Co-expression of metabolites and sensory attributes through weighted correlation network analysis to explore flavor-contributing factors in various Pyrus spp. Cultivars

Wenjun Zhang; Bo Bai; Hongxia Du; Qian Hao; Lulu Zhang; Zilei Chen; Jiangsheng Mao; Chao Zhu; Mengmeng Yan; Hongwei Qin; A M Abd El-Aty

doi:10.1016/j.fochx.2024.101189

Co-expression of metabolites and sensory attributes through weighted correlation network analysis to explore flavor-contributing factors in various Pyrus spp. Cultivars

Food Chem X. 2024 Feb 5:21:101189. doi: 10.1016/j.fochx.2024.101189. eCollection 2024 Mar 30.

Authors

Wenjun Zhang¹, Bo Bai², Hongxia Du¹, Qian Hao³, Lulu Zhang⁴, Zilei Chen¹, Jiangsheng Mao¹, Chao Zhu¹, Mengmeng Yan¹, Hongwei Qin¹, A M Abd El-Aty^{5

6}

Affiliations

¹ Shandong Provincial Key Laboratory of Test Technology on Food Quality and Safety, Institute of Quality Standard and Testing Technology for Agro-Products, Shandong Academy of Agricultural Sciences, Jinan, Shandong 250100, China.
² Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences, Jinan, Shandong 250100, China.
³ College of Food Science and Engineering, Shandong Agricultural University, Taian, Shandong 271018, China.
⁴ Department of Food Science and Engineering, College of Biological Sciences and Technology, Beijing Key Laboratory of Forest Food Processing and Safety, Beijing Forestry University, Beijing, 100083, China.
⁵ Department of Pharmacology, Faculty of Veterinary Medicine, Cairo University, Giza 12211, Egypt.
⁶ Department of Medical Pharmacology, Medical Faculty, Ataturk University, Erzurum 25240, Turkey.

Abstract

Flavor profiles of various Pyrus spp. cultivars exhibit significant variations, yet the underlying flavor-contributing factors remain elusive. In this investigation, a comprehensive approach encompassing metabolomics analysis, volatile fingerprint analysis, and descriptive sensory analysis was employed to elucidate the flavor disparities among Nanguoli, Korla fragrant pear, and Qiuyueli cultivars and uncover potential flavor contributor. The study comprehensively characterized the categories and concentrations of nonvolatile and volatile metabolites, and 925 metabolites were identified. Flavonoids and esters dominated the highest cumulative response, respectively. Utilizing weighted correlation network analysis (WGCNA), seven highly correlated modules were identified, yielding 407 pivotal metabolites. Further correlation analysis of the differential substances provided potential flavor constituents strongly associated with various sensory attributes; taste factors had a certain association with olfactory characteristics. Our findings demonstrated the manifestation of flavor was a result of the synergistic effect of various compounds; evaluation olfactory flavor necessitated a comprehensive consideration of taste substances.

Keywords: Metabolomics; Potential flavor factors; Pyrus spp.; Sensory attributes; Weighted correlation network analysis.