4.6 Article

Sugarcane Metabolome Compositional Stability in Pretreatment Processes for NMR Measurements

Journal

METABOLITES
Volume 12, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/metabo12090862

Keywords

metabolomics; nuclear magnetic resonance; sugarcane juice; metabolite composition; support vector machine; machine learning; harvest period

Funding

  1. Japan Society for the Promotion of Science [KAKENHI JP21K05553]
  2. research project on Regulatory research projects for food safety, animal health and plant protection - Ministry of Agriculture, Forestry and Fisheries of Japan [JPJ008617, 18063550]

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This study aimed to evaluate the variability of sugarcane juice metabolome affected by different pretreatment methods and determine optimal conditions for NMR-based metabolomics. The results showed that the pretreatment processes were compatible and the thermal processing provided stability to the metabolome. NMR-based metabolomics allowed for the successful identification of characteristic metabolites in sugarcane juice.
Sugarcane is essential for global sugar production and its compressed juice is a key raw material for industrial products. Sugarcane juice includes various metabolites with abundances and compositional balances influencing product qualities and functionalities. Therefore, understanding the characteristic features of the sugarcane metabolome is important. However, sugarcane compositional variability and stability, even in pretreatment processes for nuclear magnetic resonance (NMR)-based metabolomic studies, remains elusive. The objective of this study is to evaluate sugarcane juice metabolomic variability affected by centrifugation, filtration, and thermal pretreatments, as well as the time-course changes for determining optimal conditions for NMR-based metabolomic approach. The pretreatment processes left the metabolomic compositions unchanged, indicating that these pretreatments are compatible with one another and the studied metabolomes are comparable. The thermal processing provided stability to the metabolome for more than 32 h at room temperature. Based on the determined analytical conditions, we conducted an NMR-based metabolomic study to discriminate the differences in the harvest period and allowed for successfully identifying the characteristic metabolome. Our findings denote that NMR-based sugarcane metabolomics enable us to provide an opportunity to collect a massive amount of data upon collaboration between multiple researchers, resulting in the rapid construction of useful databases for both research purposes and industrial use.

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