The CAAS-YNNU Joint Academy of Potato Sciences, Yunnan Normal University, Kunming 650500, China.
Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China.
Annu Rev Plant Biol. 2019 Apr 29;70:187-212. doi: 10.1146/annurev-arplant-050718-100353. Epub 2019 Mar 5.
Although flavor is an essential element for consumer acceptance of food, breeding programs have focused primarily on yield, leading to significant declines in flavor for many vegetables. The deterioration of flavor quality has concerned breeders; however, the complexity of this trait has hindered efforts to improve or even maintain it. Recently, the integration of flavor-associated metabolic profiling with other omics methodologies derived from big data has become a prominent trend in this research field. Here, we provide an overview of known metabolites contributing to flavor in the major vegetables as well as genetic analyses of the relevant metabolic pathways based on different approaches, especially multi-omics. We present examples demonstrating how omics analyses can help us to understand the accomplishments of historical flavor breeding practices and implement further improvements. The integration of genetics, cultivation, and postharvest practices with genome-scale data analyses will create enormous potential for further flavor quality improvements.
虽然风味是消费者接受食物的一个重要因素,但育种计划主要集中在产量上,导致许多蔬菜的风味显著下降。风味质量的恶化引起了育种者的关注;然而,这种特性的复杂性阻碍了改进甚至维持它的努力。最近,将风味相关的代谢物图谱与其他源自大数据的组学方法相结合,已成为该研究领域的一个突出趋势。在这里,我们提供了一个主要蔬菜风味相关代谢物的概述,以及基于不同方法(特别是多组学)的相关代谢途径的遗传分析。我们展示了一些例子,说明组学分析如何帮助我们理解历史风味育种实践的成果,并进一步改进。将遗传学、栽培和采后实践与基因组规模的数据分析相结合,将为进一步提高风味质量创造巨大的潜力。