Related Experiment Video
Updated: Jun 9, 2025

Fruit Volatile Analysis Using an Electronic Nose
Published on: March 30, 2012
Assessment of Changes in Sensory Characteristics of Strawberries during 5-Day Storage through Correlation between
Md Shakir Moazzem1, Michelle Hayden1, Dong-Joo Kim2
1Department of Poultry Science, Auburn University, Auburn, AL 36849, USA.
Abstract:
In the last decade, significant efforts have been made to predict sensory characteristics using electronic senses, such as the electronic nose (e-nose) and the electronic tongue (e-tongue), and discuss their relationship to the eating quality evaluated by human panels. This study was conducted (1) to characterize the aroma and taste profiles of strawberries over a 5-day storage period (4 °C) using both electronic senses and human panels and (2) to correlate the electronic sense data with human panel data. A total of 10 sensory attributes of strawberries, including 7 aroma and 3 taste attributes, were analyzed by a descriptive sensory panel (n = 16) over the five days. Although the human panel did not find significant differences in the intensities of the strawberry attributes over the five days, the intensity ratings showed an increasing or decreasing trend over the storage period. However, the e-nose and the e-tongue discriminated each of the storage days of the strawberry samples. Furthermore, the partial least square regression coefficients of determination (R2) indicated that the e-nose and the e-tongue were highly predictive in their evaluation of the intensities of all the descriptive sensory attributes. Lastly, the concentrations of furaneol, one of the key volatiles imparting a distinct ripe strawberry aroma, were determined using an e-nose to correlate with the intensities of aroma attributes evaluated by the panel. A significant positive Pearson's correlation coefficient was found with the intensities of overripe aroma. The findings indicate the potential of electronic senses to determine sensory characteristics and their excellent capability to predict the eating quality of strawberries.
More Related Videos
07:12Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation
Published on: August 26, 2016
10:25Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
Published on: June 28, 2016