A systematic high-throughput phenotyping assay for sugarcane stalk quality characterization by near-infrared spectroscopy.

Abstract

Abstract Background Sugarcane ( Saccharum officinarum L.) is an economically important crop with stalks as the harvest organs. Improvement in stalk quality is deemed a promising strategy for enhancing sugarcane production. However, the lack of efficient approaches for systematic evaluation of sugarcane germplasm largely limits improvements in stalk quality. This study is designed to develop a systematic near-infrared spectroscopy (NIRS) assay for high-throughput phenotyping of sugarcane stalk quality, thereby providing a feasible solution for precise evaluation of sugarcane germplasm. Results A total of 628 sugarcane accessions harvested at different growth stages before and after maturity were employed to take a high-throughput assay to determine sugarcane stalk quality. Based on high-performance anion chromatography (HPAEC-PAD), large variations in sugarcane stalk quality were detected in terms of biomass composition and the corresponding fundamental ratios. Online and offline NIRS modeling strategies were applied for multiple purpose calibration with partial least square (PLS) regression analysis. Consequently, 25 equations were generated with excellent determination coefficients ( R 2 ) and ratio performance deviation (RPD) values. Notably, for some observations, RPD values as high as 6.3 were observed, which indicated their exceptional performance and predictive capability. Conclusions This study provides a feasible method for consistent and high-throughput assessment of stalk quality in terms of moisture, soluble sugar, insoluble residue and the corresponding fundamental ratios. The proposed method permits large-scale screening of optimal sugarcane germplasm for sugarcane stalk quality breeding and beyond.

Plant phenotyping relevance

サトウキビ茎の品質形質をNIRSで高スループット推定する測定法を開発・校正し、HPAEC-PADを基準に性能検証しており、表現型取得法が研究の中心である。

Code and data availability

The article describes NIRS phenotyping of 628 sugarcane accessions with PLS calibration models, but no public phenotype/spectral dataset, author code, or model deposit is mentioned. The only supplementary file (Additional file 1) contains HPAEC waveform details and calibration statistics tables, not raw data, and no de

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