This extraction process was repeated three times until the residue turned white. After pretreatment, 5 mL of 72% sulfuric acid was added to the residue, and the tube was incubated at room temperature for over 12 h. The hydrolyzed solution was transferred to a 50 mL volumetric flask, diluted to volume with distilled water, and mixed with anthrone reagent. Absorbance was measured at 620 nm using a spectrophotometer. Cellulose content was quantified based on a standard curve prepared from glucose solutions.

Lignin content was determined according to the method described by [22]. Briefly, 0.1 g of sample was mixed with 4 mL of 95% (v/v) ethanol in a test tube, extracted for 2 h with centrifugation at 4000 r/min, followed by two additional extractions with 4 mL ethanol (v/v) at 80 °C for 2 h each. The residue was then extracted with 4 mL chloroform at 62 °C for 1 h and air-dried at room temperature. The dried residue was treated with acetyl bromide: acetic acid (4:1, v/v) at 70 °C for 1 h, cooled to room temperature, and 0.3 mL of the mixture was transferred to a 50 mL volumetric flask containing acetic acid (82.76%, v/v), 2 mol L⁻¹ NaOH (17.24%, v/v), and 0.1 mL hydroxylamine hydrochloride. The volume was adjusted to 15 mL with acetic acid, and absorbance was measured at 280 nm. Lignin content was quantified using a standard curve.

Sucrose content was determined following the method of [23]. Briefly, 100 mg of powdered sample was extracted with 8 mL of 80% (v/v) aqueous ethanol at 80 °C for 30 min. After cooling, the mixture was centrifuged at 5000 r/min for 15 min, and the supernatant was collected into a 50 mL volumetric flask. This extraction procedure was repeated three times, and the combined supernatants were diluted to volume with 80% ethanol. The extract was decolorized with activated carbon and filtered. A 0.1 mL aliquot of the purified extract was mixed with 100 μL of 2 mol L⁻¹ NaOH, boiled at 100 °C for 30 min, and cooled. Then, 3.0 mL of 10 mol L⁻¹ HCl and 1.0 mL of 0.1% resorcinol solution were added, and the mixture was incubated at 80 °C for 10 min. Absorbance was measured at 480 nm. Sucrose content was quantified using a sucrose standard curve.

Starch content was determined according to the method of [24]. The residue from the previous centrifugation step was dried at 80 °C, then mixed with 2 mL distilled water and boiled at 100 °C for 15 min. After cooling, 2 mL of 9.6 M HClO₄ was added, and the mixture was shaken for 15 min. The solution was centrifuged at 2000 r/min for 20 min, and the supernatant was collected into a 50 mL volumetric flask. The extraction was repeated three times by adding 2 mL of 4.8 M HClO₄ to the residue each time. The combined supernatants were diluted to volume with distilled water. Anthrone reagent was added, and absorbance was measured at 620 nm. Starch content was quantified using a glucose standard curve.

Carbohydrate content calculation:

$$Carbohydratecontent\left(\mathrm{m}\mathrm{g}\mathrm{c}{\mathrm{m}}^{-1}\right)={\displaystyle \frac{Carbohydratecontent\left(\mathrm{m}\mathrm{g}{\mathrm{g}}^{-1}DW\right)}{Fillingdegree\left(\mathrm{g}\mathrm{c}{\mathrm{m}}^{-1}\right)}}.$$

2.2.5. Anatomical Traits

At 20 days after full heading, five representative main culms per plot were sampled. The fourth internode (IN4) with sheath was excised and processed for paraffin sectioning following [25]. with modifications. The samples were fixed in FAA (70% ethanol, 5% acetic acid, 5% formaldehyde) for >48 h, vacuum-infiltrated (30 min) and stored at 4 °C. After rehydration (graded ethanol series) and HF (15%, 15 d), tissues were dehydrated (ethanol/xylene series), embedded in paraffin, and sectioned at 10 μm. Sections were stained with 1% safranin (2 h), dried, deparaffinized in xylene, and mounted. Microscopic imaging (Nikon SMZ800, Nikon, Tokyo, Japan) and analysis (NIS-Elements D software, V5.41) were used to quantify Number and area of large and small vascular bundles, culm area, sheath area, pith cavity area, and pith cavity ratio.

2.3. Data Processing

All data processing and statistical analyses were conducted using SPSS (Version 27.0, IBM Corp., New York, NY, USA). A general linear model was employed to evaluate the effects of variety, nitrogen application rate, year, and their interactions. Normality of residuals was verified using the Shapiro–Wilk test. For data violating normality assumptions, nonparametric alternatives were applied. Results are reported as arithmetic means ± standard error (SE). Significance levels are denoted as * p < 0.05, ** p < 0.01, and ns (not significant).

3. Results

3.1. Effects of Nitrogen Application Rate on Yield and Yield Components of High-Quality Late-Season Indica Rice

Nitrogen application significantly affected yield and its components in both varieties (

Table 1. Effects of nitrogen application rate on yield and yield composition of high-quality late indica rice.

Year	Variety	Nitrogen	Productive Panicles (No. m2)	Grains per Panicle (No.)	Percentage of Filled Grains (%)	1000-Grain Weight (g)	Yield (t hm−2)
2019	MXZ2	N1	335 ± 7.01 c	125 ± 2.73 d	83.3 ± 0.50 a	18.3 ± 0.28 d	7.96 ± 0.16 de
		N2	383 ± 9.77 b	117 ± 1.75 de	82.9 ± 2.92 a	17.8 ± 0.26 de	8.84 ± 0.32 bc
		N3	435 ± 6.27 a	108 ± 1.92 ef	79.2 ± 3.79 ab	17.7 ± 0.12 e	9.19 ± 0.12 ab
	TY871	N1	237 ± 6.44 f	180 ± 2.49 b	73.5 ± 2.14 bc	23.1 ± 0.09 a	8.28 ± 0.29 cd
		N2	256 ± 2.48 ef	162 ± 4.25 c	69.8 ± 0.42 c	23.0 ± 0.14 ab	9.52 ± 0.32 a
		N3	301 ± 9.37 d	156 ± 4.05 c	69.0 ± 1.79 c	22.8 ± 0.13 abc	9.74 ± 0.10 a
2020	MXZ2	N1	421 ± 12.4 a	119 ± 6.19 de	62.5 ± 0.51 d	16.6 ± 0.07 f	6.64 ± 0.11 g
		N2	440 ± 11.1 a	122 ± 3.16 d	58.5 ± 3.07 de	16.9 ± 0.24 f	7.19 ± 0.08 fg
		N3	448 ± 16.5 a	103 ± 1.90 f	50.9 ± 1.76 f	15.9 ± 0.06 g	5.27 ± 0.26 h
	TY871	N1	281 ± 8.25 de	201 ± 3.50 a	58.2 ± 2.01 de	22.3 ± 0.14 c	6.93 ± 0.14 fg
		N2	287 ± 5.72 d	198 ± 4.20 a	54.3 ± 1.98 ef	22.5 ± 0.18 bc	7.54 ± 0.19 ef
		N3	298 ± 6.92 d	177 ± 7.41 b	43.7 ± 0.60 g	22.6 ± 0.19 abc	7.08 ± 0.25 fg
Three-way ANOVA
		Year (Y)	52.8 **	24.7 **	303 **	94.0 **	278 **
		Variety (V)	654 **	697 **	42.7 **	2956 **	26.7 **
		Nitrogen (N)	33.6 **	23.8 **	16.8 **	4.16 *	13.4 **
		Y × V	7.08 *	32.3 **	5.43 *	23.0 **	1.38
		Y × N	11.6 **	3.47 *	4.55 *	2.10	20.8 **
		V × N	1.87	1.22	0.20	3.99 *	4.13 *
		Y × V × N	0.58	0.15	0.47	2.72	3.55 *

Data are presented as mean ± SE. Different lowercase letters indicate significant differences at p < 0.05. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). In 2019, yield of MXZ2 and TY871 increased consistently with nitrogen level, while in 2020 it first increased then declined. Higher nitrogen increased productive panicles but reduced grains per panicle and percentage of filled grains. Compared to N1, N3 raised panicle number but lowered grain number and filled grains in both varieties. Yield components varied significantly between years due to climate conditions (Table 1). The 2020 season had lower temperature, higher rainfall, and less sunshine during grain filling, resulting in reduced percentage of filled grains. Both varieties showed significantly lower yield, percentage of filled grains, and 1000-grain weight in 2020 compared to 2019.

3.2. Effects of Nitrogen Application on Mechanical Properties

Nitrogen application significantly affected the mechanical properties of both rice varieties (

Table 2. Effect of different nitrogen application levels on mechanical indexes of high-quality late indica rice.

Year	Variety	Nitrogen	SL	FW	WP	M	SM	BS	LI
2019	MXZ2	N1	89.3 ± 1.12 g	14.0 ± 0.15 g	1251 ± 3.26 f	2552 ± 80.8 a	23.0 ± 0.46 g	1228 ± 84.0 a	50.2 ± 1.73 i
		N2	94.3 ± 0.48 f	13.4 ± 0.10 h	1265 ± 13.9 f	2060 ± 8.74 d	18.4 ± 1.29 hi	1156 ± 84.8 a	62.2 ± 0.63 h
		N3	96.1 ± 0.82 f	13.3 ± 0.10 h	1278 ± 6.30 f	1619 ± 40.5 g	16.7 ± 0.45 i	1021 ± 51.3 b	79.6 ± 1.58 f
	TY871	N1	101 ± 0.08 e	19.1 ± 0.25 a	1938 ± 25.2 ab	2539 ± 39.4 ab	48.9 ± 0.08 a	524 ± 10.1 de	77.2 ± 1.15 f
		N2	104 ± 0.11 d	18.6 ± 0.27 b	1930 ± 27.9 ab	2205 ± 20.3 c	47.1 ± 2.18 a	493 ± 14.7 e	87.8 ± 0.48 e
		N3	107 ± 0.63 c	18.1 ± 0.06 c	1938 ± 14.9 ab	1891 ± 49.0 e	36.6 ± 0.57 c	528 ± 9.5 de	103.5 ± 3.02 b
2020	MXZ2	N1	102 ± 0.76 de	14.9 ± 0.02 f	1520 ± 11.0 e	2131 ± 43.2 cd	25.4 ± 0.95 f	853 ± 26.4 c	72.0 ± 1.98 g
		N2	108 ± 0.59 c	14.5 ± 0.27 f	1568 ± 20.0 d	1861 ± 12.7 ef	22.3 ± 0.16 g	903 ± 9.50 c	84.8 ± 0.58 e
		N3	109 ± 0.55 bc	13.9 ± 0.09 g	1519 ± 16.4 e	1561 ± 33.4 g	19.5 ± 0.32 h	817 ± 31.6 c	98.4 ± 3.00 c
	TY871	N1	107 ± 0.53 c	17.7 ± 0.33 cd	1894 ± 28.6 bc	2429 ± 40.9 b	41.0 ± 0.11 b	597 ± 10.8 de	79.1 ± 1.79 f
		N2	111 ± 0.75 b	16.7 ± 0.07 e	1854 ± 17.7 c	2022 ± 12.0 d	34.0 ± 0.43 d	604 ± 11.9 de	92.4 ± 0.47 d
		N3	113 ± 0.44 a	17.5 ± 0.15 d	1973 ± 13.7 a	1761 ± 42.5 f	28.5 ± 0.50 e	624 ± 25.6 d	113 ± 2.46 a
Three-way ANOVA
		Year (Y)	669 **	5.82 *	170 **	67.8 **	49.2 **	16.3 **	222 **
		Variety (V)	391 **	1797 **	3135 **	63.1 **	1517 **	363 **	399 **
		Nitrogen (N)	98.7 **	23.3 **	3.125	333 **	127 **	1.99	363 **
		Y × V	87.7 **	136 **	260 **	3.62	179 **	66.0 **	81.8 **
		Y × N	1.16	2.10	0.83	4.98 *	1.80	1.71	0.50
		V × N	3.94 *	1.80	6.68 **	1.73	17.7 **	4.07 *	0.73
		Y × V × N	0.04	7.16 **	7.29 **	6.79 **	4.81 *	0.87	3.16

WP: Bending moment. M: Breaking moment. BS: Bending stress. SM: Section modulus. SL: Length above breaking point. FW: Fresh weight above breaking point. LI: Lodging index. Different lowercase letters indicate significant differences at p < 0.05. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). Increasing nitrogen levels raised the lodging index (LI) and length above breaking point (SL), but reduced fresh weight (FW), bending moment (M), and section modulus (SM). Compared to N1, LI increased by 20.4% and 45.7% under N2 and N3 for MXZ2, and by 15.4% and 38.3% for TY871, indicating greater nitrogen sensitivity in MXZ2. MXZ2 exhibited lower LI, SL, FW, bending force (WP), M, and SM, but higher bending stress (BS) than TY871. Interannual comparisons showed higher LI, SL, and WP in MXZ2 during 2020, alongside lower M, SM, and BS. TY871 also displayed increased SL, BS, and LI in 2020. Greater interannual variation occurred in MXZ2.

3.3. Effects of Nitrogen Application on Morphological Traits

Nitrogen application significantly altered morphological traits in both rice varieties (

Table 3. Effects of different nitrogen application levels on morphological indexes of high-quality late indica rice.

Year	Variety	Nitrogen	Flag Leaf Angle (°)	Second Top Leaf Angle (°)	Third Top Leaf Angle (°)	Plant Height (cm)	Height of Gravity Center (cm)	Culm Diameter (mm)	Wall Thickness (mm)	Upper Internode Length (cm)	Lower Internode Length (cm)	Proportion of Upper Internode Length (%)
2019	MXZ2	N1	6.63 ± 0.45 e	11.3 ± 1.00 g	17.7 ± 0.89 de	94.7 ± 0.61 f	41.5 ± 0.62 h	6.64 ± 0.03 g	1.24 ± 0.01 e	62.3 ± 0.55 h	8.11 ± 0.63 bcd	88.5 ± 0.87 cd
		N2	7.70 ± 0.23 e	13.4 ± 1.39 fg	16.0 ± 0.45 ef	100 ± 1.40 e	45.4 ± 1.06 g	6.22 ± 0.15 h	1.07 ± 0.04 fg	64.7 ± 0.86 g	8.98 ± 0.49 bc	87.8 ± 0.51 de
		N3	8.63 ± 0.22 e	14.1 ± 0.37 f	13.8 ± 0.94 f	102 ± 0.30 e	47.2 ± 0.18 f	6.10 ± 0.00 h	1.03 ± 0.01 g	67.6 ± 0.64 f	8.54 ± 0.60 bcd	88.8 ± 0.79 bcd
	TY871	N1	6.30 ± 0.68 e	12.6 ± 1.05 fg	14.5 ± 0.95 f	106 ± 0.32 d	45.2 ± 0.36 g	7.68 ± 0.02 b	2.07 ± 0.02 a	73.3 ± 0.66 e	7.33 ± 0.17 d	91.0 ± 0.25 a
		N2	8.43 ± 1.20 e	16.8 ± 0.42 e	19.3 ± 0.87 d	111 ± 1.17 c	48.2 ± 0.90 ef	7.26 ± 0.09 de	1.76 ± 0.05 b	76.0 ± 0.85 d	7.59 ± 0.29 cd	91.0 ± 0.30 a
		N3	6.47 ± 1.00 e	17.2 ± 0.50 e	17.8 ± 0.38 de	112 ± 0.13 c	50.3 ± 0.25 cd	7.07 ± 0.01 f	1.65 ± 0.03 c	79.0 ± 0.48 c	7.99 ± 0.24 bcd	90.9 ± 0.26 a
2020	MXZ2	N1	13.5 ± 0.29 cd	29.2 ± 0.35 b	34.6 ± 0.53 a	111 ± 0.89 c	49.4 ± 0.35 de	7.64 ± 0.06 b	1.29 ± 0.02 e	74.4 ± 0.59 de	11.7 ± 0.45 a	86.5 ± 0.35 e
		N2	17.5 ± 1.63 b	29.6 ± 1.00 ab	34.2 ± 1.31 a	116 ± 0.59 b	52.5 ± 0.06 ab	7.44 ± 0.01 cd	1.23 ± 0.03 e	79.2 ± 0.81 bc	12.1 ± 0.10 a	86.8 ± 0.19 e
		N3	21.2 ± 0.49 a	31.7 ± 0.52 a	34.9 ± 2.90 a	118 ± 0.59 ab	53.9 ± 0.33 a	7.15 ± 0.01 ef	1.12 ± 0.02 f	80.5 ± 0.93 bc	11.6 ± 0.65 a	87.4 ± 0.66 de
	TY871	N1	15.7 ± 1.84 bc	19.8 ± 1.04 cd	23.7 ± 0.87 b	113 ± 0.14 c	49.5 ± 0.33 de	8.01 ± 0.01 a	1.59 ± 0.02 c	78.4 ± 0.25 c	9.07 ± 0.62 b	89.7 ± 0.64 abc
		N2	15.2 ± 1.53 bc	21.8 ± 0.77 c	23.1 ± 0.36 bc	116 ± 0.28 b	51.6 ± 0.38 bc	7.66 ± 0.02 b	1.41 ± 0.01 d	81.5 ± 1.31 ab	8.29 ± 0.56 bcd	90.8 ± 0.70 a
		N3	12.4 ± 1.19 d	18.8 ± 0.88 de	20.5 ± 1.16 cd	119 ± 0.63 a	53.6 ± 0.30 a	7.45 ± 0.07 c	1.29 ± 0.04 e	83.2 ± 0.50 a	9.17 ± 0.77 b	90.1 ± 0.77 ab
Three-way ANOVA
		Year (Y)	249 **	523 **	373 **	764 **	337 **	428 **	84.8 **	412 **	63.2 **	12.7 **
		Variety (V)	10.7 **	61.3 **	75.6 **	214 **	23.3 **	347 **	833 **	254 **	47.2 **	88.2 **
		Nitrogen (N)	4.28 *	9.41 **	1.71	96.4 **	91.6 **	83.5 **	98.5 **	50.9 **	0.36	0.55
		Y × V	4.78 *	177 **	118 **	134 **	35.0 **	105 **	235 **	84.9 **	13.1 **	1.40
		Y × N	0.43	3.39	0.90	0.63	1.26	1.32	4.07 *	1.23	0.64	0.96
		V × N	12.6 **	2.69	2.18	0.50	0.91	0.57	10.2 **	0.25	1.48	1.25
		Y × V × N	6.06 **	3.18	6.32 **	0.39	0.03	0.45	0.43	0.53	0.11	0.01

Different lowercase letters indicate significant differences at p < 0.05. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). Higher nitrogen levels increased flag leaf angle, plant height, height of gravity center, and upper internode length, but reduced culm diameter and wall thickness. MXZ2 showed larger leaf angles and longer lower internodes, but lower plant height, smaller culm diameter, thinner walls, and shorter upper internodes compared to TY871. Interannual comparisons indicated that all measured traits—including flag leaf angle, second- and third-top leaf angles, plant height, height of the center of gravity, culm diameter, and lengths of both upper and lower internodes—were significantly lower in 2019 than in 2020. Conversely, wall thickness was significantly greater in 2019 compared to 2020.

3.4. Effects of Nitrogen on Dry Matter Accumulation and Allocation

Nitrogen application significantly reduced culm-sheath dry weight and its proportion, while increasing leaf dry weight, panicle dry weight, and their respective proportions, as well as panicle-culm diameter ratio and panicle weight per unit culm diameter and plant height (

Table 4. Effects of different nitrogen application levels on dry matter accumulation and distribution in different organs of high-quality late indica rice.

Year	Variety	Nitrogen	Culm-Sheath Dry Weight (g No.−1)	Leaf Dry Weight (g No.−1)	Panicle Dry Weight (g No.−1)	Culm-Sheath Dry Weight Proportion (%)	Leaf Dry Weight Proportion (%)	Panicle Dry Weight Proportion (%)	Panicle-Culm Diameter Ratio (g cm−1)	Panicle Weight Per Unit Culm Diameter and Plant Height (×10−2 g cm−2)
2019	MXZ2	N1	1.75 ± 0.03 cd	0.68 ± 0.01 h	1.94 ± 0.02 fg	40.1 ± 0.32 d	15.6 ± 0.18 e	44.3 ± 0.48 d	2.93 ± 0.03 d	3.10 ± 0.04 d
		N2	1.61 ± 0.01 e	0.73 ± 0.00 g	2.09 ± 0.03 de	36.3 ± 0.23 e	16.5 ± 0.18 cd	47.2 ± 0.41 c	3.37 ± 0.13 c	3.36 ± 0.18 c
		N3	1.44 ± 0.01 f	0.79 ± 0.01 cde	2.07 ± 0.02 ef	33.5 ± 0.26 g	18.4 ± 0.20 ab	48.2 ± 0.07 c	3.39 ± 0.03 c	3.33 ± 0.04 c
	TY871	N1	1.90 ± 0.02 ab	0.80 ± 0.01 bcde	3.11 ± 0.07 b	32.9 ± 0.49 g	13.8 ± 0.29 g	53.4 ± 0.64 b	4.04 ± 0.08 b	3.82 ± 0.09 b
		N2	1.77 ± 0.02 cd	0.83 ± 0.01 ab	3.37 ± 0.09 a	29.8 ± 0.39 h	14.0 ± 0.36 fg	56.2 ± 0.63 a	4.64 ± 0.08 a	4.18 ± 0.07 a
		N3	1.61 ± 0.01 e	0.85 ± 0.02 a	3.38 ± 0.08 a	27.7 ± 0.40 i	14.7 ± 0.17 f	57.6 ± 0.45 a	4.76 ± 0.12 a	4.24 ± 0.11 a
2020	MXZ2	N1	1.92 ± 0.02 a	0.71 ± 0.01 gh	1.52 ± 0.02 i	46.3 ± 0.19 a	17.2 ± 0.23 c	36.5 ± 0.11 g	2.00 ± 0.02 f	1.80 ± 0.03 g
		N2	1.85 ± 0.01 b	0.77 ± 0.00 ef	1.68 ± 0.04 h	43.1 ± 0.29 b	18.1 ± 0.25 b	38.9 ± 0.54 f	2.27 ± 0.06 e	1.96 ± 0.06 fg
		N3	1.80 ± 0.01 c	0.82 ± 0.01 abc	1.70 ± 0.01 h	41.4 ± 0.02 c	19.1 ± 0.18 a	39.5 ± 0.18 f	2.38 ± 0.02 e	2.02 ± 0.03 fg
	TY871	N1	1.93 ± 0.04 a	0.73 ± 0.02 fg	1.92 ± 0.05 g	42.3 ± 0.89 bc	16.1 ± 0.26 de	41.6 ± 1.03 e	2.39 ± 0.06 e	2.12 ± 0.06 f
		N2	1.74 ± 0.02 d	0.78 ± 0.03 de	2.23 ± 0.04 cd	36.8 ± 0.59 e	16.5 ± 0.68 cd	46.8 ± 0.99 c	2.92 ± 0.04 d	2.50 ± 0.03 e
		N3	1.64 ± 0.02 e	0.81 ± 0.01 bcd	2.26 ± 0.04 c	34.8 ± 0.10 f	17.2 ± 0.05 c	48.0 ± 0.14 c	3.05 ± 0.06 d	2.56 ± 0.04 e
Three-way ANOVA
		Year (Y)	177 **	0.85	789 **	1058 **	123 **	836 **	1135 **	1196 **
		Variety (V)	13.4 **	37.8 **	1005 **	713 **	158 **	651 **	510 **	214 **
		Nitrogen (N)	212 **	40.6 **	29.8 **	242 **	34.3 **	67.6 **	72.0 **	22.1 **
		Y × V	154 **	31.2 **	183 **	4.05	11.5 **	10.3 **	72.6 **	16.7 **
		Y × N	8.73 **	0.26	0.40	1.57	0.66	0.67	0.76	0.11
		V × N	4.810 *	2.58	2.78	1.11	5.02 *	3.12	3.97 *	2.03
		Y × V × N	7.25 **	0.14	0.02	7.47 **	0.96	2.34	0.12	0.24

Different lowercase letters indicate significant differences at p < 0.05. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). MXZ2 showed significantly lower values than TY871 in culm-sheath, leaf, and panicle dry weights, panicle dry matter proportion, panicle-culm diameter ratio, and panicle weight per unit culm diameter and plant height. However, MXZ2 had higher proportional dry matter allocation to culms and leaves. Compared to 2020, both varieties in 2019 exhibited significantly lower culm-sheath dry weight and its proportion, along with reduced leaf dry matter proportion, but higher panicle dry weight, panicle dry matter proportion, panicle–culm diameter ratio, and panicle weight per unit culm diameter and plant height.

3.5. Effects of Nitrogen on Culm and Sheath Carbohydrates

Increasing nitrogen significantly reduced filling degree, cellulose, lignin, starch, and sucrose content in both culm and sheath of the fourth internode across varieties (Figure 1 and Figure 2;

Table 5. Analysis of variance of carbohydrate content in culm and sheath under different nitrogen application rates of IN4 for high-quality late indica rice.

	Culm					Sheath
	CP	CC	CL	CA	CS	HP	HC	HL	HA	HS
Year (Y)	47.8 **	359 **	50.3 **	99.7 **	7.76 *	0.01	0.48	6.18 *	69.5 **	621 **
Variety (V)	1446 **	174 **	9.37 **	1991 **	1022 **	60.7 **	0.05	21.7 **	171 **	350 **
Nitrogen (N)	756 **	132 **	65.1 **	225 **	182 **	655 **	130 **	147 **	233 **	141 **
Y × V	34.8 **	76.2 **	2.64	7.29 *	1.74	0.18	25.0 **	63.7 **	5.24 *	101 **
Y × N	3.46 *	0.79	0.93	3.55 *	0.80	3.60 *	0.27	7.04 **	6.60 **	25.4 **
V × N	44.1 **	1.96	0.93	15.5 **	16.2 **	19.0 **	4.35 *	21.5 **	0.51	6.00 **
Y × V × N	31.1 **	5.28 *	1.18	16.0 **	2.45	14.7 **	3.24	5.03 *	1.14	7.11 **

CP: Culm filling degree; CC: Culm cellulose content; CL: Culm lignin content; CA: Culm starch content; CS: Culm sucrose content; HP: Sheath filling degree; HC: Sheath cellulose content; HL: Sheath lignin content; HA: Sheath starch content; HS: Sheath sucrose content. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). TY871 showed greater reductions in these carbohydrate-related traits than MXZ2. MXZ2 exhibited significantly higher filling degree, cellulose, lignin, starch, and sucrose content in the culm, as well as higher filling degree, lignin, starch, and sucrose in the sheath compared to TY871. Interannual comparisons revealed that in 2019, culms had significantly lower filling degree, cellulose, lignin, and starch but higher sucrose content, while sheaths showed lower lignin but higher starch and sucrose compared to 2020.

3.6. Effects of Nitrogen on Anatomical Traits

Increasing nitrogen application initially increased then decreased culm small vascular bundle area, while sheath large vascular bundle number first decreased then increased. Culm area, sheath area declined with higher nitrogen while pith cavity area and ratio increased (

Table 6. Effects of different nitrogen application levels on anatomic indexes of culm and sheath of IN4 for high-quality late indica rice.

Year	Variety	Nitrogen	Culm				Sheath				Culm Area (×104 μm2)	Sheath Area (×104 μm2)	Pith Cavity Area (×104 μm2)	Pith Cavity Area Ratio (%)
			Number of Large Vascular Bundles	Number of Small Vascular Bundles	Large Vascular Bundle Area (×104 μm2)	Small Vascular Bundle Area (×104 μm2)	Number of Large Vascular Bundles	Number of Small Vascular Bundles	Large Vascular Bundle Area (×104 μm2)	Small Vascular Bundle Area (×104 μm2)
2019	MXZ2	N1	30.8 ± 0.73 cde	30.3 ± 0.73 cd	1.60 ± 0.05 ab	0.40 ± 0.02 e	21.3 ± 0.67 abc	21.7 ± 1.09 ab	1.10 ± 0.07 cd	0.34 ± 0.00 g	1013 ± 27.6 cde	1127 ± 47.2 def	738 ± 4.80 j	23.9 ± 0.76 f
		N2	29.5 ± 0.58 e	29.2 ± 0.44 d	1.59 ± 0.05 ab	0.45 ± 0.02 de	20.2 ± 0.60 c	20.8 ± 0.73 b	1.06 ± 0.08 d	0.37 ± 0.02 fg	962 ± 30.0 defg	1076 ± 16.0 ef	823 ± 8.60 i	25.3 ± 0.42 ef
		N3	31.8 ± 0.33 bcd	31.0 ± 0.29 bcd	1.43 ± 0.05 b	0.48 ± 0.02 cd	21.3 ± 0.44 abc	21.3 ± 0.17 ab	1.15 ± 0.05 bcd	0.35 ± 0.02 g	866 ± 24.4 fg	1015 ± 46.8 f	928 ± 35.5 gh	29.4 ± 0.54 bc
	TY871	N1	33.7 ± 0.44 a	33.3 ± 0.44 a	1.49 ± 0.09 ab	0.57 ± 0.02 b	22.3 ± 1.01 ab	22.2 ± 1.09 ab	1.27 ± 0.04 abcd	0.43 ± 0.01 cdef	1208 ± 25.4 ab	1822 ± 30.2 a	1224 ± 5.59 e	26.9 ± 0.60 de
		N2	32.3 ± 0.17 abcd	31.8 ± 0.44 abc	1.53 ± 0.07 ab	0.61 ± 0.03 b	20.8 ± 0.60 bc	21.0 ± 0.87 ab	1.40 ± 0.05 a	0.44 ± 0.02 bcde	1138 ± 71.3 bc	1758 ± 29.2 ab	1330 ± 28.5 d	29.5 ± 0.36 bc
		N3	33.5 ± 0.76 ab	33.0 ± 0.58 ab	1.59 ± 0.05 ab	0.75 ± 0.01 a	22.2 ± 0.60 abc	22.2 ± 0.73 ab	1.43 ± 0.03 a	0.46 ± 0.01 bcd	1060 ± 34.8 cd	1703 ± 12.2 abc	1446 ± 32.2 c	32.5 ± 0.67 a
2020	MXZ2	N1	31.0 ± 0.76 cde	30.2 ± 1.09 cd	1.65 ± 0.04 ab	0.40 ± 0.03 e	21.5 ± 0.29 abc	21.3 ± 0.44 ab	1.14 ± 0.09 bcd	0.36 ± 0.02 g	994 ± 52.5 cdef	1241 ± 16.4 d	864 ± 8.40 hi	24.5 ± 0.17 f
		N2	30.7 ± 0.73 de	30.3 ± 0.60 cd	1.56 ± 0.05 ab	0.46 ± 0.00 de	21.0 ± 0.50 bc	20.8 ± 0.60 b	1.26 ± 0.03 abcd	0.38 ± 0.01 efg	906 ± 58.7 efg	1188 ± 56.2 de	962 ± 3.74 g	28.4 ± 0.87 cd
		N3	29.5 ± 0.76 e	29.8 ± 0.73 cd	1.58 ± 0.07 ab	0.42 ± 0.04 de	21.3 ± 0.33 abc	21.3 ± 0.33 ab	1.21 ± 0.06 abcd	0.41 ± 0.04 defg	820 ± 30.0 g	1076 ± 71.9 ef	1055 ± 35.4 f	32.4 ± 0.22 a
	TY871	N1	33.2 ± 0.33 ab	33.3 ± 0.33 a	1.71 ± 0.15 a	0.54 ± 0.04 bc	21.0 ± 0.76 bc	20.7 ± 0.73 b	1.36 ± 0.13 ab	0.51 ± 0.03 ab	1304 ± 34.7 a	1769 ± 59.5 ab	1502 ± 20.8 c	26.7 ± 0.27 e
		N2	32.5 ± 0.58 abc	31.7 ± 1.01 abc	1.51 ± 0.14 ab	0.70 ± 0.05 a	20.7 ± 0.67 bc	20.3 ± 0.44 b	1.31 ± 0.08 abc	0.49 ± 0.02 abc	1212 ± 84.6 ab	1688 ± 42.4 bc	1622 ± 34.0 b	30.5 ± 0.83 b
		N3	33.5 ± 0.29 ab	32.7 ± 0.88 ab	1.72 ± 0.06 a	0.49 ± 0.02 cd	23.2 ± 1.30 a	23.2 ± 1.20 a	1.40 ± 0.16 a	0.54 ± 0.04 a	1129 ± 46.8 bc	1624 ± 30.4 c	1778 ± 33.2 a	32.6 ± 0.33 a
Three-way ANOVA
		Year (Y)	0.41	0.08	2.82	7.07 *	0.04	0.33	1.02	11.6 **	0.47	0.37	213 **	15.9 **
		Variety (V)	54.7 **	39.5 **	0.25	133 **	2.11	0.68	19.4 **	68.2 **	75.8 **	636 **	1586 **	57.9 **
		Nitrogen (N)	2.87	2.64	0.55	9.12 **	3.80 *	2.73	1.01	2.19	10.7 **	10.5 **	73.7 **	121 **
		Y × V	0.10	0.02	0.27	2.93	0.39	0.10	1.43	2.31	4.41 *	11.4 **	33.1 **	8.65 **
		Y × N	2.35	0.82	1.24	16.3 **	0.70	0.88	0.08	0.61	0.11	0.25	0.30	2.80
		V × N	0.18	0.63	1.72	0.50	0.88	1.24	0.08	0.55	0.02	0.12	1.34	1.65
		Y × V × N	2.35	0.65	0.38	6.62 **	0.91	0.56	1.11	0.09	0.01	0.07	0.35	0.92

Different lowercase letters indicate significant differences at p < 0.05. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). MXZ2 showed significantly lower values than TY871 in number and area of vascular bundles, culm area, sheath area, pith cavity area (39.7% lower), and pith cavity ratio (8.33% lower) averagely. Significant interannual differences were observed. Compared to 2020, 2019 exhibited 16.6% lower pith cavity area and 4.46% lower pith cavity ratio.

3.7. Effects of Nitrogen on Sheath Contribution Rate

Increasing nitrogen significantly reduced sheath contribution to breaking moment (CM), section modulus (CSM), and lodging index (CLI) in both varieties (p < 0.05; Figure 3,

Table 7. Analysis of variance of influence of sheaths on contribution rate of mechanical index of different nitrogen application for high-quality late indica rice.

Treatment	CSL	CFW	CWP	CM	CSM	CBS	CLI
Year (Y)	5.62 *	3.50	9.85 **	18.4 **	52.7 **	120 **	58.1 **
Variety (V)	1.69	302 **	260 **	107 **	152 **	58.4 **	0.56
Nitrogen (N)	5.11 *	7.50 **	8.87 **	87.6 **	8.17 **	7.21 **	95.8 **
Y × V	0.04	69.9 **	65.3 **	32.9 **	27.5 **	82.8 **	1.84
Y × N	5.53 *	9.77 **	12.4 **	2.1	3.51 *	4.36 *	1.05
V × N	0.27	20.2 **	19.2 **	4.64 *	1.52	3.501 *	0.07
Y × V × N	0.38	0.79	1.12	3.81 *	2.06	2.28	5.08 *

CSL: Sheath contribution rate to length above breaking point. CFW: Sheath contribution rate to fresh weight above breaking point. CWP: Sheath contribution rate to bending moment. CM: Sheath contribution rate to breaking moment. CSM: Sheath contribution rate to section modulus. CBS: Sheath contribution rate to bending stress. CLI: Sheath contribution rate to lodging index. The asterisks denote significance levels: * p < 0.05, ** p < 0.01.

). MXZ2 showed significantly higher sheath contribution to fresh weight (CFW), bending moment (CWP), CM, CSM, and bending stress (CBS) compared to TY871 (p < 0.05), while CLI showed no significant varietal difference. Interannual comparisons revealed that CWP, CSM, and CBS were significantly lower in 2019 than in 2020, whereas CM and CLI were significantly higher.

4. Discussion

4.1. Elevated Nitrogen Increased Yield with a Slight Penalty in Lodging Resistance

Achieving high rice yield requires a greater number of spikelets per panicle, which increases the bending moment on the culm and consequently elevates the risk of lodging [26]. This highlights the inherent contradiction between high yield and lodging resistance. The present study demonstrates that nitrogen application rate significantly influences yield components (Table 1) and lodging-related traits (Table 2), with notable varietal and interannual variations. Moderate nitrogen application enhanced grain yield, whereas excessive nitrogen (e.g., N3 treatment) led to yield reduction, particularly under unfavorable climatic conditions such as the low temperature and insufficient sunlight encountered in 2020 (Figure S1). In terms of yield formation, increased nitrogen input significantly raised the number of productive panicles but reduced grains per panicle and percentage of filled grains (Table 1), consistent with previous studies [27,28]. The interannual differences in yield were primarily driven by meteorological factors: during the grain-filling period in 2020, lower temperatures, higher rainfall, and reduced solar radiation significantly decreased both percentage of filled grains and 1000-grain weight.

Increased nitrogen application elevated the lodging index (LI) and length above breaking point (SL), while reducing mechanical strength indicators such as bending moment (M) and section modulus (SM, Table 2), indicating higher lodging susceptibility under high nitrogen conditions [29]. Although MXZ2 exhibited greater sensitivity to nitrogen than TY871, it demonstrated overall lower lodging risk, as reflected in its lower LI, SL, and FW, alongside higher bending stress (BS), likely attributable to its superior culm structural characteristics. Morphological observations revealed that high nitrogen levels increased leaf angle, plant height, and height of the center of gravity, while reducing culm diameter and wall thickness (Table 3), collectively compromising lodging resistance. These changes may come from intensified intra-population competition for light, temperature, water, and nutrients during the vegetative growth stage, particularly under high seedling density [30]. Although MXZ2 displayed lower plant height and center of gravity, its larger leaf angles may negatively impact canopy light interception efficiency. During the elongation to heading stage in 2020, persistent rainy weather (Figure S1) promoted vertical growth, resulting in elongated internodes, increased plant height, and elevated center of gravity, further exacerbating lodging risk.

4.2. Mechanism of Nitrogen Regulation on Lodging Resistance in Rice via Modulating Dry Matter Partitioning and Sheath Structural Properties

Increased nitrogen application promoted dry matter allocation to leaves and panicles but reduced culm-sheath dry weight and its proportion [31], (Table 4), resulting in a “heavy panicle–light culm” structure that elevated lodging risk. MXZ2 exhibited higher cellulose, sucrose, and starch content in culm-sheath tissues than TY871, indicating superior culm quality. In contrast, TY871 demonstrated higher panicle dry weight and lower culm-sheath dry matter allocation. Such large-panicle varieties often experience imbalanced dry matter partitioning among organs, increasing susceptibility to lodging [32]. Carbohydrate content in culm and sheath decreased with increasing nitrogen levels (Figure 1 and Figure 2), which can be attributed to vigorous leaf growth under high nitrogen input [33], leading to deteriorated light penetration and ventilation within the canopy [34]. This accelerated consumption of photo-assimilates and impeded sugar translocation to culms [35], ultimately reducing culm filling and impairing mechanical tissue development [36]. The favorable climatic conditions in 2019 further enhanced panicle dry matter accumulation and optimized yield formation. Interannual variations suggest that photosynthetic product accumulation and translocation efficiency are significantly influenced by environmental conditions [37].

High nitrogen treatment reduced culm and sheath cross-sectional area while increasing the proportion of pith cavity area (Table 6), collectively diminishing mechanical resistance to bending. MXZ2, with its smaller pith cavity area and lower pith ratio, demonstrated stronger lodging resistance, likely due to its superior anatomical structure. The sheath contribution to lodging resistance reached 27.7% across treatments (Figure 3). Key sheath contribution indicators—including CM (sheath contribution to breaking moment), CSM (to section modulus), and CLI (to lodging index)—decreased with increasing nitrogen application. This decline corresponded to reduced filling degree, cellulose, lignin, starch, and sucrose content in sheaths (Figure 2), suggesting that accelerated sheath senescence and diminished toughness under high nitrogen input compromised mechanical strength [38]. The sheath contribution to lodging index was 21.9% higher in 2019 than in 2020 (Figure 3), which may be attributed to more favorable temperature and solar radiation conditions in 2019 that promoted the accumulation of non-structural carbohydrates in sheaths, thereby enhancing their structural support function (Figure 2).

Nitrogen application rate significantly influences both grain yield and lodging resistance by modulating plant growth, morphological construction, dry matter partitioning, and culm-sheath structural properties. Although MXZ2 exhibits slightly lower yield potential compared to TY871, it demonstrates superior culm mechanical strength and higher sheath contribution rate, resulting in enhanced lodging resistance. It is recommended that nitrogen application strategies be optimized according to variety-specific characteristics and meteorological conditions to achieve synergistic improvement of both yield and lodging resistance.

5. Conclusions

Elevated nitrogen application improves yield but raises lodging risk by reducing mechanical strength, worsening plant structure, lowering culm carbohydrate content, and diminishing sheath support. The low temperature and limited sunlight under the humid subtropical monsoon climate in southern China during grain filling directly led to significant reductions in yield and stem strength. Producers in this specific agroecological zone should prioritize the cultivation of Meixiangzhan 2 due to its demonstrated superior lodging resistance and stable performance across varying environmental conditions. Variety-specific nitrogen management in this region is recommended, including (i) increasing nitrogen (N3) for lodging-resistant MXZ 2 to boost yield, while strictly controlling mid-to late-stage nitrogen for the lodging-prone TY 871; and (ii) adjust strategies according to weather conditions to balance yield and lodging resistance.