Literature DB >> 28917744

Differentiation of cumin seeds using a metal-oxide based gas sensor array in tandem with chemometric tools.

Mahdi Ghasemi-Varnamkhasti1, Zahra Safari Amiri2, Mojtaba Tohidi2, Majid Dowlati3, Seyed Saeid Mohtasebi4, Adenilton C Silva5, David D S Fernandes5, Mário C U Araujo5.   

Abstract

Cumin is a plant of the Apiaceae family (umbelliferae) which has been used since ancient times as a medicinal plant and as a spice. The difference in the percentage of aromatic compounds in cumin obtained from different locations has led to differentiation of some species of cumin from other species. The quality and price of cumin vary according to the specie and may be an incentive for the adulteration of high value samples with low quality cultivars. An electronic nose simulates the human olfactory sense by using an array of sensors to distinguish complex smells. This makes it an alternative for the identification and classification of cumin species. The data, however, may have a complex structure, difficult to interpret. Given this, chemometric tools can be used to manipulate data with two-dimensional structure (sensor responses in time) obtained by using electronic nose sensors. In this study, an electronic nose based on eight metal oxide semiconductor sensors (MOS) and 2D-LDA (two-dimensional linear discriminant analysis), U-PLS-DA (Partial least square discriminant analysis applied to the unfolded data) and PARAFAC-LDA (Parallel factor analysis with linear discriminant analysis) algorithms were used in order to identify and classify different varieties of both cultivated and wild black caraway and cumin. The proposed methodology presented a correct classification rate of 87.1% for PARAFAC-LDA and 100% for 2D-LDA and U-PLS-DA, indicating a promising strategy for the classification different varieties of cumin, caraway and other seeds.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  2D-LDA; Classification; Cumin seeds; Electronic nose; U-PLS-DA

Mesh:

Substances:

Year:  2017        PMID: 28917744     DOI: 10.1016/j.talanta.2017.08.024

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  2 in total

1.  Electronic Nose for Differentiation and Quantification of Yeast Species in White Fresh Soft Cheese.

Authors:  Nawaf Abu-Khalaf; Wafa Masoud
Journal:  Appl Bionics Biomech       Date:  2022-01-17       Impact factor: 1.781

Review 2.  An Outlook of Recent Advances in Chemiresistive Sensor-Based Electronic Nose Systems for Food Quality and Environmental Monitoring.

Authors:  Alishba T John; Krishnan Murugappan; David R Nisbet; Antonio Tricoli
Journal:  Sensors (Basel)       Date:  2021-03-24       Impact factor: 3.576

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.