Sensory omics combined with mathematical modeling for integrated analysis of retronasal Muscat flavor in table grapes

Xiaomiao Zhou; Bingqi Shan; Songyu Liu; Wenping Gao; Xiaoyue Wang; Huiling Wang; Haiying Xu; Lei Sun; Baoqing Zhu

doi:10.1016/j.fochx.2024.101198

Sensory omics combined with mathematical modeling for integrated analysis of retronasal Muscat flavor in table grapes

Food Chem X. 2024 Feb 5:21:101198. doi: 10.1016/j.fochx.2024.101198. eCollection 2024 Mar 30.

Authors

Xiaomiao Zhou^{1

2

3

4}, Bingqi Shan^{3

5}, Songyu Liu³, Wenping Gao³, Xiaoyue Wang^{4

6}, Huiling Wang^{4

6}, Haiying Xu^{1

7}, Lei Sun^{1

7}, Baoqing Zhu^{2

3}

Affiliations

¹ Institute of Forestry and Pomology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100093, China.
² State Key Laboratory of Tree Genetics and Breeding, Bejing Forestry University, Beijing 100083, China.
³ Beiing Key Laboratory of Forestry Food Processing and Safety, Department of Food Science, Beijing Forestry University, Beijing 100083, China.
⁴ Beijing Engineering Research Center for Deciduous Fruit Trees, Beijing 100093, China.
⁵ Heilongjiang Feihe Dairy Co., Ltd., Beijing 100015, China.
⁶ Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture and Rural Affairs, China.
⁷ Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Ministry of Agriculture and Rural Affairs, Beijing 100093, China.

Abstract

This study focused on analyzing the aroma formation mechanism of retronasal muscat flavor in table grapes. The sensory characteristics and fragrance components of table grape juice with different intensities of Muscat were investigated using GC-Quadrupole-MS, quantitative descriptive analysis and three-alternate forced choice. Free monoterpenoids were the main contributors to the retronasal Muscat flavor. The contribution of Muscat compounds to this flavor was quantified by Stevens coefficient, the most and the least sensitive compounds to concentration changes were citronellol and linalool, respectively. To predict the Muscat flavor intensity by mathematical modeling, established a model between Muscat flavor intensity and monoterpenoids concentration, and an optimal partial least squares regression model with a linear relationship between natural logarithms was obtained. These findings provide reference for understanding the formation mechanism of specific aromas in fruits and provide a basis for the development and quality control of processed products such as Muscat flavor grape juice.

Keywords: Flavor sensoryomics; Mathematical model; Monoterpenoid; Sensory characteristics; Table grapes.