Next-Gen Approaches to Flavor-Related Metabolism

Abstract

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.

Metabolomics‐driven gene mining and genetic improvement of tolerance to salt‐induced osmotic stress in maize

“…Metabolite biomarkers can provide sensitive chemical fingerprints for various complex traits (e.g. fruit flavor, stress tolerance), making the metabolite biomarker‐based GWAS to be a cutting‐edge approach for targeted mining of QTLs associated with complex agronomic traits (Weckwerth, 2003; Weckwerth et al ., 2004; Nakabayashi & Saito, 2015; Zhu et al ., 2018; Zhu et al ., 2019; Weckwerth et al ., 2020). Given the fact that SIOS tolerance is a complex trait, and that metabolites can act as biomarkers of complex traits, here we employed a metabolite biomarker‐based approach to investigate the natural variations of SIOS tolerance in maize (Fig.…”

Metabolomics clarify the compounds contributing to the quality of apples among different regions in China

“…In recent years, metabolomic has shown great potential in the field of Fruit nutrition evaluation, quality detection, and metabolic pathway analysis (Shang & Huang, 2019; Zhao et al., 2019; Zhu et al., 2019). Untargeted metabolomics relied on a holistic approach toward the profiling of as many metabolites as possible without a prior knowledge of these metabolites.…”

“…It has extensively studied in postharvest fields (Dobson et al., 2008; Pedreschi et al., 2009; Ritota et al., 2010; Rudell et al., 2008, 2009; Sánchez Pérez et al., 2011; Young et al., 2004). As an effective way, it provides powerful tool to find compounds contributing to flavor in the major vegetables as well as genetic analyses of the relevant metabolic pathways (Benkeblia, 2014; Zhu et al., 2019). The metabolomic studies of volatiles identified potential biomarkers of tomatoes by different varieties, genotype, and growing conditions (Lee et al., 2019; Slimestad & Verheul, 2005; Socaci et al., 2014; Tikunov et al., 2005).…”

Comparing nutrients and volatiles among different tomato varieties

“…Linear regression was performed between the concentration measured by GC/MS and the theoretically calculated concentration. The calibration curve was as follows: y = 1.004x-0.044, R 2 = 0.998 (4) According to the calibration curve (4), the concentration of each volatile was determined.…”

“…With the improvement of living standards, not only should people eat enough, but also eat well. However, the flavor and quality of tomato did not be improved with the increase in yield, but decreased in modern cultivated tomatoes [3,4]. The tomato flavor became less, and the sweetness was lower, causing consumers to complain [5].…”