A Systematic and Consistent Assay for High-throughput Characterization of Stalk Quality in Sugarcane by Near-infrared Spectroscopy

Abstract

Abstract Stalk quality improvement is deemed a promising strategy to enhance sugarcane production. However, the lack of efficient approaches for a systematic evaluation of sugarcane germplasm limited stalk quality improvement. In this study, 628 sugarcane samples were employed to take a high-throughput assay for determining the sugarcane stalk quality. Based on the high-performance anion chromatography method, large sugarcane stalk quality variations were detected in biomass composition and the corresponding fundamental ratio values. Online and offline Near-infrared Spectroscopy (NIRS) modeling strategies were applied for multiple purpose calibration. Consequently, 25 equations were generated with the excellent determination coefficient ( R 2 ) and ratio performance deviation (RPD) values. Notably, for some observations, RPD values as high as 6.3 were observed that indicated their exceptional performance potential and prediction capacity. Hence, this study provides a feasible way for high-throughput assessment of stalk quality, permitting large-scale screening of optimal sugarcane germplasm.

Code and data availability

The paper describes NIRS/HPAEC phenotyping of 628 sugarcane samples and 25 calibration equations, but no public phenotype dataset, spectral data, code, or trained model deposit is mentioned. The only URL besides the DOI is the authors' lab website, which is not a paper-specific asset deposit. Supplementary annexes only

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