Metabolomics and machine learning integrated analysis of flavor quality in 'Legacy' and a mutant blueberry

代谢组学和机器学习相结合的分析方法用于研究“Legacy”蓝莓和一种突变蓝莓的风味品质。

阅读:1

Abstract

Blueberry flavor quality, as a core determinant of its commercial value and consumer acceptance, has become an important goal of blueberry breeding. This study compared flavor quality characteristics of the 'Legacy' and a natural mutant blueberry. The results revealed that mutant fruits showed a reduction in fruit weight and anthocyanin content. Further primary metabolism analysis revealed that the content of amino acids in mutant fruit was increased compared to the 'Legacy' fruit, while the content of organic acids was reduced. Based on the HS-SPME-GC-MS analysis, the content of volatile organic compounds (VOCs) in the mutant blueberry was doubled compared to the 'Legacy' fruit, with terpenoids increasing by 8 times, and alcohols, esters, and aldehydes increasing by 1.5-2.2 times. Further analysis revealed that 189 VOCs were significantly upregulated in mutant fruit (including 40 alcohols, 30 esters, and 23 terpenoids). Metabolomics analysis indicated that the accumulation of amino acids and specific VOCs, as well as the reduction of citric acid in mutant fruit, enhanced sweetness and aroma profiles through a synergistic effect. Random forest algorithm identified characteristic metabolites such as alanine and 3-cyclohexene-1-carbaldehyde, indicating their potential as candidate targets for blueberry flavor breeding. Our results provided new insights into the mechanisms of flavor formation and molecular design breeding of high-flavor quality blueberries.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。