Skip to main content
NCBI home page
Rice logoLink to Rice
. 2026 Jul 4;19:62. doi: 10.1186/s12284-026-00935-3

Structural Volume Composition of Internodes is a Key Morphological Factor Contributing to Culm Non-structural Carbohydrate Accumulation in Rice

Yu Wakabayashi 1,✉, Naohiro Aoki 2, Ryutaro Morita 2, Megumi Sudo 1, Yoichiro Kato 2
PMCID: PMC13616894  PMID: 42400704

Abstract

Non-structural carbohydrates (NSC) stored in the stem play a crucial role in supporting yield formation in rice. However, internode morphological factors associated with NSC accumulation remain unclear. This study aimed to clarify the relationship between internode morphology and NSC accumulation and to identify a robust morphological indicator for evaluating NSC accumulation capacity. Two years of field experiments were conducted using multiple cultivars. The NSC content was quantified for individual internodes and at the whole-plant culm level, and its relationships with internode morphological traits were analyzed. Since the upper internodes (UIN; first and second internodes) and lower internodes (LIN; third and subsequent internodes) exhibited contrasting roles in NSC accumulation, a novel index was introduced, the volume composition ratio (VCR) of UIN/LIN, which represents their relative volumetric contributions within a culm. The VCR of UIN/LIN showed the strongest correlation with culm NSC and high reproducibility across years, outperforming simple morphological traits. In addition, plant growth regulator treatments that altered VCR were accompanied by changes in culm NSC accumulation. Accordingly, the VCR of UIN/LIN serves as a robust morphological indicator of culm NSC accumulation capacity, providing a practical framework for improving stem carbohydrate storage capacity in rice.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12284-026-00935-3.

Keywords: Culm structure, High yield, Internode volume, Non-structural carbohydrates, Oryza sativa, Rice, Volume composition ratio, Yield stability

Background

Rice (Oryza sativa L.) is a staple food for nearly half of the world’s population and accounts for approximately 17% of the global caloric intake (FAO 2023; IRRI, 2016). Therefore, increasing rice production is of great significance for global food security to feed the rapidly increasing world population (Khush 2005; Powell et al. 2012). To date, numerous high-yielding rice cultivars with extra-large sink capacities, characterized by a high harvest index and increased spikelet number per panicle, have been developed, such as the IRRI’s New Plant Type and Chinese hybrid rice (Khush 2013; Peng et al. 1999). In Japan, many high-yield cultivars with extra-large sink capacities, including Takanari, Momiroman, and Hokuriku193, have been developed since the early 1980s (Taylaran et al. 2009; Yoshinaga et al. 2013). These breeding efforts have focused on improving sink-related traits, such as spikelet number and grain weight. Although studies using these cultivars have contributed to the identification of many genes involved in sink capacity (Chen et al. 2021; Lu et al. 2022), sink expansion alone does not necessarily lead to improved grain yield (Fukushima et al. 2017; Nakano et al. 2017; Ohsumi et al. 2011) and enhancement of carbohydrate supply ability (source capacity) must be pursued in parallel (Ueda et al. 2025).

Carbohydrates used for grain development originate from two major sources: carbohydrates stored in the stem prior to heading and photosynthates newly-produced during the grain-filling period. Under normal growing conditions, approximately 25% of the final grain mass is derived from the former, with the remainder supplied by the latter (Cock and Yoshida 1972). The stem serves as a major temporary storage organ that accumulates soluble sugars and starch, which can be rapidly remobilized to the grains after heading (Perez et al. 1971). These temporarily-stored carbohydrates are referred to as non-structural carbohydrates (NSC) to distinguish them from structural carbohydrates such as cellulose and lignin, which constitute cell wall components.

Within a rice panicle, inferior spikelets, which are located on the lower branches and flower later, are characterized by slow and incomplete grain filling (Mohapatra et al. 1993; Zhao et al. 2020). Enhancing the grain-filling ability of inferior spikelets is particularly important for high-yielding varieties, in which the large sink size often exceeds the available source capacity (You et al. 2016). NSC reserves play a key role in determining the grain-filling performance of inferior spikelets in such varieties, and increasing NSC availability largely contributes to higher grain yield (Chen et al. 2019; Fu et al. 2011; Lin et al. 2024). In addition, NSC reserves are known to mitigate yield losses when exposed to unfavorable conditions during grain filling (Slewinski 2012). Under stresses such as low solar radiation (Nagata et al. 2001; Okamura et al. 2013; Okawa et al. 2003), low nitrogen availability (Ju et al. 2015; Li et al. 2018; Pan et al. 2011), drought (Yang et al. 2001; Yang and Zhang 2010), and high temperature (Morita and Nakano 2011), the relative contribution of stem NSC to grain filling increases.

Although NSC accumulation at the pre-heading stage is strongly influenced by environmental factors, such as soil nitrogen status (Ju et al. 2015; Li et al. 2018; Pan et al. 2011) and solar radiation (Nagata et al. 2001), substantial genotypic variation in NSC accumulation has been reported (Samonte et al. 2001; Lubis et al. 2003; Arai-Sanoh et al. 2013; Yoshinaga et al. 2013; Tu et al. 2025). Some varietal differences have been explained by biomass production capacity (Takai et al. 2006), growth duration (Nagata et al. 2002), and physiological factors (Hirano et al. 2005; Wang et al. 2017; Okamura et al. 2018). However, no study has systematically evaluated the relationship between culm morphological traits and the NSC accumulation capacity. Previously, we analyzed NSC dynamics across nodal positions at the pre- and post-heading stages in two large-panicle cultivars differing in NSC accumulation at heading (Wakabayashi et al. 2022). We found clear genotypic differences in NSC accumulation, specifically in the lower internodes of the culm, rather than in the upper internodes or leaf sheaths. Our study suggested that these genotypic differences were associated with internode morphological traits, such aslength and diameter, although the specific causal factors and their generality across cultivars remained unclear.

Therefore, in the current study, a multi-cultivar comparison was conducted to identify the morphological factors associated with NSC accumulation in the culm. Furthermore, relevant morphological traits were experimentally modified using plant growth regulators to examine whether these morphological changes were accompanied by changes in NSC accumulation.

Materials and Methods

Experimental Design

Two field experiments and one pot experiment were conducted. The 2022 field experiment was designed to examine the relationship between NSC accumulation and morphological traits of each internode in the main culm. The 2024 field experiment aimed to relate plant-level culm NSC accumulation to the morphological traits of each internode in the main culm under more uniform climatic conditions across cultivars during the period from panicle formation to heading when NSC accumulates in the culm. A pot experiment was conducted to evaluate how altering the internode composition within a culm by applying plant growth regulators (gibberellin and uniconazole) affected NSC accumulation.

Field Experiments

Field experiments were conducted in 2022 and 2024 in the paddy field at the Institute for Sustainable Agro-ecosystem Services (ISAS), The University of Tokyo (35°44′N, 139°32′E, altitude: 58 m), Tokyo, Japan. Ten high-yielding cultivars with different genome types were used (Table S1). Seeds were sown in seedling nursery boxes, and seedlings (approximately 25 d old) were transplanted on 31 May 2022. In 2024, the sowing and transplanting dates were adjusted for each cultivar based on the heading dates in 2022 to synchronize the heading period. In both years, the planting density was 22.2 hills m− 2 (300-mm row spacing, 150-mm hill spacing). Three seedlings per hill were transplanted in two rows (15 plants per row, 2.1 m) for each cultivar. N (6 g m− 2 as urea), P (8 g m− 2 as single superphosphate), and K (9 g m− 2 as potassium chloride) were applied as basal fertilizer before transplanting. N (4 g m− 2 as ammonium sulfate) and P (3 g m− 2 as single superphosphate) were applied as top dressings at the tillering stage on 12 July 2022, and 20 July 2024. Weeds, insects, and diseases were prevented by administering herbicides and pesticides as needed. The plots were arranged in a randomized block design with four replicates. The cultivar arrangement in the plot was fully randomized in 2022, whereas two cultivars with similar transplant dates were randomly placed next to each other in 2024. Border plants were excluded from sampling to minimize edge effects.

In 2022, four main stems were sampled from different plants at 5 d after heading (DAH), when the first internode had completed elongation. One stem whose culm length was closest to the mean of the four sampled stems was selected as a representative. This representative stem was used for all subsequent morphological and biochemical measurements. Therefore, the replicate plot was treated as the experimental unit for statistical analyses (n = 4). The selected stems were divided into individual internodes and leaf sheaths, and the lengths of each internode and leaf sheath were measured. An approximately 1 mm-thick cross-section was cut at the midpoint of each internode using a razor blade, stained with safranin, and scanned using a GT-X980 scanner (Epson, Nagano, Japan) for cross-sectional trait analysis. Internodes at each position (including the decolorized section prepared for cross-sectional imaging), leaf sheaths, leaf blades, and panicle were dried at 80 °C for at least 72 h and weighed. Each internode and leaf sheath was ground to a powder using a ShakeMaster Auto (Biomedical Science, Tokyo, Japan) for soluble sugar and starch measurements.

In 2024, three whole plants per plot were sampled at full heading, when 80–90% of the panicles had fully emerged, and dried at 80 °C for at least 72 h. One plant whose aboveground dry weight was closest to the mean was selected as a representative. This representative plant was used for all subsequent organ weight and NSC measurements in each plot (n = 4). The plant was divided into panicles, leaf blades, culms, and leaf sheaths, and each organ was weighed. Culms and leaf sheaths were ground to powder using a Wiley laboratory mill (1029-C, Yoshida Seisakusho, Tokyo, Japan) and a Hi-speed vibration sample mill (TI-200, Cosmic Mechanical Technology, Fukushima, Japan) for soluble sugar and starch measurements. Three main stems per plot were sampled and one stem with a culm length closest to the mean was selected. The selected stem was divided into individual internodes, and the internode length and cross-sectional traits were measured as in 2022. To assess the NSC-buffering effect under source-limited conditions during the grain-filling period, all flags and second leaves were manually removed from the four plants per plot at full heading. At maturity, panicles from four plants with or without defoliation treatment were harvested and threshed, and their dry weights were determined after drying at 80 °C for at least 72 h. Total spikelet numbers per plant were counted in plants without defoliation treatment. The representative-sampling approach in the field experiments was adopted to obtain samples that best reflected the average characteristics of each plot for detailed morphological and biochemical analyses.

Pot Experiment

A pot experiment was conducted in a greenhouse at ISAS using the cultivar ‘Hokuriku 193’, one of the highest-yielding cultivars in Japan (Okamura et al. 2022). Seeds were sown in a seedling nursery box on 5 May, and ten seedlings were transplanted into 1/5000-a Wagner pots in a circular arrangement on 1 June 2024. All emerging tillers were removed throughout the growth period so that only the main stem developed. Plant growth regulator treatments were applied at 25 d before heading (DBH) and 3 DBH, corresponding to the periods of lower and upper internode elongation, respectively (Wakabayashi et al. 2022).

Seven treatment groups were established based on a combination of application timing and chemical components (Fig. S1A). A 100-µL aliquot of either 70 µM gibberellin solution (GA₃ dissolved in 0.6% [v/v] ethanol) or 100 µM uniconazole solution (uniconazole-P dissolved in 0.6% [v/v] ethanol) was applied to each plant for three consecutive days, following previously reported solvent systems with minor modifications (Nagai et al. 2020). The control plants were treated with a mock solution containing 0.6% (v/v) ethanol. The solutions were injected into the gap between the leaf sheaths using a micropipette (Fig. S1B). To affect the elongation of the fourth internode (IN4), the leaf sheath attached to the fourth leaf blade below the uppermost expanding leaf was targeted on 28–30 July. To affect the elongation of the second internode (IN2), the second leaf sheath was treated on 23–25 August.

At 0 DAH, when the first and second internodes (IN1 and IN2) were elongating, internodes IN2 and IN4 and their corresponding leaf sheaths (LS2 and LS4) were sampled from five plants and immediately frozen in liquid N₂. These samples were ground into a powder using a ShakeMaster Auto for ADP-glucose pyrophosphorylase (AGPase) activity assays. At 5 DAH, five plants were sampled and divided into panicles, leaf blades, culms, and leaf sheaths. The culm and leaf sheaths were further divided into individual nodal segments. Internode length, cross-sectional traits, and leaf sheath length were measured as in the field experiments. Each organ was dried at 80 °C for at least 72 h and weighed. Each internode and leaf sheath was ground to a powder for soluble sugar and starch measurements.

Analysis of Images Obtained using a Scanner

The cross-sectional traits (diameter, wall thickness, and cross-sectional area) of each internode were analyzed from the scanned images (Fig. S2). The areas of the outer and inner circles were measured using ImageJ software (ver. 1.54 g). Each morphological trait was calculated using the following equation:

graphic file with name d33e445.gif
graphic file with name d33e449.gif

Cross-sectional area = outer circle area – inner circle area.

Volume = internode length × cross-sectional area.

Volume composition ratio (VCR) = volume of the internode(s) / total culm volume.

Measurement of Starch and Soluble Sugars

All samples used for NSC analysis were collected between 15:00 and 18:00 to minimize potential effects of diurnal variation in NSC concentration. Soluble sugar (sucrose, glucose, and fructose) and starch contents were measured according to the method of Okamura et al. (2013). Approximately 20 mg of dried powder was extracted with 80% ethanol. Soluble sugars (sucrose, glucose, and fructose) were quantified enzymatically using an E-kit (E1247A; J.K. International, Tokyo, Japan). The ethanol-insoluble residue was subsequently digested with glucoamylase (Toyobo Co., Osaka, Japan), and starch content was determined enzymatically using the same E-kit. Absorbance at 340 nm was measured using a microplate reader (Synergy H1; Agilent Technologies, California, USA), reflecting NADPH production during the enzymatic conversion of hexoses. The concentrations of soluble sugars and starch were calculated according to the manufacturer’s instructions. NSC content was defined as the sum of soluble sugar and starch contents. Residual components (RC) were calculated by subtracting NSC content from organ dry weight. Thus, RC represents the non-NSC fraction of the organ and includes structural carbohydrates, proteins, lipids, minerals, and other components. NSC/RC was calculated as the ratio of NSC content to RC content and used as an indicator of NSC accumulation efficiency.

Enzyme Activity Assay

The activity of ADP–glucose pyrophosphorylase (AGPase; EC 2.7.7.27) was analyzed because it catalyzes the first committed step of starch biosynthesis and is widely used as an indicator of starch biosynthetic capacity in rice stems (Okamura et al. 2013, 2018; Jiang et al. 2022). Approximately 50 mg of the ground sample was suspended in 10 volumes of extraction buffer (50 mM HEPES–KOH (pH 7.4), 5 mM MgCl₂, 2 mM EDTA, 12.5% [v/v] glycerol, 5 mM DTT, 5% [w/v] polyvinylpolypyrrolidone, and one tablet of protease inhibitor cocktail [cOmplete Mini, EDTA-free] per 10 mL). After centrifugation at 12,000 × g for 5 min at 4 °C, the supernatant was used as the crude enzyme extract for the AGPase assays.

The AGPase activity assay was conducted in reaction mixtures consisting of 20 µL crude enzyme sample and 174 µL reaction solution containing 50 mM HEPES–KOH (pH 7.4), 3 mM 3-phosphoglycerate, 4 mM pyrophosphate, 5 mM MgCl2, 4 mM DTT, 0.8 mM NADP+, 0.5 U phosphoglucomutase, and 1 U glucose-6-phosphate dehydrogenase. The reaction was initiated by the addition of 6 µL of ADP-glucose (final concentration, 3 mM), and the increase in absorbance at 340 nm was monitored at 30 °C for 10 min using a microplate reader. The AGPase activity was calculated as the difference between the reaction rate after the addition of ADP–glucose and the pre-addition baseline rate.

Statistical Analysis

All statistical analyses were performed using R software (v.4.0.3). Cultivar effects on NSC-related and morphological traits were evaluated using a one-way analysis of variance (ANOVA), followed by Tukey’s honestly significant difference (HSD) test for multiple comparisons among cultivars. In the growth-regulator experiment, MM (mock-treated plants receiving solvent only) was used as the control and the differences between MM and each treatment were assessed using Dunnett’s test. The relationships between NSC-related and morphological traits were examined using Pearson’s correlation coefficients. All the hypothesis-based statistical tests were two-sided. Hierarchical clustering was performed using Ward’s method on a correlation matrix. In the field experiments, n represents the number of replicate plots, whereas in the pot experiment, n represents the number of individual plants.

Results

NSC Accumulation Traits

In the 2022 field experiment, NSC accumulation traits were evaluated in the main culm to characterize cultivar differences in each internode. Although all cultivars are generally classified as heavy-panicle types, they differed in panicle number and heading time (Fig. S3; Table S1). Therefore, in the 2024 experiment, NSC accumulation in culms was evaluated at the whole-plant level, with sowing dates adjusted to minimize the variation in heading time (Yonemaru et al. 2014) (Table S1). Compared with the 2022 experiment, cultivar differences in air temperature and solar radiation during the pre-heading period were smaller in the 2024 experiment (Fig. S4). Culm NSC content showed no correlation with air temperature or solar radiation during the pre-heading stage (Fig. S5), indicating that genetic factors were the primary drivers of NSC variation.

Significant cultivar differences were observed in the main culm NSC content in 2022 (Fig. 1A), and similar differences were detected at the whole-plant level in 2024 (Fig. 1B, C), indicating that NSC accumulation in the main culm reflected that at the whole-plant level. NSC content differed significantly among cultivars in all internodes (IN1–IN5+), and the magnitude of cultivar variation was greater in IN4 and IN5 + than in the upper internodes, as indicated by the larger F values (Table S2). To further characterize the relationship between internode morphology and NSC accumulation, NSC content was partitioned into two components: residual components (RC) and NSC/RC. This approach allowed us to distinguish whether cultivar differences in NSC accumulation were primarily associated with variation in dry matter investment (RC) or in the efficiency of NSC accumulation per unit of invested RC (NSC/RC). Both RC and NSC/RC also showed significant cultivar differences at every internode as well as in the main and whole-plant culms (Table S2).

Fig. 1.

Fig. 1

Open in a new tab

Culm NSC accumulation and its relationships with morphological and NSC-related traits for each cultivar. A NSC content of the main culm at heading in 2022. Bars represent stacked NSC contents of individual internodes (IN1–IN8). Bars show means ± SE (n = 4). Different letters above bars indicate significant differences among the cultivars (Tukey’s HSD, P < 0.05). Cultivar abbreviations are as follows: M23, Milyang 23; TN, Takanari; AH, Akenohoshi; N11, Nanjing 11; YA, Yumeaoba; MR, Momiroman; TQ, Teqing; H193, Hokuriku 193; HA, Hoshiaoba; and KH, Kusanohoshi. B NSC content at the whole-plant culm level in 2024. Bars show means ± SE (n = 4). Different letters above bars indicate significant differences among the cultivars (Tukey’s HSD, P < 0.05). C Relationship between the main culm NSC content (2022) and the whole-plant culm NSC content (2024). The regression line is shown with its 95% confidence interval (shaded). Correlation coefficients (r) and P-values are from Pearson’s tests (n = 10). D Correlation matrix among NSC-related traits (NSC, RC, NSC/RC) of individual internodes (IN1–IN5+) in the main culm or whole-plant culms. IN5 + indicates internodes at and below IN5. Circle size and color indicate correlation strength and direction, respectively (Pearson’s r). Significance levels: † P < 0.10, * P < 0.05, ** P < 0.01, *** P < 0.001 (n = 10)

Correlation analyses indicated that RC in IN3–IN5 + was positively associated with NSC in IN2–IN5+, whereas RC in IN1 and IN2 showed no such relationship with any of the internodes (Fig. 1D). NSC/RC was strongly correlated with NSC in the same or adjacent internodes within a culm. At the whole-plant level, NSC was positively correlated with both RC and NSC/RC.

Leaf sheath NSC also differed among cultivars, and showed strong positive correlations with culm NSC except in two cultivars (MR and HA) (Fig. S6). The regression slopes indicated that NSC accumulation in leaf sheaths reached one-third to one-half of the culm NSC content, reflecting parallel variation between the two organs while differing in the extent of NSC accumulation. In addition, culm NSC, but not leaf-sheath NSC, was negatively correlated with the reduction ratio of grain dry weight under defoliation, indicating that culm NSC contributed more strongly to mitigating yield loss than leaf-sheath NSC (Fig. S7).

Morphological Traits

To evaluate cultivar differences in the morphological traits of each internode, internode volume, length, cross-sectional area, diameter, and wall thickness were quantified. Significant cultivar differences were observed in internode volume across all internodes in both years, with greater variation observed in the lower internodes (Fig. 2B; Table S3, S4). Most other morphological traits showed significant cultivar differences, except for the cross-sectional areas of IN1 and IN5 + and the wall thickness of IN2 in 2022. Correlation analyses indicated that internode length was positively associated with volume in all internodes in 2022 and in IN3–IN5 + in 2024 (Fig. 2C). The cross-sectional area was positively correlated with the volume in IN2 in both years. The diameter exhibited a consistently stronger relationship with the cross-sectional area than did the wall thickness. In particular, the diameters of IN2–IN4 were significantly correlated with the cross-sectional area in both years.

Fig. 2.

Fig. 2

Open in a new tab

Morphological traits of individual internodes for each cultivar. A Main culm at heading for each cultivar. Each internode position is indicated by a colored dashed line. The bottom panel shows cross-sectional images of each internode, aligned by cultivar and nodal position, indicating genotypic variation in internode diameter and wall thickness. Scale bars indicate 100 mm for the whole culm (top) and 10 mm for the transverse cross-sections of internodes (bottom). B Internode volume for each cultivar in 2022 (left) and 2024 (right). Bars represent stacked volumes of the individual internodes. Bars show means ± SE (n = 4). Different letters above bars indicate significant differences among the cultivars (Tukey’s HSD, P < 0.05). C Relationships between internode volume and its component traits (internode length, cross-sectional area, diameter, and wall thickness) for each internode position (IN1–IN5+) in 2022 and 2024. Red or blue lines indicate positive or negative correlations, respectively. Line thickness corresponds to correlation strength. Significance levels: † P < 0.10, * P < 0.05, ** P < 0.01, *** P < 0.001 (n = 10).

Morphological Factors Associated with NSC Accumulation

To clarify the relationship between morphological factors and NSC accumulation, the correlations between internode volume and NSC-related traits at each internode were analyzed (Fig. 3A). The volumes of IN1 and IN2 had no significant correlation with NSC, RC, or NSC/RC in most internodes, indicating a minimal contribution of the upper internodes to culm NSC accumulation. In contrast, the volumes of IN3–IN5 + were positively correlated with NSC and RC in most of IN3–IN5 + as well as in the culm, and with NSC/RC across multiple internodes. Therefore, IN3–IN5 + play a major role in culm NSC accumulation. Cluster analysis indicated that the RC and volumes of IN1 and IN2 formed a distinct cluster separate from other traits, including culm NSC (Fig. 3B). Based on these results, IN1 and IN2 were defined as upper internodes (UIN) and IN3–IN5 + as lower internodes (LIN). Both UIN and LIN volumes showed significant cultivar differences, with the variation being larger in LIN than in UIN in both years (Fig. 3C). Cultivar differences were also observed in the volume composition ratio (VCR) of UIN and LIN within the culm.

Fig. 3.

Fig. 3

Open in a new tab

Relationships among NSC-related traits and internode morphological characteristics across cultivars. A Correlation matrix between the internode volume and NSC-related traits (NSC, RC, NSC/RC) for each internode (IN1–IN6). Significance levels: † P < 0.10, * P < 0.05, ** P < 0.01, and *** P < 0.001(n = 10). B Heatmap of pairwise correlations among the NSC, RC, NSC/RC, and internode volumes in 2022. Hierarchical clustering (Ward’s method) highlights trait groups showing similar correlation patterns across the cultivars. C Cultivar differences in the internode volume (top) and VCR (bottom) for UIN (IN1–IN2) and LIN (IN3–IN5+) in 2022 (left) and 2024 (right). Bars show means ± SE (n = 4). Different letters above bars indicate significant differences among the cultivars (Tukey’s HSD, P < 0.05). F values and significance levels from the ANOVA are shown in each panel. Significance levels: *** P < 0.001. The VCRs of UIN and LIN are complementary components of a proportional index that sums up to one within a culm. Therefore, both components exhibit identical F values and share the same groupings in multiple-comparison tests

To further identify the morphological factors most strongly associated with NSC accumulation, the relationships between NSC content and morphological traits were examined with their year-to-year reproducibility (Fig. 4A). In three relationships— between main-culm morphological traits and either main culm NSC or whole-plant NSC, and the year-to-year reproducibility of each trait— the VCR in IN1, IN2, IN4, IN5, UIN and LIN, the volumes in IN4 and IN5+, and the length in IN3 and IN4 showed significant correlations. In particular, the VCR in UIN and LIN (complementary traits that sum up to one within a culm) showed a relatively strong correlation in each relationship (Figs. 4B; S8), indicating that these traits were less susceptible to environmental factors and were the most suitable indicators for evaluating cultivar differences in terms of NSC accumulation.

Fig. 4.

Fig. 4

Open in a new tab

Relationships between internode morphological traits and culm NSC accumulation. A Correlation coefficients between internode morphological traits (VCR, volume, length, cross-sectional area, diameter, and wall thickness) and main culm NSC content in 2022 (left), whole-plant culm NSC content in 2024 (middle), and year-to-year reproducibility of each trait (right). Bars represent Pearson’s correlation coefficients for each internode (IN1–IN5+), including UIN (IN1–IN2) and LIN (IN3–IN5+). Red and blue bars indicate positive and negative correlations, respectively. Significance levels: † P < 0.10, * P < 0.05, ** P < 0.01, *** P < 0.001 (n = 10). B Relationships between LIN VCR and main culm NSC content in 2022 (left), between LIN VCR and whole-plant culm NSC content in 2024 (middle) and between LIN VCR in 2022 and 2024 (right), showing year-to-year stability. Regression lines are shown with 95% confidence intervals (shaded). Correlation coefficients (r) and P-values are from Pearson’s tests (n = 10)

Effect of VCR-altering Treatment on NSC Accumulation

Based on the results of the field experiments using multiple cultivars, it was hypothesized that the VCR of UIN/LIN within a culm was a key morphological factor associated with NSC accumulation. To test this, gibberellin (GA) and uniconazole (UZ) treatments were applied to modify the VCR in Hokuriku 193 (Fig. 5A). GA and UZ treatments targeting IN4 significantly increased or decreased LIN volumes, respectively, except in UG (Fig. 5B). Treatments targeting IN2 increased or decreased the UIN volumes, except in GU. Consequently, the VCR of UIN or LIN was altered in each treatment group, with most changes explained by alterations in the internode length rather than in the cross-sectional area (Fig. 5C).

Fig. 5.

Fig. 5

Open in a new tab

Effects of plant growth regulator treatments on internode morphology and VCR of the main culm. A Main culm for each treatment group (MM, UM, GM, MU, MG, UG, GU). Each internode position is indicated by a colored dashed line (IN1–IN5). The bottom panel shows cross-sectional images of each internode, aligned by treatment and nodal position, indicating treatment variation in internode diameter and wall thickness. Scale bars indicate 100 mm for the whole culm (top) and 10 mm for the transverse cross-sections of internodes (bottom). B Effects of gibberellin (GA) and uniconazole (UZ) on UIN (IN1–IN2) and LIN (IN3–IN5+) morphology. Volume (top) and volume composition ratio (VCR) (bottom) of UIN and LIN are shown. UIN VCR and LIN VCR are complementary values and sum to 1 within a culm. Bars show means ± SE (n = 5). Horizontal brackets indicate statistically significant differences among treatments (Dunnett vs. MM, * P < 0.05, ** P < 0.01, *** P < 0.001). C Correlations between internode volume and morphological traits (length, cross-sectional area, diameter, and wall thickness) for IN1–IN5+. Red or blue lines indicate positive or negative correlations, respectively. Line thickness corresponds to correlation strength. Significance levels: † P < 0.10, * P < 0.05, ** P < 0.01, *** P < 0.001 (n = 7)

The culm NSC content increased significantly in GU and decreased in UM and UG relative to MM (Fig. 6A). Although not statistically significant, NSC tended to be higher in GM and MU and lower in MG. The UIN volume was not correlated with culm NSC, whereas the LIN volume was positively correlated (Fig. 6B). The VCR of UIN or LIN within a culm showed strong correlations with culm NSC, which was consistent with the field experiments (Figs. 4B and 6B). NSC-related traits were examined in the UIN and LIN to further clarify the basis of these changes (Fig. 6C). The NSC of UIN was significantly higher in GM, accompanied by increases in both RC and NSC/RC, despite no changes in the UIN volume. An increase in NSC/RC was also observed in GU, indicating that GA applied to IN4 influenced NSC accumulation in the upper internodes. No decline in UIN NSC was observed in MG or UG, although both treatments showed increases in RC and reductions in NSC/RC. In LIN, NSC decreased in UM and UG due to reductions in RC. Although not statistically significant, MG and UG showed a slight decline in NSC/RC, suggesting that enhanced elongation of the upper internodes may have limited NSC accumulation in the lower internodes. In contrast, GU exhibited an increase in the lower-internode NSC content due to a large increase in RC, despite the reduced NSC/RC. GM showed no increase in NSC because the increase in RC was offset by a substantial decrease in NSC/RC. Although the effects were not statistically significant, MU showed a slight increase in both RC and NSC/RC, which may account for the differences in NSC levels between GM and GU. Morphological changes in the internodes affected NSC accumulation not only in the culm, but also in the leaf sheaths (Fig. S9). Leaf sheath NSC decreased significantly in MG and UG, mainly due to a reduction in NSC in the lower leaf sheaths (LS3–LS6) rather than the upper leaf sheaths (LS1 and LS2).

Fig. 6.

Fig. 6

Open in a new tab

Effects of VCR-modifying treatments on culm NSC accumulation and NSC-related traits in upper and lower internodes. A Culm NSC content at 5 d after heading for each treatment (MM, UM, GM, MU, MG, UG, GU). Bars represent stacked NSC contents of individual internodes (IN1–IN6). Bars show means ± SE (n = 5). Horizontal brackets indicate significant differences among treatments (Dunnett vs. MM, ** P < 0.01). B Relationships between culm NSC content and the volume of UIN (IN1–IN2) (top left) and LIN (IN3–IN5+) (top right), as well as the VCR of UIN (bottom left) and LIN (bottom right). Regression lines are shown with 95% confidence intervals (shaded). Correlation coefficients (r) and P-values are from Pearson’s tests (n = 7). C NSC-related traits in UIN and LIN for each treatment. NSC content, RC content, and NSC/RC in UIN (top) and LIN (bottom) are shown. D AGPase activity in IN2, IN4, LS2 and, LS4. Bars show means ± SE (n = 5). Horizontal brackets indicate statistically significant differences among the treatments (Dunnett vs. MM, † P < 0.10, * P < 0.05, ** P < 0.01, *** P < 0.001)

To investigate a potential physiological mechanism underlying the effects of VCR on NSC accumulation, the AGPase activity per organ was determined as an indicator of starch biosynthetic capacity, which may reflect one aspect of sink strength in IN2, IN4, LS2, and LS4 (Fig. 6D). AGPase activity in IN2 increased significantly in GM and GU and decreased in MG and UG, largely consistent with the changes in NSC/RC in these treatments. In IN4, AGPase activity increased in GM and GU, but decreased in UM and UG. These results suggest that elongation of the upper internodes reduced the sink strength within the same internode, whereas elongation of the lower internodes exerted an opposing effect. No significant differences were observed in LS2. In contrast, AGPase activity in LS4 decreased significantly in MG and UG and slightly increased in MU, indicating that lower leaf sheaths were more sensitive to changes in upper internode morphology than upper leaf sheaths.

Discussion

Contrasting Roles of Upper and Lower Internodes in Culm NSC Storage

The relationships between NSC accumulation and various morphological traits in the culm were examined and clearly demonstrated that the volume composition ratio (VCR) of the internodes was a trait strongly associated with NSC accumulation capacity. The contribution of internode volume to NSC accumulation differed markedly between the upper internodes (UIN: IN1 and IN2) and lower internodes (LIN: IN3–IN5+). The volume of UIN showed no or even a negative association with NSC accumulation (Fig. 3A). In particular, IN2 volume was negatively correlated with NSC accumulation efficiency (NSC/RC) in IN2, and this negative relationship was supported by the experiment with the plant growth regulator (Fig. 6C, D). During rapid internode elongation, a substantial proportion of assimilated carbon is invested in structural growth, as evidenced by the strong accumulation of cell wall components in the elongating internodes (Lin et al. 2017). Therefore, assimilate investment for internode elongation and structural growth is likely to compete with NSC accumulation (Fujita and Yoshida 1984; Arai-Sanoh et al. 2011; Botha et al. 2023), and reduce the efficiency of these internodes as storage organs.

In contrast, the volume of LIN was a major contributor to culm NSC accumulation (Fig. 3A). Culms with larger LIN volumes exhibited greater NSC storage capacities, which is consistent with previous findings in wheat (Ehdaie et al. 2006a). These larger LIN volumes were primarily attributable to increased internode length rather than cross-sectional traits (Fig. 2C), as in sweet sorghum (Bihmidine et al. 2015). Our previous study indicated that the LIN function as major NSC storage organs during the pre-heading stage because they begin elongating earlier and act as sinks sooner than the UIN (Wakabayashi et al. 2022). Therefore, this temporal advantage likely enables the larger LIN to accumulate NSC more efficiently (Botha and Marquardt 2024), even though the larger LIN require greater carbon investment for their elongation and structural formation, as observed for the UIN. The positional differentiation of internodes in carbohydrate storage has also been reported in other crops, including wheat (Ehdaie et al. 2006b; Li et al. 2013; Chen et al. 2014; Joudi et al. 2024), sweet sorghum (Hoffmann-Thoma et al. 1996; Gutjahr et al. 2013; Bihmidine et al. 2015; Shukla et al. 2017; Kanbar et al. 2021), and sugarcane (Wu and Birch 2007; Vasantha et al. 2022; Botha et al. 2023; Botha and Marquardt 2024), in which mature lower internodes preferentially accumulate carbohydrates. In grasses, internode elongation is generally initiated in the lower internodes and proceeds acropetally. Accordingly, the internode volume composition reflects not only the spatial architecture but also the temporal hierarchy of sink establishment within grass culms.

Despite the functional differentiation between UIN and LIN, the LIN exerted positive effects not only on their own NSC storage but also on NSC accumulation efficiency in the UIN, as indicated by the positive associations between the NSC/RC of the UIN and the residual components (RC) or volume of the LIN (Figs. 1D and 3A). This observation was supported by the plant growth regulator experiment, in which the elongation of LIN enhanced sink strength in UIN, thereby increasing their NSC accumulation (Fig. 6C, D). These results suggested that the increased sink strength of LIN, associated with their larger volume, enhanced the overall sink strength within a culm.

Unlike previous studies that emphasized growth duration or biomass production (Nagata et al. 2002; Takai et al. 2006), culm NSC accumulation in this study was more closely associated with dry matter allocation to the culm (Fig. S10). Cultivars with larger LIN volumes exhibited higher dry matter allocation to the culm, which likely contributed to greater NSC accumulation. This preferential allocation of assimilates to culms with larger LIN likely explains why the enlargement of LIN promotes NSC accumulation efficiency in UIN, as discussed above. Moreover, such enhanced sink demand by the culm may also mitigate the sugar-mediated feedback inhibition of leaf photosynthesis by facilitating continuous assimilate export from the source leaves, which may lead to increased assimilate allocation to the culm, as proposed in source-sink regulation models (Slewinski 2012).

Taken together, the cultivars with smaller upper internodes and larger lower internodes exhibited a higher capacity for NSC accumulation in the culm, which could be attributed to the contrasting contributions of the upper and lower internodes to NSC storage (Fig. 7). Nevertheless, the responses observed in the plant growth regulator experiment cannot be attributed solely to changes in internode volume allocation, because gibberellin and uniconazole may also affect other aspects of plant growth and physiology, including source–sink relationships and carbohydrate metabolism. Therefore, although the treatment responses support the association between internode volume and culm NSC accumulation, further studies using genetic approaches will be required to establish its causal basis.

Fig. 7.

Fig. 7

Open in a new tab

Conceptual model linking internode morphology to culm NSC accumulation. This diagram summarizes how morphological and physiological characteristics of the upper internodes (UIN; IN1–IN2) and lower internodes (LIN; IN3–IN5+) differentially contribute to culm NSC storage. Cultivars with high NSC accumulation capacity are characterized by smaller UIN volumes and larger LIN volumes. Reduced structural investment in the UIN is associated with higher NSC accumulation efficiency (NSC/RC) in these internodes. In contrast, the enlarged LIN exhibit greater structural volume, higher RC, and larger NSC pools, indicating a greater capacity for NSC storage. Based on these observations, larger LIN may contribute to enhanced sink demand and increased assimilate partitioning to the culm

We further considered the relationship between culm NSC accumulation and grain yield. NSC stored in the stem can serve as an important carbon reserve for grain filling and contribute to high grain yield, particularly in cultivars with extra-large sink capacities (Chen et al. 2019; Fu et al. 2011; Lin et al. 2024). However, in the present study, neither culm NSC content nor VCR showed a significant correlation with grain yield under normal field conditions (Fig. S11), although culm NSC was associated with reduced grain dry weight loss under source-limited conditions caused by defoliation (Fig. S7). This lack of correlation may reflect differences in grain-filling ability among cultivars. For example, KH and HA accumulated large amounts of NSC but exhibited poor grain filling because of limited starch biosynthetic capacity in developing spikelets (Wakabayashi et al. 2022). Therefore, the contribution of culm NSC accumulation to grain yield under normal conditions may vary among cultivars because the physiological factors limiting yield formation are not necessarily the same across cultivars.

VCR as a Robust Indicator of Culm NSC Accumulation Capacity

To identify a robust morphological indicator associated with NSC accumulation capacity and provide implications for breeding programs, several morphological traits were evaluated (Fig. 4A). The main stem VCR of the UIN/LIN emerged as the most suitable indicator because it consistently showed the strongest correlation with NSC accumulation, not only in the main culm, but also at the whole-plant level (Fig. 4B). This is likely because VCR integrates both the negative contributions of UIN and the positive contributions of LIN, whereas simple volume metrics capture only the absolute size without reflecting these contrasting functional effects. In addition to its strong association with NSC accumulation, the VCR exhibited high year-to-year reproducibility across experiments (Fig. 4B). This stability suggests that VCR serves as a reliable predictor for evaluating the genetic basis of NSC storage capacity, as it is less affected by environmental fluctuations than NSC accumulation itself (Nagata et al. 2001; Wakabayashi et al. 2022). Nevertheless, the present study was conducted using a limited number of cultivars and environments, and further validation across broader genetic backgrounds and environmental conditions will be required to establish the general applicability of VCR. From a practical perspective, although VCR measurement requires destructive sampling, it can be quantified far more rapidly and with a substantially higher throughput than biochemical NSC analysis, which involves labor-intensive extraction and colorimetric procedures. Accordingly, these advantages indicate that VCR is a practical and robust phenotypic indicator for breeding programs aimed at enhancing stem NSC storage capacity.

Relationships between Leaf Sheath NSC Accumulation and Morphological Traits of Internodes

Although the NSC content and buffering effect against yield loss were lower in the leaf sheath than in the culm (Figs. S6B, S7B), leaf sheaths represent an important temporal NSC storage organ (Nagata et al. 2001; Chen and Wang 2008). Leaf sheath NSC content was strongly correlated with culm NSC content (Fig. S6B), suggesting that internode morphological traits also influenced NSC accumulation in leaf sheaths. Active elongation of the UIN was associated with a reduction in NSC content in the leaf sheaths (Figs. S9, S12), which was accompanied by changes in the starch biosynthetic capacity of the lower leaf sheaths (Fig. 6D). Leaf sheaths, particularly those at lower positions, transition from sink to source organs earlier than the culm, even at the pre-heading stage (Wakabayashi et al. 2022). Therefore, NSC accumulation in these tissues may be particularly sensitive to the assimilation demands generated by the elongation of the upper internodes. In contrast, the elongation-promoting LIN treatment increased NSC accumulation in the upper leaf sheaths. However, this effect was likely indirect and attributable to the concomitant elongation of the upper leaf sheaths (Table S7). At the cultivar level, genotypes with longer LIN consistently exhibited longer lower leaf sheaths, suggesting that such morphological coordination may influence NSC accumulation in the leaf sheaths (Fig. S13, Table S8). However, several cultivars deviated from the general relationship between culm and leaf sheath NSC accumulation (Figs. S6, S12), indicating that factors other than internode morphology may also contribute to NSC accumulation in leaf sheaths.

Agronomic Consequences of Modifying Internode VCR

Although this study primarily focused on identifying morphological traits associated with culm NSC accumulation, changes in internode VCR inevitably alter plant architecture. Therefore, the potential agronomic consequences of VCR modification, particularly for lodging resistance and panicle development, should also be considered. Several studies have reported that elongation of the lower internodes negatively affects lodging resistance in rice (Wu et al. 2017; W. J. Zhang et al. 2016). However, these studies have primarily evaluated variation induced by nitrogen fertilization or shading. In contrast, analyses using multiple cultivars have shown little relationship between lower internode length and lodging-related traits (Islam et al. 2007; Liu et al. 2018), suggesting that the negative effects of lower internode elongation arise primarily from environmentally induced variation rather than inherent genotypic differences. Meanwhile, in the present study, IN5 + length was strongly and positively correlated with total culm length (Fig. S14), indicating that elongation of the lower internodes accompanied overall culm elongation. Although rice breeding has traditionally favored short-statured cultivars as a primary strategy to improve lodging resistance (Hedden 2003; Shah et al. 2019), the importance of long-culm traits in forage, bioethanol, and high-yield rice cultivars has recently been highlighted (Wu et al. 2011; Okuno et al. 2014; Nomura et al. 2019). Lodging resistance can be achieved even in long-culm cultivars by increasing the culm cross-sectional area and thickness of the cortical fiber tissues (Ookawa et al. 2010, 2014). Therefore, when modifying the length of the lower internodes, it is essential to simultaneously enhance culm stiffness to maintain adequate lodging resistance.

Panicle size was also associated with internode morphology. In particular, the length or diameter of the upper internodes is positively correlated with the spikelet number or panicle length (Yamamoto et al. 2001; Sunohara et al. 2003; Liu et al. 2008; Harshitha et al. 2024). In the present study, the diameters of IN1, IN2, and IN3 were positively correlated with spikelet number (Fig. S15). Therefore, reducing the volume of the upper internodes through selection for smaller culm diameters may lead to yield penalties due to a reduction in spikelet number. In contrast, no significant correlation was observed between the lengths of IN1 and IN2 and spikelet number, suggesting that modification of UIN length is an effective approach to enhancing the NSC accumulation efficiency without negatively affecting panicle size (Sunohara et al. 2006).

Variations in internode VCR also alter the vertical distribution of leaves and canopy structure, potentially affecting within-canopy light interception and micrometeorological conditions. Therefore, further analyses integrating these factors are needed to elucidate how VCR modifications influence yield formation.

Conclusions

In the current study, the volume composition ratio of internodes within a culm was identified as a key trait associated with NSC accumulation capacity in rice. By integrating the contrasting contributions of the upper and lower internodes, VCR provides a robust morphological indicator that is reproducible across environments and cultivars. The findings highlight the importance of internode architecture in regulating carbon allocation within the culm, and offer a practical framework for improving stem carbohydrate storage capacity in rice breeding programs.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1. (5.9MB, pdf)
Supplementary Material 2. (52.6KB, xlsx)

Acknowledgements

We thank the staff at the Institute for Sustainable Agro-ecosystem Services (ISAS), The University of Tokyo, for technical support in rice cultivation and management.

Abbreviations

LIN

Lower internodes

NSC

Non-structural carbohydrates

RC

Residual components

UIN

Upper internodes

VCR

Volume composition ratio

Author Contributions

Y.W. designed and conducted the experiments, analyzed the data, and prepared the manuscript. Y.W. and M.S. performed the quantification of soluble sugars and starch and measured AGPase activity. All authors read and approved the final manuscript.

Funding

This work was supported by JSPS KAKENHI (Grant Numbers 23K13935 to Y.W. and 22KK0083 to Y.K.).

Data Availability

The datasets supporting the conclusions of this article are included within the article and its additional files.

Declarations

Ethics Approval and Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Competing Interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Arai-Sanoh Y, Ida M, Zhao R et al (2011) Genotypic variations in non-structural carbohydrate and cell-wall components of the stem in rice, sorghum, and sugarcane. Biosci Biotechnol Biochem 75:1104–1112. 10.1271/bbb.110009 [DOI] [PubMed] [Google Scholar]
  2. Arai-Sanoh Y, Ida M, Zhao R et al (2013) Varietal differences in cell wall β-(1→3),(1→4)-glucan and nonstructural carbohydrate in rice stems during the grain filling stage. Plant Prod Sci 16:335–341. 10.1626/pps.16.335 [DOI] [Google Scholar]
  3. Bihmidine S, Baker RF, Hoffner C, Braun DM (2015) Sucrose accumulation in sweet sorghum stems occurs by apoplasmic phloem unloading and does not involve differential Sucrose transporter expression. BMC Plant Biol 15:186. 10.1186/s12870-015-0572-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Botha FC, Marquardt A (2024) Metabolic Control of Sugarcane Internode Elongation and Sucrose Accumulation. Agronomy 14:1487. 10.3390/agronomy14071487 [DOI] [Google Scholar]
  5. Botha FC, Scalia G, Marquardt A, Wathen-Dunn K (2023) Sink Strength During Sugarcane Culm Growth: Size Matters. Sugar Tech 25:1047–1060. 10.1007/s12355-023-01273-0 [DOI] [Google Scholar]
  6. Chen HJ, Wang SJ (2008) Molecular regulation of sink-source transition in rice leaf sheaths during the heading period. Acta Physiol Plant 30:639–649. 10.1007/s11738-008-0160-8 [DOI] [Google Scholar]
  7. Chen W, Deng XP, Eneji AE et al (2014) Dry-Matter Partitioning across Parts of the Wheat Internode during the Grain Filling Period as Influenced by Fertilizer and Tillage Treatments. Commun Soil Sci Plant Anal 45:1799–1812. 10.1080/00103624.2014.907918 [DOI] [Google Scholar]
  8. Chen L, Deng Y, Zhu H et al (2019) The Initiation of Inferior Grain Filling is Affected by Sugar Translocation Efficiency in Large Panicle Rice. Rice 12:75. 10.1186/s12284-019-0333-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Chen K, Łyskowski A, Jaremko Ł, Jaremko M (2021) Genetic and Molecular Factors Determining Grain Weight in Rice. Front Plant Sci 12:605799. 10.3389/fpls.2021.605799 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Cock JH, Yoshida S (1972) Accumulation of 14C-labeled carbohydrate before flowering and its subsequent redistribution and respiration in the rice plant. Japanese J Crop Sci 41:226–234. 10.1626/jcs.41.226 [DOI] [Google Scholar]
  11. Ehdaie B, Alloush GA, Madore MA, Waines JG (2006a) Genotypic variation for stem reserves and mobilization in wheat: I. Postanthesis changes in internode dry matter. Crop Sci 46:735–746. 10.2135/cropsci2005.04-0033 [DOI] [Google Scholar]
  12. Ehdaie B, Alloush GA, Madore MA, Waines JG (2006b) Genotypic variation for stem reserves and mobilization in wheat: II. Postanthesis changes in internode water-soluble carbohydrates. Crop Sci 46:2093–2103. 10.2135/cropsci2006.01.0013 [DOI] [Google Scholar]
  13. FAO (2023) Food and Agriculture Organization of the United Nations, FAOSTAT, Data, Food Balance (2010-) https://www.fao.org/faostat/en/
  14. Fu J, Huang Z, Wang Z et al (2011) Pre-anthesis non-structural carbohydrate reserve in the stem enhances the sink strength of inferior spikelets during grain filling of rice. Field Crops Res 123:170–182. 10.1016/j.fcr.2011.05.015 [DOI] [Google Scholar]
  15. Fujita K, Yoshida S (1984) Partitioning of photosynthates between panicle and vegetative organs of rice under different planting densities. Soil Sci Plant Nutr 30:519–525. 10.1080/00380768.1984.10434719 [DOI] [Google Scholar]
  16. Fukushima A, Ohta H, Yokogami N et al (2017) Effects of genes increasing the number of spikelets per panicle, TAW1 and APO1, on yield and yield-related traits in rice. Plant Prod Sci 20:485–489. 10.1080/1343943X.2017.1365614 [DOI] [Google Scholar]
  17. Gutjahr S, Clément-Vidal A, Soutiras A et al (2013) Grain, sugar and biomass accumulation in photoperiod-sensitive sorghums. II. Biochemical processes at internode level and interaction with phenology. Funct Plant Biol 40:355–368. 10.1071/FP12177 [DOI] [PubMed] [Google Scholar]
  18. Harshitha BS, Singh VJ, Nandakumar S et al (2024) Uncovering QTLs for uppermost internode length and panicle exsertion in rice (Oryza sativa L). Front Sustain Food Syst 8:1470871. 10.3389/fsufs.2024.1470871 [DOI] [Google Scholar]
  19. Hedden P (2003) The genes of the green revolution. Trends Genet 19:5–9 10.1016/s0168-9525(02)00009-4 [DOI] [PubMed] [Google Scholar]
  20. Hirano T, Saito Y, Ushimaru H, Michiyama H (2005) The effect of the amount of nitrogen fertilizer on starch metabolism in leaf sheath of japonica and indica rice varieties during the heading period. Plant Prod Sci 8:122–130. 10.1626/pps.8.122 [DOI] [Google Scholar]
  21. Hoffmann-Thoma G, Hinkel K, Nicolay P, Willenbrink J (1996) Sucrose accumulation in sweet sorghum stem internodes in relation to growth. Physiol Plant 97:277–284. 10.1034/j.1399-3054.1996.970210.x [DOI] [Google Scholar]
  22. IRRI (2016) Leading innovations annual report 2016. ISSN 0074-7793. http://books.irri.org/AR2016_content.pdf
  23. Islam MS, Peng S, Visperas RM et al (2007) Lodging-related morphological traits of hybrid rice in a tropical irrigated ecosystem. Field Crops Res 101:240–248. 10.1016/j.fcr.2006.12.002 [DOI] [Google Scholar]
  24. Jiang Z, Chen Q, Chen L et al (2022) Sink Strength Promoting Remobilization of Non-Structural Carbohydrates by Activating Sugar Signaling in Rice Stem during Grain Filling. Int J Mol Sci 23:4864. 10.3390/ijms23094864 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Joudi M, Esmailpour M, Mohammadi V, Ahmadi A (2024) Employing entire stem might underestimate the amount of carbohydrate remobilization in wheat. Cereal Res Commun 52:1163–1174. 10.1007/s42976-023-00451-w [DOI] [Google Scholar]
  26. Ju C, Buresh RJ, Wang Z et al (2015) Root and shoot traits for rice varieties with higher grain yield and higher nitrogen use efficiency at lower nitrogen rates application. Field Crops Res 175:47–55. 10.1016/j.fcr.2015.02.007 [DOI] [Google Scholar]
  27. Kanbar A, Shakeri E, Alhajturki D et al (2021) Sweet versus grain sorghum: Differential sugar transport and accumulation are linked with vascular bundle architecture. Ind Crops Prod 167:113550. 10.1016/j.indcrop.2021.113550 [DOI] [Google Scholar]
  28. Khush GS (2005) What it will take to feed 5.0 billion rice consumers in 2030. Plant Mol Biol 59:1–6. 10.1007/s11103-005-2159-5 [DOI] [PubMed] [Google Scholar]
  29. Khush GS (2013) Strategies for increasing the yield potential of cereals: Case of rice as an example. Plant Breeding 132:433–436. 10.1111/pbr.1991 [DOI] [Google Scholar]
  30. Li H, Cai J, Jiang D et al (2013) Carbohydrates Accumulation and Remobilization in Wheat Plants as Influenced by Combined Waterlogging and Shading Stress During Grain Filling. J Agron Crop Sci 199:38–48. 10.1111/j.1439-037X.2012.00532.x [DOI] [Google Scholar]
  31. Li G, Hu Q, Shi Y et al (2018) Low Nitrogen Application Enhances Starch-Metabolizing Enzyme Activity and Improves Accumulation and Translocation of Non-structural Carbohydrates in Rice Stems. Front Plant Sci 9:1128. 10.3389/fpls.2018.01128 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Lin F, Williams BJ, Thangella PAV et al (2017) Proteomics coupled with metabolite and cell wall profiling reveal metabolic processes of a developing rice stem internode. Front Plant Sci 8:1134. 10.3389/fpls.2017.01134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Lin Y, Xia Y, Hu Y et al (2024) Inferior spikelet filling is affected by T6P/SnRK1-mediated NSC remobilization in large-panicle rice (Oryza sativa L). Physiol Plant 176:e14469. 10.1111/ppl.14469 [DOI] [PubMed] [Google Scholar]
  34. Liu GL, Mei HW, Yu XQ et al (2008) QTL analysis of panicle neck diameter, a trait highly correlated with panicle size, under well-watered and drought conditions in rice (Oryza sativa L). Plant Sci 174:71–77. 10.1016/j.plantsci.2007.09.011 [DOI] [Google Scholar]
  35. Liu S, Huang Y, Xu H et al (2018) Genetic enhancement of lodging resistance in rice due to the key cell wall polymer lignin, which affects stem characteristics. Breed Sci 68:508–515. 10.1270/jsbbs.18050 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lu Y, Chuan M, Wang H et al (2022) Genetic and molecular factors in determining grain number per panicle of rice. Front Plant Sci 13:964246. 10.3389/fpls.2022.964246 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Lubis I, Shiraiwa T, Ohnishi M et al (2003) Contribution of sink and source sizes to yield variation among rice cultivars. Plant Prod Sci 6:119–125. 10.1626/pps.6.119 [DOI] [Google Scholar]
  38. Mohapatra P, Patel R, Sahu S (1993) Time of Flowering Affects Grain Quality and Spikelet Partitioning Within the Rice Panicle. Aust J Plant Physiol 20:231. 10.1071/PP9930231 [DOI] [Google Scholar]
  39. Morita S, Nakano H (2011) Nonstructural carbohydrate content in the stem at full heading contributes to high performance of ripening in heat-tolerant rice cultivar Nikomaru. Crop Sci 51:818–828. 10.2135/cropsci2010.06.0373 [DOI] [Google Scholar]
  40. Nagai K, Mori Y, Ishikawa S, et al (2020) Antagonistic regulation of the gibberellic acid response during stem growth in rice. Nature 584:109–114 10.1038/s41586-020-2501-8 [DOI] [PubMed]
  41. Nagata K, Yoshinaga S, Takanashi J, Terao T (2001) Effects of Dry Matter Production, Translocation of Nonstructural Carbohydrates and Nitrogen Appication on Grain Filling in Rice Cultivar Takanari, a Cultivar Bearing a Large Number of Spikelets. Plant Prod Sci 4:173–183. 10.1626/pps.4.173 [DOI] [Google Scholar]
  42. Nagata K, Shimizu H, Terao T (2002) Quantitative Trait Loci for Nonstructural Carbohydrate Accumulation in Leaf Sheaths and Culms of Rice (Oryza sativa L.) and their Effects on Grain Filling. Breed Sci 52:275–283. 10.1270/jsbbs.52.275 [DOI] [Google Scholar]
  43. Nakano H, Yoshinaga S, Takai T et al (2017) Quantitative trait loci for large sink capacity enhance rice grain yield under free-air CO2 enrichment conditions. Sci Rep 7:1827. 10.1038/s41598-017-01690-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Nomura T, Arakawa N, Yamamoto T et al (2019) Next generation long-culm rice with superior lodging resistance and high grain yield, Monster Rice 1. PLoS ONE 14:e0221424. 10.1371/journal.pone.0221424 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ohsumi A, Takai T, Ida M et al (2011) Evaluation of yield performance in rice near-isogenic lines with increased spikelet number. Field Crops Res 120:68–75. 10.1016/j.fcr.2010.08.013 [DOI] [Google Scholar]
  46. Okamura M, Hirose T, Hashida Y et al (2013) Starch reduction in rice stems due to a lack of OsAGPL1 or OsAPL3 decreases grain yield under low irradiance during ripening and modifies plant architecture. Funct Plant Biol 40:1137–1146. 10.1071/FP13105 [DOI] [PubMed] [Google Scholar]
  47. Okamura M, Arai-Sanoh Y, Yoshida H et al (2018) Characterization of high-yielding rice cultivars with different grain-filling properties to clarify limiting factors for improving grain yield. Field Crops Res 219:139–147. 10.1016/j.fcr.2018.01.035 [DOI] [Google Scholar]
  48. Okamura M, Hosoi J, Nagata K et al (2022) Cross-locational experiments to reveal yield potential and yield-determining factors of the rice cultivar ‘Hokuriku 193’ and climatic factors to achieve high brown rice yield over 1.2kg m– 2 at Nagano in central inland of Japan. Plant Prod Sci 25:131–147. 10.1080/1343943X.2021.1981140 [DOI] [Google Scholar]
  49. Okawa S, Makino A, Mae T (2003) Effect of Irradiance on the Partitioning of Assimilated Carbon During the Early Phase of Grain Filling in Rice. Ann Bot 92:357–364. 10.1093/aob/mcg147 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Okuno A, Hirano K, Asano K et al (2014) New approach to increasing rice lodging resistance and biomass yield through the use of high gibberellin producing varieties. PLoS ONE 9:e86870. 10.1371/journal.pone.0086870 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Ookawa T, Hobo T, Yano M et al (2010) New approach for rice improvement using a pleiotropic QTL gene for lodging resistance and yield. Nat Commun 1:132. 10.1038/ncomms1132 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Ookawa T, Inoue K, Matsuoka M et al (2014) Increased lodging resistance in long-culm, low-lignin gh2 rice for improved feed and bioenergy production. Sci Rep 4:6567. 10.1038/srep06567 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Pan J, Cui K, Wei D et al (2011) Relationships of non-structural carbohydrates accumulation and translocation with yield formation in rice recombinant inbred lines under two nitrogen levels. Physiol Plant 141:321–331. 10.1111/j.1399-3054.2010.01441.x [DOI] [PubMed] [Google Scholar]
  54. Peng S, Cassman KG, Virmani SS et al (1999) Yield potential trends of tropical rice since the release of IR8 and the challenge of increasing rice yield potential. Crop Sci 39:1552–1559. 10.2135/cropsci1999.3961552x [DOI] [Google Scholar]
  55. Perez CM, Palmiano EP, Baun LC, Juliano BO (1971) Starch Metabolism in the Leaf Sheaths and Culm of Rice1. Plant Physiol 47:404–408. 10.1104/pp.47.3.404 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Powell N, Ji X, Ravash R et al (2012) Yield stability for cereals in a changing climate. Funct Plant Biol 39:539–552. 10.1071/FP12078 [DOI] [PubMed] [Google Scholar]
  57. Samonte SOPB, Wilson LT, McClung AM, Tarpley L (2001) Seasonal dynamics of nonstructural carbohydrate partitioning in 15 diverse rice genotypes. Crop Sci 41:902–909. 10.2135/cropsci2001.413902x [DOI] [Google Scholar]
  58. Shah L, Yahya M, Shah SMA et al (2019) Improving lodging resistance: using wheat and rice as classical examples. Int J Mol Sci 20:4211. 10.3390/ijms20174211 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Shukla S, Felderhoff TJ, Saballos A, Vermerris W (2017) The relationship between plant height and sugar accumulation in the stems of sweet sorghum (Sorghum bicolor (L.) Moench). Field Crops Res 203:181–191. 10.1016/j.fcr.2016.12.004 [DOI] [Google Scholar]
  60. Slewinski TL (2012) Non-structural carbohydrate partitioning in grass stems: A target to increase yield stability, stress tolerance, and biofuel production. J Exp Bot 63:4647–4670. 10.1093/jxb/ers124 [DOI] [PubMed] [Google Scholar]
  61. Sunohara H, Satoh H, Nagato Y (2003) Mutations in panicle development affect culm elongation in rice. Breed Sci 53:109–117. 10.1270/jsbbs.53.109 [DOI] [Google Scholar]
  62. Sunohara H, Miura K, Wu X et al (2006) Effects of Ssi1 Gene Controlling dm-type Internode Elongation Pattern on Lodging Resistance and Panicle Characters in Rice. Breed Sci 56:261–268 10.1270/jsbbs.56.261 [DOI] [Google Scholar]
  63. Takai T, Matsuura S, Nishio T et al (2006) Rice yield potential is closely related to crop growth rate during late reproductive period. Field Crops Res 96:328–335. 10.1016/j.fcr.2005.08.001 [DOI] [Google Scholar]
  64. Taylaran R, Ozawa S, Miyamoto N et al (2009) Performance of a High-Yielding Modern Rice Cultivar Takanari and Several Old and New Cultivars Grown with and without Chemical Fertilizer in a Submerged Paddy Field. Plant Prod Sci 12:365–380. 10.1626/pps.12.365 [DOI] [Google Scholar]
  65. Tu J, Wen F, Li F et al (2025) Analysis of the Relationship Between Assimilate Production and Allocation and the Formation of Rice Quality. Agriculture 15:1011. 10.3390/agriculture15091011 [DOI] [Google Scholar]
  66. Ueda T, Taniguchi Y, Adachi S et al (2025) Gene Pyramiding Strategies for Sink Size and Source Capacity for High-Yield Japonica Rice Breeding. Rice 18:6. 10.1186/s12284-025-00756-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Vasantha S, Kumar RA, Tayade AS et al (2022) Physiology of Sucrose Productivity and Implications of Ripeners in Sugarcane. Sugar Tech 24:715–731. 10.1007/s12355-021-01062-7 [DOI] [Google Scholar]
  68. Wakabayashi Y, Morita R, Yamagishi J, Aoki N (2022) Varietal difference in dynamics of non-structural carbohydrates in nodal segments of stem in two varieties of rice (Oryza sativa L.) at pre- and post-heading stages. Plant Prod Sci 25:30–42. 10.1080/1343943X.2021.1914513 [DOI] [Google Scholar]
  69. Wang DR, Han R, Wolfrum EJ, McCouch SR (2017) The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa. New Phytol 215:658–671. 10.1111/nph.14614 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Wu L, Birch RG (2007) Doubled sugar content in sugarcane plants modified to produce a sucrose isomer. Plant Biotechnol J 5:109–117. 10.1111/j.1467-7652.2006.00224.x [DOI] [PubMed] [Google Scholar]
  71. Wu LL, Liu ZL, Wang JM et al (2011) Morphological, anatomical, and physiological characteristics involved in development of the large culm trait in rice. Aust J Crop Sci 5:1356–1363 [Google Scholar]
  72. Wu L, Zhang W, Ding Y et al (2017) Shading Contributes to the Reduction of Stem Mechanical Strength by Decreasing Cell Wall Synthesis in Japonica Rice (Oryza sativa L). Front Plant Sci 8:881. 10.3389/fpls.2017.00881 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Yamamoto T, Taguchi-Shiobara F, Ukai Y et al (2001) Mapping Quantitative Trait Loci for Days-to-heading, and Culm, Panicle and Internode Lengths in a BC₁F₃ Population Using an Elite Rice Variety, Koshihikari, as the Recurrent Parent. Breed Sci 51:63–71 10.1270/jsbbs.51.63 [DOI] [Google Scholar]
  74. Yang J, Zhang J (2010) Crop management techniques to enhance harvest index in rice. J Exp Bot 61:3177–3189. 10.1093/jxb/erq112 [DOI] [PubMed] [Google Scholar]
  75. Yang J, Zhang J, Wang Z et al (2001) Remobilization of carbon reserves in response to water deficit during grain filling of rice. Field Crops Res 71:47–55. 10.1016/S0378-4290(01)00147-2 [DOI] [Google Scholar]
  76. Yonemaru J, Mizobuchi R, Kato H et al (2014) Genomic regions involved in yield potential detected by genome-wide association analysis in Japanese high-yielding rice cultivars. BMC Genomics 15:346. 10.1186/1471-2164-15-346 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Yoshinaga S, Takai T, Arai-Sanoh Y et al (2013) Varietal differences in sink production and grain-filling ability in recently developed high-yielding rice (Oryza sativa L.) varieties in Japan. Field Crops Res 150:74–82. 10.1016/j.fcr.2013.06.004 [DOI] [Google Scholar]
  78. You C, Zhu H, Xu B et al (2016) Effect of removing superior spikelets on grain filling of inferior spikelets in rice. Front Plant Sci 7:1161. 10.3389/fpls.2016.01161 [DOI] [PMC free article] [PubMed] [Google Scholar]
  79. Zhang WJ, Wu LM, Ding YF et al (2016) Top-dressing nitrogen fertilizer rate contributes to decrease culm physical strength by reducing structural carbohydrate content in japonica rice. J Integr Agric 15:992–1004. 10.1016/S2095-3119(15)61166-2 [DOI] [Google Scholar]
  80. Zhao Q, Hao X, Ali I et al (2020) Characterization and grouping of all primary branches at various positions on a rice panicle based on grain growth dynamics. Agronomy 10:223. 10.3390/agronomy10020223 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (5.9MB, pdf)
Supplementary Material 2. (52.6KB, xlsx)

Data Availability Statement

The datasets supporting the conclusions of this article are included within the article and its additional files.

Articles from Rice are provided here courtesy of Springer

RESOURCES