Literature DB >> 26416698

Application of Sensory Evaluation, HS-SPME GC-MS, E-Nose, and E-Tongue for Quality Detection in Citrus Fruits.

Shanshan Qiu1, Jun Wang1.   

Abstract

UNLABELLED: In this study, electronic tongue (E-tongue), headspace solid-phase microextraction gas chromatography-mass spectrometer (GC-MS), electronic nose (E-nose), and quantitative describe analysis (QDA) were applied to describe the 2 types of citrus fruits (Satsuma mandarins [Citrus unshiu Marc.] and sweet oranges [Citrus sinensis {L.} Osbeck]) and their mixing juices systematically and comprehensively. As some aroma components or some flavor molecules interacted with the whole juice matrix, the changes of most components in the fruit juice were not in proportion to the mixing ratio of the 2 citrus fruits. The potential correlations among the signals of E-tongue and E-nose, volatile components, and sensory attributes were analyzed by using analysis of variance partial least squares regression. The result showed that the variables from the sensor signals (E-tongue system and E-nose system) had significant and positive (or negative) correlations to the most variables of volatile components (GC-MS) and sensory attributes (QDA). The simultaneous utilization of E-tongue and E-nose obtained a perfect classification result with 100% accuracy rate based on linear discriminant analysis and also attained a satisfying prediction with high coefficient association for the sensory attributes (R(2) > 0.994 for training sets and R(2) > 0.983 for testing sets) and for the volatile components (R(2) > 0.992 for training sets and R(2) > 0.990 for testing sets) based on random forest. Being easy-to-use, cost-effective, robust, and capable of providing a fast analysis procedure, E-nose and E-tongue could be used as an alternative detection system to traditional analysis methods, such as GC-MS and sensory evaluation by human panel in the fruit industry. PRACTICAL APPLICATION: Being easy-to-use, cost-effective, robust, and capable of providing a fast analysis procedure, E-nose and E-tongue could be used as an alternative detection system to traditional analysis methods for characterizing food flavors. Based on those results, one can draw a conclusion that the fusion system composed of E-tongue and E-nose could guarantee a satisfying result in the prediction of sensory attributes and volatile components for fruit quality profile.
© 2015 Institute of Food Technologists®

Entities:  

Keywords:  citrus juice; electronic nose; electronic tongue; quantitative describe analysis; random forest

Mesh:

Substances:

Year:  2015        PMID: 26416698     DOI: 10.1111/1750-3841.13012

Source DB:  PubMed          Journal:  J Food Sci        ISSN: 0022-1147            Impact factor:   3.167


  7 in total

1.  Characterization and Discrimination of Apples by Flash GC E-Nose: Geographical Regions and Botanical Origins Studies in China.

Authors:  Xinye Wu; Marie-Laure Fauconnier; Jinfeng Bi
Journal:  Foods       Date:  2022-05-31

Review 2.  Metabolomics for Evaluating Flavor-Associated Metabolites in Plant-Based Products.

Authors:  Shruti Pavagadhi; Sanjay Swarup
Journal:  Metabolites       Date:  2020-05-15

3.  Sensory Quality Evaluation of Korla Pear from Different Orchards and Analysis of Their Primary and Volatile Metabolites.

Authors:  Yuan Liu; Simin Xiang; Haipeng Zhang; Hongyan Zhang; Cuiyun Wu; Zhanghu Tang; Jiangbo Wang; Juan Xu
Journal:  Molecules       Date:  2020-11-27       Impact factor: 4.411

4.  Characterization and Analysis of Okoume and Aiele Essential Oils from Gabon by GC-MS, Electronic Nose, and Their Antibacterial Activity Assessment.

Authors:  Youssra Aghoutane; Mohammed Moufid; Soukaina Motia; Guy Stephane Padzys; Linda Priscilia Omouendze; Eduard Llobet; Benachir Bouchikhi; Nezha El Bari
Journal:  Sensors (Basel)       Date:  2020-11-26       Impact factor: 3.576

5.  Tracing internal quality and aroma of a red-fleshed kiwifruit during ripening by means of GC-MS and E-nose.

Authors:  Dongdong Du; Min Xu; Jun Wang; Shuang Gu; Luyi Zhu; Xuezhen Hong
Journal:  RSC Adv       Date:  2019-07-08       Impact factor: 4.036

Review 6.  Machine Learning in Human Olfactory Research.

Authors:  Jörn Lötsch; Dario Kringel; Thomas Hummel
Journal:  Chem Senses       Date:  2019-01-01       Impact factor: 3.160

7.  The Ancient Neapolitan Sweet Lime and the Calabrian Lemoncetta Locrese Belong to the Same Citrus Species.

Authors:  Domenico Cautela; Maria Luisa Balestrieri; Sara Savini; Anna Sannino; Giovanna Ferrari; Luigi Servillo; Luigi De Masi; Annalisa Pastore; Domenico Castaldo
Journal:  Molecules       Date:  2019-12-27       Impact factor: 4.411

  7 in total

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