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Article

Effects of Nitrogen Application at Different Panicle Development Stages on the Panicle Structure and Grain Yield in Hybrid Indica Rice Cultivars

by
Qiguang Zhang
1,
Jie Sun
2,
Longping Wang
1,
Jun Chen
1,
Jian Ke
2 and
Liquan Wu
2,*
1
Anhui Agricultural Reclamation Group Co., Ltd., Hefei 230031, China
2
College of Agronomy, Anhui Agricultural University, Hefei 230031, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(3), 595; https://doi.org/10.3390/agronomy15030595
Submission received: 26 January 2025 / Revised: 20 February 2025 / Accepted: 26 February 2025 / Published: 27 February 2025
(This article belongs to the Special Issue Molecular Mechanism of Quality Formation in Rice)
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Abstract

:
To increase the seed setting rate and yield of large-panicle rice varieties, one agronomic and breeding strategy is to increase the proportion of spikelets in the middle portion of the panicle as many of the lower spikelets fail to produce grains. Current nitrogen management during panicle development mainly focuses on fertilization at the emergence of the top fourth leaf, which increases the number of secondary branch spikelets on the lower part of the panicle. Two-year field experiments were conducted in 2021 and 2022 with two typical large-panicle hybrid indica rice cultivars, IIYM86 and JLY8612. Nitrogen was applied at the emergence of the top fifth (TL5), fourth (TL4), third (TL3), and second (TL2) leaves, with no nitrogen application as a control. This study aimed to investigate the effects of nitrogen application on the panicle structure, seed setting rate, and grain yield at different stages of panicle development. Nitrogen application at TL3 achieved the highest grain yield, followed by application at TL4, for both cultivars over the two years. TL3 did not significantly alter the number of spikelets per panicle but increased the proportion of spikelets located in the middle part of the panicle and reduced the proportions in the upper and lower parts compared to TL4. These effects were attributed to a significant increase in secondary branch spikelet differentiation in the middle part and a decrease in secondary branch spikelet differentiation in the upper and lower parts. Compared to TL4, TL3 significantly increased the seed setting rate by 9.46 and 9.48% and the grain yield by 6.86 and 8.92% in IIYM86 and JLY8612, respectively. In TL3, the significant increase in secondary branch spikelet differentiation in the middle part was primarily due to significantly reduced indole acetic acid (IAA) and an increased cytokinin/IAA ratio, which inhibited apical dominance. The significant decrease in secondary branch spikelet differentiation in the lower part of TL3 was mainly related to a significant increase in IAA and a reduction in the cytokinin/IAA ratio. Transcriptome analysis of young panicles confirmed these results, and differentially expressed genes between TL3 and TL4 were primarily enriched in plant hormone signal transduction related to IAA biosynthesis and degradation. These findings indicate that postponing nitrogen application until TL3 can improve the PTI and the seed setting rate by regulating hormonal balance, thereby optimizing nitrogen management during panicle development in large-panicle hybrid indica rice cultivars.

1. Introduction

Rice is a major food crop throughout the world, and there is an urgent need to increase rice yield by at least 1% annually until 2050 to meet the growing food demand from population growth [1]. Large-panicle rice cultivars currently prevail in high-yield rice cultivation, with yield potentials exceeding 15 t ha−1 [2]. However, large-panicle rice cultivars commonly suffer from low seed setting rates, leading to a significant gap between actual and expected yields [3,4,5]. Optimization of the grain-filling process for large-panicle rice cultivars is a key area of research in high-yield rice cultivation.
Large-panicle rice cultivars are widely recognized to exhibit significant variations in seed setting rates in different parts of the panicle [6,7]. The spikelets on the secondary branches in the lower part of the panicle (inferior spikelets) typically have the lowest seed setting rates, which is a major constraint limiting the improvement of the seed setting rate in large-panicle rice cultivars. Yang and Zhang observed the panicle traits of 12 super rice cultivars and found that the seed setting rate of secondary branch spikelets in the lower part of the panicle was 20.7% lower than that in the upper part [8]. Enhancing the accumulation and translocation of non-structural carbohydrates (NSCs) in the stem and sheath during the rice heading stage is a key strategy for increasing sink strength and improving grain filling in inferior spikelets [9,10]. NSC accumulation and translocation in the stem and sheath of rice in the heading stage are typically intensified under stress conditions, such as drought and nitrogen deficiency, primarily due to the increased activity of enzymes involved in sucrose-to-starch conversion in the stem and sheath [11,12,13]. These findings indicate that the strategy for enhancing grain filling in large-panicle rice cultivars and promoting seed setting rates in inferior spikelets by increasing NSCs in the stem and sheath may risk a yield reduction.
Increasing the proportion of spikelets in the middle parts of the panicle is a key strategy for increasing rice yield [14,15]. This proportion is quantified by the panicle type index (PTI), which is the ratio of the node position on the panicle axis where the primary branch with the most numerous secondary branch spikelets is located to the number of primary branches. Xu et al. observed considerable variations in the PTI (0.29–0.61) across 16 rice cultivars and identified a PTI above 0.5 as a key indicator of high-yield, high-quality rice cultivars [16]. Previous studies have shown that the number of spikelets on the secondary branches located in the middle and lower parts of the panicle is significantly influenced by nitrogen [17,18]. This indicates that adjusting nitrogen application during panicle development can increase the number of secondary branch spikelets in the middle of the panicle and improve the PTI. However, the widely adopted nitrogen application at the emergence of the top fourth leaf, which primarily aims to increase the number of secondary branch spikelets in the lower part to improve the number of spikelets per panicle, does not effectively enhance the PTI [19,20]. This approach involves a considerable trade-off between the number of spikelets per panicle and the seed setting rate [4,21]. However, nitrogen management strategies targeting PTI improvement during panicle development in large-panicle rice cultivars have yet to be established, and the yield-enhancing effects of such techniques are unclear.
Plant hormones serve as the primary physiological and biochemical foundations for regulating spikelet differentiation and development [22]. Previous studies on rice have shown that cytokinin (CTK) extends the duration of branch and spikelet differentiation and increases the total number of branches and spikelets on the panicle [23]. Indole acetic acid (IAA) promotes spikelet differentiation in the upper part of the panicle but inhibits their growth in the lower part, and gibberellin (GA) promotes branch differentiation in the lower part [24,25]. Additionally, ethylene (ETH) and abscisic acid (ABA) regulate rice spikelet degeneration [26]. For instance, rice spikelet degeneration is inhibited by an increase in ABA and a decrease in ETH [27]. These findings indicate that plant hormones and their interactions play an important role in regulating spikelet distribution along the rice panicle. However, recent research has mainly focused on the hormonal mechanisms of the spikelets per panicle, but the hormones and their balance mechanisms of the grain number per panicle at each panicle position and the formation of a high PTI have not been reported.
Hybrid indica rice cultivars are typically cultivated in the southern regions of China. Our previous research has shown that differences in yield components among various large-panicle hybrid indica rice cultivars are primarily attributable to the number of effective panicles and 1000-grain weight [28]. To enhance the applicability of our findings, we investigated two large-panicle hybrid indica rice cultivars commonly grown in the southern regions of China: one with a low panicle number and high 1000-grain weight, and one with a high panicle number and low 1000-grain weight. We examined the effects of nitrogen application at different panicle developmental stages on the PTI, seed setting rate, and grain yield and elucidated the key processes and hormonal mechanisms underlying the formation of a high PTI. We proposed an innovative nitrogen management strategy during panicle development aimed at optimizing grain filling in large-panicle hybrid indica rice cultivars. Our findings provide a theoretical basis and technical support for the breeding and agronomy of high-yield rice cultivars.

2. Materials and Methods

2.1. Experimental Site and Rice Cultivars

A field experiment was conducted at Wanzhong Experimental Station of Anhui Agriculture University, Anhui Province, China (31°48′ N, 117°23′ E), for mid-season rice in 2021 and 2022. The characteristics of the topsoil (0–20 cm) before the experiment were as follows: 23.85 g kg−1 soil organic matter; 1.51 g kg−1 total nitrogen; 25.2 mg kg−1 Olsen-P; 132.0 mg kg−1 available potassium; and pH 5.33. The average air temperature and precipitation during the rice-growing period across the two years were measured at a weather station close to the experimental site (Figure 1).
Two local mid-season indica hybrid rice cultivars, IIyouming 86 (IIYM86) and Jingliangyou 8612 (JLY8612), were used in this experiment. IIYM86 has a low panicle number (230.4 panicles per m2) and a high 1000-grain weight (28.2 g), whereas JLY8612 has a high panicle number (248.9 panicles per m2) and a low 1000-grain weight (24.6 g) (https://www.ricedata.cn/variety/, accessed on 20 January 2021). IIYM86 and JLY8612 are representative hybrid indica rice cultivars commonly grown in the southern regions of China [28].

2.2. Experimental Design and Management

The experiment was carried out in a randomized block design with two cultivars and three replications for five panicle N application treatments: panicle N application at emergence of top fifth leaf (TL5), top fourth leaf (TL4), top third leaf (TL3), and top second leaf (TL2), and no panicle N application (CK) as the control. Except for CK, 112.5 kg ha−1 of N as urea was applied as topdressing fertilizer in each treatment. In all treatments, N (112.5 kg ha−1 as urea), phosphorus (80 kg ha−1 as superphosphate), and potassium (120 kg ha−1 as potassium chloride) were also applied and incorporated into the soil once before transplanting. Plot dimensions were 6 × 8 m, and plots were separated by a 50 cm wide alley with plastic film inserted into the soil to a depth of 30 cm to form a barrier.
Seeds were sown on special plastic nursery trays with 80 g of dry seeds per tray on 18 May 2021 and 19 May 2022. Artificial transplanting was performed on 15 June 2021 and 16 June 2022. The row spacing was 33 × 16 cm, with two seedlings per hill. Over the rice-growing season and until physiological maturity was achieved, plots were irrigated by flooding to a depth of 5 ± 2 cm above the soil surface, except during mid-season aeration. Pest and disease management was the same as that used for local high-yield cultivation.

2.3. Sampling and Measurements

2.3.1. Criteria for Determining Rice Growth Stages

Rice panicle differentiation was determined using the remaining leaf number and plant microscopic analysis [29].

2.3.2. Spikelet Differentiation and Degeneration

In 2022, rice plants were selected when 50% of the panicles emerged from the flag leaf sheath. Fifteen uniform panicles per plot were selected and analyzed following Wang [30]. Following the node method described by Dong [31], each panicle was divided into the upper, middle, and lower parts by evenly distributing the primary branches (e.g., 4, 3, and 4 for a total of 11 primary branches, or 4, 5, and 4 for a total of 13 primary branches). The numbers of existing primary branches, primary branch spikelets, secondary branches, and secondary branch spikelets were examined for each part. The number of degenerated spikelets in each part was determined following Ji [32]. The number of differentiated spikelets per panicle was the sum of existing and degenerated spikelets.

2.3.3. Hormone Extraction and Analysis

In 2022, samples of young panicles measuring 2.0–3.0 cm in length were collected from each JLY8612 plot under the TL4 and TL3 treatments. Following the method described in Section 2.3.2, the young panicles were divided into upper, middle, and lower parts. CTK, IAA, and ABA were measured in each part using an enzyme-linked immunosorbent assay according to Caruso [33]. ACC in the young panicles was determined according to Cheng and Lur [34].

2.3.4. Transcriptome Sequencing and Analysis

In 2022, young panicle samples of IIYM86 and JLY8612 under the TL4 and TL3 treatments were collected from each plot at the emergence of the top first leaf and subjected to transcriptome sequencing analysis. The young panicle samples were snap-frozen in liquid nitrogen and maintained at a low temperature in dry ice. Using an optical microscope, the sheath surrounding the young panicle was removed, and the panicle was stored at −80 °C for total RNA extraction and transcriptome sequencing.
Transcriptome sequencing was performed by Frasergen (Wuhan, China). The constructed libraries were quality-checked using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and then sequenced on the HiSeq 2000 sequencing platform (Illumina Inc., San Diego, CA, USA). Raw reads were quality-controlled and adapter-trimmed using Trimmomatic to obtain clean reads. The clean reads were aligned to the reference genome using HISAT2. The matched clean reads were normalized to fragments per kilobase of transcript per million mapped reads (FPKM). Differentially expressed genes (DEGs) were identified using the criteria of false discovery rate <0.05 and |log2(fold change)|>2. The two sets of DEGs were subjected to pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The significance of the enriched pathways was determined using a hypergeometric distribution test to determine the biological functions or pathways affected by the DEGs.
To evaluate the accuracy of the sequencing results, six representative genes, OsABF1, OsAHP1, OsPP2C51, OsIAA3, OsERF1, and OsJAZ1, were selected for qRT-PCR validation, and Histone was used as the internal reference gene. Each sample was analyzed with three biological replicates. The primers used in this study are listed in Table S1. The fold change in gene expression between samples was calculated using the 2−ΔΔCt method.

2.3.5. Measurement of PTI

The PTI is the ratio of node position on the panicle axis where the primary branch with the most numerous secondary branch spikelets is located to the number of primary branches (Figure S1) [16]. At the rice maturity stage in 2022, plants in 5 consecutive groups of 20 hills in each plot were collected to calculate the number of effective panicles. Based on the average number of effective panicles, representative plants from five hills in each plot were selected, and the primary branches of all panicles were counted. Ten representative panicles were selected based on the mode of the primary branch count, and the primary branches were numbered sequentially from the base to the top of the panicle axis. The number of secondary branch spikelets on each primary branch was measured to calculate the PTI.

2.3.6. Yield and Yield Components

Once the rice matured, the grain yield was determined from a 5 m2 harvest area in the middle of each plot and adjusted to 13.5% moisture. Five hills of the plants were sampled randomly from each plot to determine the yield components, including the number of panicles per m2, number of spikelets per panicle, seed setting rate, and 1000-grain weight.

2.4. Statistical Analysis

All data analyses were performed in SPSS statistics 22.0 (SPSS Inc., Chicago, IL, USA). Data were subjected to the Shapiro–Wilk test for normality and Levene’s test for homoscedasticity. Datasets for each year were examined separately by one-way analysis of variance. Treatment means were compared using Duncan’s new multiple range test at the 0.05 probability level.

3. Results

3.1. Rice Yield and Its Components

Year (Y), treatment (T), and cultivar (C) had a significant effect on yield, but the interactions of Y × C, Y × T, and Y × C × T were not significant (Figure 2). Compared to CK, nitrogen application significantly increased the grain yield, with increases over 2 years of 7.9–44.6% for IIYM86 and 5.5–20.8% for JLY8612. In the nitrogen application treatments, TL3 exhibited the highest grain yield, followed by TL4, with consistent trends observed for both cultivars over the 2 years. TL3 achieved an even higher grain yield than TL4, largely due to a significant increase in the seed setting rate while maintaining a similar number of spikelets per panicle. In the 2 study years, TL3 achieved average yield increases of 6.86% for IIYM86 and 8.92% for JLY8612 and seed setting rate increases of 9.46 and 9.48%, respectively, compared to TL4.
The grain yield was significantly lower in 2022 than in 2021, likely due to the higher average temperatures from panicle differentiation to the heading stage, which adversely affected the number of spikelets per panicle and the seed setting rate (Figure 1). Since year was not a significant factor in the experiment, data from TL3 and TL4 in 2022 were used for further analysis.

3.2. PTI

The spikelets in different parts of the panicle demonstrated significant differences between TL4 and TL3 (Figure 3). Compared to TL4, TL3 showed significantly reduced spikelet numbers in the upper and lower parts of the panicle and a significantly increased number of spikelets in the middle part, and this trend was consistent in the two cultivars. In TL3, the proportion of spikelets in the middle part of the panicle was 42.6 and 46.6% for IIYM86 and JLY8612, respectively, which were 14.1 and 12.0% higher than those in TL4, respectively. The proportion of spikelets in the lower part of the panicle in TL3 was 23.9 and 27.0% for IIYM86 and JLY8612, respectively, which were 11.2 and 7.7% lower than those in TL4, respectively. Moreover, TL3 resulted in an increase in the PTI of 11.59% for IIYM86 and 8.82% for JLY8612 compared to TL4 (Figure 4).

3.3. PTI Formation

There were significant differences in the number of secondary branch spikelets in different parts of the panicle between TL4 and TL3, while the number of primary branch spikelets did not differ significantly (Figure 5). Compared to TL4, TL3 significantly reduced the number of secondary branch spikelets in the upper and lower parts of the panicle, whereas it significantly increased the number of secondary branch spikelets in the middle part. This trend was consistent in the two cultivars. Additionally, the number of secondary branches in different parts of the panicle did not differ significantly between TL4 and TL3 (Figure 6).
In TL4 and TL3, the formation of a number of secondary branch spikelets in different parts of the panicle was jointly affected by the number of differentiated and degenerated spikelets (Figure 7). In terms of spikelet differentiation, TL3 significantly reduced the number of differentiated secondary branch spikelets in the upper and lower parts, whereas it significantly increased the number of differentiated secondary branch spikelets in the middle part compared to TL4. This trend was consistent in the two cultivars. Moreover, TL3 reduced the number of degenerated spikelets in all parts to varying degrees compared to TL4. However, quantitative analysis showed that the number of differentiated secondary branch spikelets, rather than the number of degenerated secondary branch spikelets, was the dominant factor influencing the number of secondary branch spikelets.

3.4. Spatial Distribution of Plant Hormones in the Panicle

The IAA and ABA contents in different parts of the panicle varied significantly between TL4 and TL3, while the CTK and ACC contents did not differ significantly (Figure 8). Compared to TL4, TL3 significantly increased the ABA/ACC ratio, primarily due to elevated ABA, and this trend was consistent across the different parts of the panicle. However, the CTK/IAA ratio between TL3 and TL4 demonstrated significant differences in different parts of the panicle. In the upper and middle parts, TL3 significantly increased the CTK/IAA ratio compared to TL4, mainly due to the significant reduction in IAA. Moreover, TL3 significantly reduced the CTK/IAA ratio in the lower part, mainly due to the significant increase in IAA.

3.5. Transcriptome Analysis

3.5.1. Transcriptome Data Analysis

For transcriptome analysis, 12 independent samples were collected, generating 431.36 million clean reads. The percentage of Q30 (an error rate of sequencing lower than 1%) was 91.48%, and the GC content ranged from 48.9 to 49.8% (Table S2). Principal component analysis of the transcriptome data revealed a clear distinction between TL3 and TL4 (Figure S2). PC1 and PC2 accounted for 43.4 and 22.1% of the variation, respectively, indicating substantial transcriptome changes in young panicles in response to nitrogen application during panicle development. These results indicate that the transcriptome data were appropriate for subsequent RNA sequencing (RNA-seq) analysis.
Compared to TL4, TL3 showed 3195 upregulated and 2476 downregulated DEGs in IIYM86 as well as 1424 upregulated and 2259 downregulated DEGs in JLY8612 (Figure 9). Furthermore, the two cultivars shared 467 upregulated and 671 downregulated DEGs.

3.5.2. KEGG Analysis of DEGs

Using the KEGG database, the biological functions of the DEGs between TL3 and TL4 were further investigated. Among the top 20 enriched pathways, the two cultivars shared 4 physiological and metabolic pathways: carotenoid biosynthesis, glyoxylate and dicarboxylate metabolism, plant hormone signal transduction, and MAPK signaling pathway-plant (Figure 10). IIYM86 and JLY8612 had 76 and 64 DEGs enriched in plant hormone signal transduction, respectively. This suggests that plant hormone signal transduction may play an important role in the nitrogen-mediated regulation of rice spikelet differentiation and degeneration.

3.5.3. Analysis of DEGs Involved in Plant Hormone Signal Transduction

Analysis of the DEGs involved in plant hormone signal transduction revealed that among the five OsIAA DEGs in the IAA biosynthesis pathway, four were upregulated and one was downregulated (Figure 11). All five OsARF DEGs were upregulated, and two of the three OsGH DEGs were downregulated. However, OsGH3.8 expression differed between the two cultivars. Of the three OsSAUR DEGs, two were downregulated. In the ABA biosynthesis pathway, the DEGs of OsPYR/PYL and OsPP2C, which inhibited the expression of OsSnRK2 and OsABF, were downregulated, resulting in general upregulation of the DEGs of OsSnRK2 and OsABF.

3.5.4. qRT-PCR Validation

The following six DEGs were selected for qRT-PCR analysis to confirm the accuracy and reproducibility of the transcriptome analysis: OsABF1, OsAHP1, OsPP2C51, OsIAA3, OsERF1, and OsJAZ1 (Figure 12). The expression profiles of these selected genes in qRT-PCR analysis were similar to the results of the transcriptome analysis. Compared with TL4, the expression levels of OsABF1 and OsAHP1 were upregulated and the expression levels of OsPP2C51, OsIAA3, OsERF1, and OsJAZ1 were downregulated in young panicles under TL3. This further demonstrates the reliability of our DEGs identified by transcriptome sequencing.

4. Discussion

4.1. Effects of Nitrogen Application During Panicle Development on PTI and Yield of Large-Panicle Hybrid Indica Rice Cultivars

Conventional panicle N application occurs at TL4 to increase the number of spikelets per panicle. This effect primarily results from the increase in secondary branch spikelets on the lower part of the panicle (inferior spikelets) and thus often correlates with a marked decrease in the seed setting rate, particularly in large-panicle rice cultivars, ultimately restricting the grain yield [35]. Similarly, in the current study, TL4 showed the highest number of spikelets per panicle and the lowest seed setting rate, and this trend was consistent across both years and cultivars. Consequently, it is critical and timely to investigate optimized panicle N management techniques to enhance the grain-filling ability of large-panicle rice. Fortunately, compared to TL4, postponing the nitrogen application to TL3 did not significantly reduce the number of spikelets per panicle and significantly improved the seed setting rate and grain yield (Figure 2). Consequently, understanding the key mechanisms by which TL3 maintains a stable number of spikelets per panicle and enhances the seed setting rate and whether these effects are linked to PTI improvement is of significant interest.
Compared to TL4, TL3 reduced the number of spikelets in the upper and lower parts of the panicle, and this reduction was offset by increasing the number of spikelets in the middle part, thus maintaining the number of spikelets per panicle. In general, TL3 showed a concentration of spikelets in the middle part of the panicle, thereby significantly enhancing the PTI (Figure 4). In our study, the PTI of IIYM86 and JLY8612 in TL3 reached 0.77 and 0.74, respectively, meeting the threshold for high-yield and high-quality rice cultivars reported by Xu et al. [16]. These results confirm that the primary mechanism by which TL3 maintains the number of spikelets per panicle and improves the seed setting rate is the formation of a spikelet distribution pattern with an increased number of secondary branch spikelets in the middle part and a decreased number in the lower part of the panicle, thereby enhancing the PTI. This means that it is very necessary to introduce the PTI to comprehensively evaluate the panicle structure and seed setting rate of large-panicle rice cultivars.

4.2. Formation of High PTI in Large-Panicle Hybrid Indica Rice Cultivars

Previous studies have shown that the number of secondary branch spikelets is responsive to nitrogen application during panicle development [20]. Consistent with this, the present study showed that nitrogen application primarily regulated the number of secondary branch spikelets by influencing spikelet differentiation (Figure 5, Figure 6 and Figure 7). There were no significant differences in the number of primary branch spikelets or secondary branches between TL4 and TL3, and this trend was consistent in different parts of the two cultivars. Therefore, we further analyzed the differences in the formation of the number of secondary branch spikelets in different parts of the panicle between the two treatments.
The formation of the number of spikelets per panicle is affected by spikelet differentiation and degeneration. It is generally accepted that nitrogen application at TL4 promotes spikelet differentiation and that postponing nitrogen application is beneficial for reducing degeneration [19]. Our results similarly showed that TL3 reduced the degeneration of secondary branch spikelets to varying degrees in all parts of the panicle but significantly reduced the differentiation of secondary branch spikelets in the upper and lower parts compared to TL4 (Figure 7). In contrast, TL3 significantly increased the differentiation of the secondary branch spikelets in the middle part. This discrepancy may be attributed to the fact that previous studies primarily used japonica rice cultivars, which have a high proportion of secondary branch spikelets in the lower part, contributing to the total number of spikelets per panicle [36]. Therefore, the nitrogen application response of secondary branch spikelet differentiation in the middle part may have been overlooked. Furthermore, since the contribution of spikelet differentiation to the number of spikelets per panicle is greater than that of spikelet degeneration [22], the improvement in the PTI in TL3 compared to TL4 was mainly related to the promotion of secondary branch spikelet differentiation in the middle part and the inhibition of secondary branch spikelet differentiation in the lower part.

4.3. Mechanism of High-PTI Formation in Large-Panicle Hybrid Indica Rice Cultivars

Previous studies have pointed out that the CTK/IAA and ABA/ACC ratios are the main hormonal balance indicators affecting spikelet differentiation and degeneration in young rice panicles [37,38]. A more consistent view holds that an increase in the CTK/IAA ratio typically promotes spikelet differentiation, while an increase in the ABA/ACC ratio is associated with a reduction in spikelet degeneration [38,39]. In our study, the effects of nitrogen application during panicle development on plant hormones and their balance varied in different parts of the panicle [40]. Among growth-promoting hormones, nitrogen application mainly affected the IAA content in the young panicles (Figure 8). Compared to TL4, TL3 significantly reduced the IAA content in the upper and middle parts of the panicle. Transcriptome analysis of the young panicles confirmed these findings, as DEGs responding to nitrogen application were mainly enriched in plant hormone signal transduction, which is involved in regulating IAA biosynthesis and degradation (Figure 11). Compared to TL4, TL3 downregulated the expression of AUX/IAA and SAUR3 related to the IAA signaling pathway but upregulated the expression of ARF, thereby inhibiting IAA biosynthesis. Additionally, GH3 upregulation in TL3 may promote the conjugation of IAA with amino acids, converting active IAA to inactive forms and thereby promoting IAA degradation [41]. However, we observed that the TL3 treatment significantly increased the IAA content in the lower part of the panicle. This may be related to the relatively lower CTK content in the middle and lower parts of the panicle, which promotes the downward transport of IAA from the upper and middle parts of the panicle [42]. Surprisingly, within the context of this study, the differences in the CTK content at each panicle position under the TL3 and TL4 treatments did not reach a significant level, which is inconsistent with previous results indicating that the application of panicle nitrogen fertilizer increases the CTK content in the panicle [24,39]. The nitrogen concentration difference in the panicles between TL4 and TL3 in this study may not have reached the threshold needed to affect the CTK content, causing this inconsistency. Further investigation is required to clarify the relationship between panicle CTK levels and nitrogen concentrations. In general, TL3 increased the CTK/IAA ratio in the middle part of the panicle and decreased this ratio in the lower part, consequently increasing secondary branch spikelet differentiation in the middle part and decreasing this differentiation in the lower part. It is worth noting that TL3 resulted in a significant increase in the CTK/IAA ratio but a notable decrease in secondary branch spikelet differentiation in the upper part of the panicle. This discrepancy may be attributed to the fact that the IAA content is the primary hormonal factor influencing upper spikelet differentiation [27,43]. This means that the effects of plant hormones and their balance on the regulation of spikelet number per panicle exhibited significant differences in different parts of the panicle. Nevertheless, although TL3 improved the PTI compared to TL4, the number of secondary branch spikelets in the upper part of the panicle was significantly reduced. Further research is needed to increase the IAA content in the upper part of the panicle to promote secondary branch spikelet differentiation.
Among the growth-inhibiting hormones, TL3 significantly elevated the ABA content compared to TL4 but did not significantly affect ACC. Transcriptome analysis showed that PP2C expression, which is involved in the ABA signaling pathway, was generally downregulated in TL3. As PP2C acts as a negative regulator of ABA signaling, its downregulation may result in SnRK2 upregulation, thereby increasing the ABA content [44]. Moreover, the downregulation of PYR/PYL in TL3 suggests reduced ABA signal perception, which may be an important reason for ABA accumulation [41]. Compared to TL4, TL3 significantly increased the ABA/ACC ratio in various parts of the panicle (Figure 8). Moreover, the increased ABA/ACC ratio in all parts of the panicle reduced secondary branch spikelet degeneration throughout the panicle.

5. Conclusions

The effects of nitrogen application during rice panicle development on plant hormones and their balance as well as the regulation of spikelet number per panicle exhibited significant differences in different parts of the panicle. In comparison to the traditional strategy of nitrogen application at TL4, postponing nitrogen application to TL3 significantly decreased IAA and increased the CTK/IAA ratio in the middle part of the panicle. Concurrently, IAA decreased in the upper part, while IAA increased and the CTK/IAA ratio decreased in the lower part of the panicle. These changes correspond to variations in the number of secondary branch spikelets, which increased in the middle part and decreased in the upper and lower parts. Compared to TL4, TL3 increased the PTI by 11.59 and 8.82%, the seed setting rate by 9.46 and 9.48%, and the yield by 6.86 and 8.92% in IIYM86 and JLY8612, respectively. Therefore, delaying panicle N application to TL3 is recommended as optimal for large-panicle hybrid indica rice in the southern regions of China.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy15030595/s1, Figure S1: The distribution of varieties on the panicle axis. PRBG, grains in primary rachis branches; SRBG, grains in secondary rachis branches; TG, total grains. PTI, Panicle type index. PTI = the node position on the panicle axis where the primary branch with the most numerous secondary branch spikelets is located/the number of primary branches. Figure S2: Principal component analysis of transcriptome data from young rice panicle samples. II, IIYM86. JLY, JLY8612. TL4, nitrogen application at emergence of the top fourth leaf. TL3, nitrogen application at emergence of the top third leaf. Table S1: Primers for real-time fluorescence quantitative PCR. Table S2: Summary information of sequencing data.

Author Contributions

Conceptualization, J.C. and L.W. (Longping Wang); methodology, J.K.; software, J.S.; validation, L.W. (Longping Wang) and J.K.; formal analysis, Q.Z.; investigation, Q.Z. and J.S.; resources, J.C.; data curation, L.W. (Liquan Wu); writing—original draft preparation, Q.Z.; writing—review and editing, Q.Z. and J.S.; visualization, J.K.; supervision, L.W. (Liquan Wu); project administration, J.K.; funding acquisition, L.W. (Liquan Wu). All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (32201895), Anhui Province Science and Technology Key Project (202423l10050004).

Data Availability Statement

The data presented in this study are included within the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

Authors Qiguang Zhang, Longping Wang, Jun Chen were employed by the company Anhui Agricultural Reclamation Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

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Figure 1. Meteorological data during the rice growth period in 2021 and 2022. SS, sowing stage. TP, transplanting. TL5, nitrogen application at emergence of top fifth leaf. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. TL2, nitrogen application at emergence of top second leaf. MS, maturity stage. Red text indicates the rice growth stage.
Figure 1. Meteorological data during the rice growth period in 2021 and 2022. SS, sowing stage. TP, transplanting. TL5, nitrogen application at emergence of top fifth leaf. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. TL2, nitrogen application at emergence of top second leaf. MS, maturity stage. Red text indicates the rice growth stage.
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Figure 2. Yield and yield components of rice in 2021 and 2022. (A–D) Panicles, (E–H) Spikelets per panicle, (I–L) Seed setting rate, (M–P) Grain weight, and (Q–T) Yield of IIYM86 and JLY8612 in 2021 and 2022, respectively. CK, no panicle nitrogen application. TL5, nitrogen application at emergence of top fifth leaf. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. TL2, nitrogen application at emergence of top second leaf. Values are mean ± SD (n = 3). Different letters above the columns denote statistical significance at p < 0.05. ns, no significance at p = 0.05; * and **, F-value significant at the 0.05 and 0.01 probability levels, respectively.
Figure 2. Yield and yield components of rice in 2021 and 2022. (A–D) Panicles, (E–H) Spikelets per panicle, (I–L) Seed setting rate, (M–P) Grain weight, and (Q–T) Yield of IIYM86 and JLY8612 in 2021 and 2022, respectively. CK, no panicle nitrogen application. TL5, nitrogen application at emergence of top fifth leaf. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. TL2, nitrogen application at emergence of top second leaf. Values are mean ± SD (n = 3). Different letters above the columns denote statistical significance at p < 0.05. ns, no significance at p = 0.05; * and **, F-value significant at the 0.05 and 0.01 probability levels, respectively.
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Figure 3. Spikelet distribution along the panicle. (A) IIYM86; (B) JLY8612. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
Figure 3. Spikelet distribution along the panicle. (A) IIYM86; (B) JLY8612. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
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Figure 4. Panicle type index (PTI). (A–D) Node position on the panicle axis where the primary branch with the most numerous secondary branch spikelets is located, primary branch, secondary branch, and PTI. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
Figure 4. Panicle type index (PTI). (A–D) Node position on the panicle axis where the primary branch with the most numerous secondary branch spikelets is located, primary branch, secondary branch, and PTI. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
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Figure 5. Number of primary and secondary branch spikelets in different parts of the panicle. (A,B) Spikelets in primary branches of IIYM86 and JLY8612, respectively; (C,D) Spikelets in secondary branches of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (**, p < 0.01).
Figure 5. Number of primary and secondary branch spikelets in different parts of the panicle. (A,B) Spikelets in primary branches of IIYM86 and JLY8612, respectively; (C,D) Spikelets in secondary branches of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (**, p < 0.01).
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Figure 6. Number of primary and secondary branches in different parts of the panicle. (A,B) Number of primary branches of IIYM86 and JLY8612, respectively; (C,D) Number of secondary branches of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (**, p < 0.01).
Figure 6. Number of primary and secondary branches in different parts of the panicle. (A,B) Number of primary branches of IIYM86 and JLY8612, respectively; (C,D) Number of secondary branches of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (**, p < 0.01).
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Figure 7. Number of differentiated and degenerated secondary branch spikelets in different parts of the panicle. (A,B) Number of differentiated secondary branch spikelets of IIYM86 and JLY8612, respectively; (C,D) Number of degenerated secondary branch spikelets of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
Figure 7. Number of differentiated and degenerated secondary branch spikelets in different parts of the panicle. (A,B) Number of differentiated secondary branch spikelets of IIYM86 and JLY8612, respectively; (C,D) Number of degenerated secondary branch spikelets of IIYM86 and JLY8612, respectively. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
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Figure 8. Spatial distribution of plant hormones in the panicle of JLY8612. (A–F) CTK content, IAA content, CTK/IAA, ABA content, ACC content, and ABA/ACC. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
Figure 8. Spatial distribution of plant hormones in the panicle of JLY8612. (A–F) CTK content, IAA content, CTK/IAA, ABA content, ACC content, and ABA/ACC. TL4, nitrogen application at emergence of top fourth leaf. TL3, nitrogen application at emergence of top third leaf. Values are mean ± SD (n = 3). Asterisks indicate significant differences between TL4 and TL3 (*, p < 0.05; **, p < 0.01).
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Figure 9. Venn diagram of differentially expressed genes.
Figure 9. Venn diagram of differentially expressed genes.
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Figure 10. Scatter diagram of KEGG pathway enrichment.
Figure 10. Scatter diagram of KEGG pathway enrichment.
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Figure 11. Expression patterns of differentially expressed genes related to indole acetic acid and abscisic acid signal transduction in young rice panicles.
Figure 11. Expression patterns of differentially expressed genes related to indole acetic acid and abscisic acid signal transduction in young rice panicles.
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Figure 12. Comparison of expression results obtained by RNA-seq and qRT-PCR for six differentially expressed genes in (A) IIYM86 and (B) JLY8612. The qRT-PCR data were obtained from three biological replicates, and bars represent SD.
Figure 12. Comparison of expression results obtained by RNA-seq and qRT-PCR for six differentially expressed genes in (A) IIYM86 and (B) JLY8612. The qRT-PCR data were obtained from three biological replicates, and bars represent SD.
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Zhang, Q.; Sun, J.; Wang, L.; Chen, J.; Ke, J.; Wu, L. Effects of Nitrogen Application at Different Panicle Development Stages on the Panicle Structure and Grain Yield in Hybrid Indica Rice Cultivars. Agronomy 2025, 15, 595. https://doi.org/10.3390/agronomy15030595

AMA Style

Zhang Q, Sun J, Wang L, Chen J, Ke J, Wu L. Effects of Nitrogen Application at Different Panicle Development Stages on the Panicle Structure and Grain Yield in Hybrid Indica Rice Cultivars. Agronomy. 2025; 15(3):595. https://doi.org/10.3390/agronomy15030595

Chicago/Turabian Style

Zhang, Qiguang, Jie Sun, Longping Wang, Jun Chen, Jian Ke, and Liquan Wu. 2025. "Effects of Nitrogen Application at Different Panicle Development Stages on the Panicle Structure and Grain Yield in Hybrid Indica Rice Cultivars" Agronomy 15, no. 3: 595. https://doi.org/10.3390/agronomy15030595

APA Style

Zhang, Q., Sun, J., Wang, L., Chen, J., Ke, J., & Wu, L. (2025). Effects of Nitrogen Application at Different Panicle Development Stages on the Panicle Structure and Grain Yield in Hybrid Indica Rice Cultivars. Agronomy, 15(3), 595. https://doi.org/10.3390/agronomy15030595

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