Abstract
In apples, consumers predominantly use visual, auditory and texture cues as quality/preference indicators and struggle to describe complex olfactory sensations. This study investigated apple cultivar differentiation using analytical and sensory techniques with the goal of achieving more relevant instrumental characterization. Sensory flavor/odor data were compared with volatile organic compounds (VOCs) measured using proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) and sensory texture data were compared with mechanical-acoustic textural parameters obtained using a texture analyzer. Both techniques separated cultivars similarly. PTR-ToF-MS data separated cultivars into VOC families that correlated to specific sensory attributes (e.g., butanoate esters to lemon flavor/odor). Analytical and sensory firmness were positively correlated where the former differentiated crunchy from hard-not crunchy cultivars. Sweet taste did not correlate to soluble solids content but was positively correlated to fruity esters which could indicate a taste-aroma interaction. This study demonstrates the potential to predict sensory attributes of apples using analytical techniques.
Practical ApplicationThe description of apple flavor is challenging for both trained panelists and consumers to describe due to the complexity of the multimodal stimulations that occur within the oral and ortho/retro nasal cavity during consumption that induce odor, taste, flavor and sound perception. Therefore, this study looks at objectively characterizing apple cultivars based solely on instrumental techniques that reflect attributes attained from a descriptive sensory analysis of the same cultivars. The current study found apple cultivars were separated into similar groups when sensory and instrumental texture, physicochemical and VOC data were compared. Specific analytical properties that correlated strongly to sensory attributes could be used as predictors of important sensory attributes that differentiated the samples. Hence, the use of these instrumental techniques to characterize apples could be an option to increase throughput.