Optimization of Main Ingredient Ratio, Metabolomics Analysis, and Antioxidant Activity Analysis of Lycopene-Enriched Compound Fruit Wine

Abstract

To find the optimal main ingredient ratio of compound fruit wine for enriching the varieties of lycopene-enriched fruit products and improving their economic value, fuzzy mathematics sensory evaluation and the D-optimal mixture design were considered. Under the main ingredient ratios of tomato juice, papaya juice, carrot juice, and gac fruit juice of 27.2%, 27.5%, 10.0%, and 35.3%, respectively, a clear and transparent compound fruit wine with a full-bodied fruit and wine aroma and mellow taste can be obtained. Meanwhile, a total of 406 metabolites were identified in the compound fruit wine, which were classified into nine superclasses including lipids and lipid-like molecules (150), organic acids and derivatives (69), and others. The relative levels of 54 metabolites after optimization were decreased significantly (VIP > 1.0, p < 0.05, FC < 0.5), while the relative levels of 106 metabolites including lycopene and (13Z)-lycopene were increased significantly (VIP > 1.0, p < 0.05, FC > 2). Furthermore, the EC50 values of this compound fruit wine after optimization of the main ingredient ratio for scavenging ABTS+·, DPPH·, O2−·, and ·OH were 78.62%, 57.74%, 42.85%, and 59.91%, respectively. Together, a compound fruit wine rich in lycopene with antioxidant activities was manufactured, which has application potential in the development of functional foods.

Effects of Different Primary Processing Methods on the Flavor of Coffea arabica Beans by Metabolomics

“…Variable importance in projection (VIP) analysis ranked the overall contribution of each variable to the OPLS-DA model. Those variables with VIP > 1.0, p < 0.05, and fold change (FC) > 2 or <0.5 were classified as differentially changed non-volatile compounds (DCnVCs) or differentially changed volatile compounds (DCVCs) [13].…”

“…1.0, p < 0.05, and fold change (FC) > 2 or < 0.5 were classified as differentially changed nonvolatile compounds (DCnVCs) or differentially changed volatile compounds (DCVCs) [13].…”

Interaction and Metabolic Function of Microbiota during the Washed Processing of Coffea arabica

“…LC-MS data were preprocessed by Progensis QI software 3.0 (Waters Corporation, Milford, MA, USA) [ 36 ]. At the same time, the metabolites were searched and identified by the HMDB, Metlin, and Majorbio Database [ 37 ]. The response intensity of the sample mass spectrum peaks was normalized by the sum normalization method, and variables with relative standard deviation (RSD) > 30% of QC samples were removed, and log10 logarithmization was performed.…”