Structural volume composition of internodes determines culm non-structural carbohydrates accumulation in rice

Abstract

Non-structural carbohydrates (NSC) stored in the stem play a crucial role in supporting yield formation in rice. However, internode morphological determinants of NSC accumulation are 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. Manipulation of internode development using plant growth regulators demonstrated that altering VCR effectively modified 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 NSC accumulation to achieve high and stable yield performance in rice. Highlight This novel internode structural index robustly predicts the culm non-structural carbohydrate accumulation capacity, providing a practical morphological indicator for improving yield stability in rice.

Plant phenotyping relevance

稲の節間形態から茎のNSC蓄積能力を評価する新規指標VCRを導入し、複数年・品種で再現性と予測性能を検証しているため、形態表現型の測定・評価法が研究の中心である。

Code and data availability

The supplied blocks describe field/pot phenotyping experiments, ImageJ-based cross-sectional trait analysis, and R statistical analysis, but contain no data availability statement, deposited dataset, public repository, or author code URL. No paper-specific public asset is identified.

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