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

Ghasemi-Varnamkhasti, Mahdi; Amiri, Zahra; Tohidi, Mohammad; Dowlati, Majid; Mohtasebi, Seyed Saeid; Silva, Adenilton C.; Fernandes, David; Araújo, Mário César Ugulino de

doi:10.1016/j.talanta.2017.08.024

Cited by 22 publications

(11 citation statements)

References 28 publications

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“…It is based on detecting volatile organic compounds (VOCs). It has been successfully used in several biological and agricultural applications [11,12], especially in food spoilage [13][14][15][16][17][18]. Furthermore, it was used for the identification of several bacterial strains and fungi strains, since these microorganisms can produce VOCs during their metabolic activities.…”

Section: Introductionmentioning

confidence: 99%

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

Abu-Khalaf

Masoud

2022

Applied Bionics and Biomechanics

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Detection of food spoilage with simple and fast methods is an important issue in food security and safety. The present study is mainly aimed at identifying and quantifying four yeast species in white fresh soft cheese using an electronic nose (EN). The yeast species Pichia anomala, Pichia kluyveri, Hanseniaspora uvarum, and Debaryomyces hansenii were used. Six concentrations of each yeast species (100, 200, 400, 600, 800, and 1000 cells/g cheese) were inoculated in 100 g of fresh soft cheese and incubated for 48 h at 25°C. The EN was used to identify and quantify different yeast species in cheese samples. It was found that EN was able to discriminate between four yeast species using principal component analysis (PCA). Moreover, EN was able to quantify in good precision three (Pichia anomala, Pichia kluyveri, and Debaryomyces hansenii) of the four tested yeasts presented in cheese samples using partial least squares (PLS) models. It seems that EN is a reliable tool that can be used as a fast technique to identify and quantify cheese spoilage in the cheese industry.

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Section: Introductionmentioning

confidence: 99%

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

Abu-Khalaf

Masoud

2022

Applied Bionics and Biomechanics

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“…E-nose is widely used in agricultural to analyze growth, classify seeds, detect the maturity, monitor quality, which promoted agricultural modernization and saved labor [ 2 ]. Eight MOS sensors produced by FIS (Osaka, Japan), MQ (Hanwei, China), and TGS (Figaro Engineering Inc.) were applied for classifying cumin, caraway, and other seeds [ 179 ]. Similarly, e-nose based on MOS TGS and FIS sensors (Fig.…”

Section: Summary and Perspectivementioning

confidence: 99%

Gas Sensors Based on Chemi-Resistive Hybrid Functional Nanomaterials

et al. 2020

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HIGHLIGHTS• This review gives a thinking based on the generic mechanisms rather than simply dividing them as different types of combination of materials, which is unique and valuable for understanding and developing the novel hybrid materials in the future.• The hybrid materials, their sensing mechanism, and their applications are systematically reviewed. Critical thinking and ideas regarding the orientation of the development of hybrid material-based gas sensor in the future are also discussed.ABSTRACT Chemi-resistive sensors based on hybrid functional materials are promising candidates for gas sensing with high responsivity, good selectivity, fast response/recovery, great stability/repeatability, room-working temperature, low cost, and easy-to-fabricate, for versatile applications. This progress report reviews the advantages and advances of these sensing structures compared with the single constituent, according to five main sensing forms: manipulating/constructing heterojunctions, catalytic reaction, charge transfer, charge carrier transport, molecular binding/sieving, and their combinations. Promises and challenges of the advances of each form are presented and discussed.Critical thinking and ideas regarding the orientation of the development of hybrid material-based gas sensor in the future are discussed.

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“…Numerous applications of electronic noses in food products are reported in literature and, selecting only those dealing with spices, we can report that canonical discriminant function analysis on onion (head-space of allinase inactivated samples) analyzed with a MOS (Metal Oxide Semiconductor)-based electronic nose showed a clear separation among four onion groups with an overall correct classification rate of 97.5% (Russo et al, 2013). An electronic nose based on eight MOS sensors used for discriminating cultivated and wild black caraway and cumin seeds revealed a correct classification rate of 87.1% for parallel factor analysis-LDA (linear discriminant analysis) and 100% for two-dimensional-LDA and unfolded-partial least square discriminant analysis (Ghasemi-Varnamkhasti et al, 2018). An overall of 94.44% of the accuracy in the recognition and classification of adulterated cumin samples with coriander was obtained with a five sensor array of an electronic nose (Tahri, Tiebe, El Bari, Hübert, & Bouchikhi, 2016).…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Characterization of dried and freeze-dried sea fennel (Crithmum maritimum L.) samples with headspace gas-chromatography/mass spectrometry and evaluation of an electronic nose discrimination potential

Giungato

Renna

Rana

et al. 2019

Food Research International

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

Cited by 22 publications

References 28 publications

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

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

Gas Sensors Based on Chemi-Resistive Hybrid Functional Nanomaterials

Characterization of dried and freeze-dried sea fennel (Crithmum maritimum L.) samples with headspace gas-chromatography/mass spectrometry and evaluation of an electronic nose discrimination potential

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