Optimization of HS-SPME/GC-MS Method for Determining Volatile Organic Compounds and Sensory Profile in Cocoa Honey from Different Cocoa Varieties (<i>Theobroma cacao</i> L.)

Abstract

This study aimed to develop an analytical method using HS-SPME/GC-MS to determine the volatile organic compound (VOC) profiles and evaluate the sensory attributes of cocoa honey from four cocoa varieties (CCN51, PS1319, SJ02, and Parazinho). Using a multivariate factorial experimental design, the HS-SPME/GC-MS method was optimized to determine the VOC profiles. Twenty previously trained tasters participated in the ranking descriptive analysis, while 108 consumers participated in the acceptance and purchase intention tests. A total of 84 volatile organic compounds were identified from various chemical classes, including acids, alcohols, aldehydes, esters, ketones, monoterpenes, oxygenated monoterpenoids, sesquiterpenes, and oxygenated sesquiterpenoids. Palmitic acid was the compound found in the highest concentration in all varieties (5.13–13.10%). Multivariate analysis tools identified key compounds for differentiation and grouping of the samples. The results revealed that the variety significantly influenced both the VOCs’ concentrations and sensory profiles. The CCN51, PS1319, and SJ02 varieties exhibited the highest diversity of VOCs and sensory attributes. Notably, the SJ02 and CCN51 varieties demonstrated superior acceptability and purchase intention, with means ranging from 7.21 and 7.08 to 3.71 and 3.56, respectively. These results indicate their potential as promising sources of cocoa honey for the food industry.

Keywords

• cocoa honey
• multivariate optimization
• volatile organic compounds
• sensory profile
• descriptive analysis
• consumer acceptance