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

Plant Methods

Qian Hu¹  Yinjuan Shen¹  Xinru Li¹  Muhammad Adnan¹  Jiangfeng Huang¹  Fuhong Jiang¹  Baoshan Chen¹  Pan Lu¹  Muqing Zhang¹  Maoyao Wang¹  Le Mao¹  Zuhu Deng²  Muhammad Tahir Khan³ 

[1] Guangxi Key Laboratory of Sugarcane Biology, Sugar Industry Collaborative Innovation Center, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, 530004, Nanning, Guangxi, China;Guangxi Key Laboratory of Sugarcane Biology, Sugar Industry Collaborative Innovation Center, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, College of Agriculture, Guangxi University, 530004, Nanning, Guangxi, China;National Engineering Technology Research Center of Sugarcane, Fujian Agriculture and Forestry University, 350002, Fuzhou, Fujian, China;Sugarcane Biotechnology Group, Nuclear Institute of Agriculture (NIA), Tandojam, Pakistan;

关键词: Sugarcane;    Culm sugar content;    Biomass;    NIRS;    HPAEC;   

DOI  :  10.1186/s13007-021-00777-8

来源: Springer

【 摘 要 】

BackgroundSugarcane (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.ResultsA 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 (R2) 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.ConclusionsThis 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.

【 授权许可】

CC BY