Comparison of Coffee Species by Sensory Panel and Electronic Nose

Vietoris, Vladimí­r; Zajác, Peter; Čapla, Jozef; Mendelová, Andrea; Križanová, Kamila; Benešová, Lucia

doi:10.15414/jmbfs.20115/16.5.3.234-237

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…Next, chemical analysis data would be required for identification of chemical compositions and cupping attributes correlation that might impact overall civet coffee quality. Flavor should be linked with its taste, several researchers have been made to predict the coffee sensory profile by instrumental measurement results [29], [30] and [31]. Therefore a novel approach of data standardization schemes is proposed to relate the chemical compounds and its sensory properties.…”

Section: A Sensory Characteristicsmentioning

confidence: 99%

Sensory and Microbial Characteristics of Civet Coffee

Muzaifa¹,

Hasni²,

Patria³

et al. 2018

International Journal on Advanced Science, Engineering and Information Technology

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Civet coffee has been known as the most expensive coffee in the world. Its high prices are mainly contributed by its uncommon production method. Civet coffee is produced from the coffee beans which have been digested by Asian palm civet or Luwak (Paradoxorus hermaprodites). Civet coffee production is very limited due to its processing is merely depends on civet biologic system. Unfortunately, reliable information on civet microbial digestive is still limited. The aim of this research is to evaluate cup (sensory) and microbial quality of wild and caged civet coffee. Samples of wild and caged civet coffee obtained from Bener Meriah District, Aceh, Indonesia. Sensory quality parameters consist of fragrance, aroma, flavour, aftertaste, acidity, body, balance, uniformity, clean cups, sweetness and overall. Microbial quality was done by enumeration of lactic acid bacteria. The results showed that wild and caged civet coffee relatively had similar profile sensory and microbial characteristics. The score cupping of wild civet coffee is slightly higher than caged civet coffee. Aroma and flavour characteristics of wild and caged civet coffee were herby, nutty, grassy tobacco-like, fishy and sweet but there were over fruity-papaya and guava-like aroma and flavour of caged civet coffee. The lactic acid bacteria count on wild and caged civet were 5.8 x 10 8 cfu/ml and 3,8 x10 8 cfu/ml. Three different colonies from MRS media were isolated and submitted to gram and catalase test. All isolates showed gram-positive and catalase negative. The result confirmed that most colonies are lactic acid bacteria group. Two isolates (ICF 1 and ICF 3) showed proteolytic activity, and isolated ICF 1 showed the largest zone of clearance of 15 mm. Further investigation is required for identification and selection of performance lactic acid bacteria for artificial civet coffee fermentation.

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Section: A Sensory Characteristicsmentioning

confidence: 99%

Sensory and Microbial Characteristics of Civet Coffee

Muzaifa¹,

Hasni²,

Patria³

et al. 2018

International Journal on Advanced Science, Engineering and Information Technology

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“…Tazi (2018) mengembangkan enose untuk mendeteksi kontaminan minyak babi pada minyak zaitun, filma. Vietoris (2015) menggunakan enose untuk mengklasifikasi beberapa macam kopi berdasarkan aromanya (Vietoris et al, 2015).…”

Section: Pendahuluanunclassified

Klasifikasi Pola Aroma Teh Hijau Menggunakan Hidung Elektronik (E-Nose) Berbasis Linear Diskriminan Analisis (LDA)

Kusairi¹,

Muthmainnah

Tazi

et al. 2022

jpm

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Aroma teh merupakan sesuatu yang sulit diukur karena membutuhkan kejelian dalam indra penciuman sehingga untuk mengukur aroma dalam rangka mempertahankan kualitas teh yaitu menggunakan alat Hidung elektronik/enose yang terdiri dari sensor-sensor yang digunakan untuk mendeteksi aroma atau bau. Hidung elektronik/Enose terbuat dari beberapa larik sensor gas dan memiliki sistem kerja seperti indra penciuman manusia. Melalui e-nose aroma teh hijau dapat diidentifikasi dan diklasifikasi menggunakan metode LDA (linear discriminant analysis). Tujuan penelitian ini untuk mengetahui klasifikasi beberapa merek teh hijau menggunakan hidung elektronik dan analisis hasil data keluaran dari hidung elektronik menggunakan metode linear diskriminan analisis (LDA) berdasarkan aromanya. Hasil pengukuran hidung elektronik (e-nose) yang berupa kurva sensing dan flessing, dicari luasannya dengan menggunakan metode integral trapesium. Data berupa luasan diolah dengan menggunakan metode LDA. Dilakukan pengujian untuk tingkat akurasi dan presisi hidung elektronik (e-nose) dengan uji validitas dan reabilitas hasil pengukuran. Hasil pengukuran berbasis hidung elektronik, menghasilkan empat cluster besar dengan menggunakan pengolahan data metode LDA yaitu kelompok teh hijau merek TT dan TJ, kelompok teh hijau TCB, kelompok teh hijau merek TKD dan teh hijau merek TM. Dari data LDA didapatkan Fungsi diskriminan pertama (FD1) dan Fungsi diskriminan kedua (FD2) yang mempunyai nilai 48,8% dan 37,6% dari total varians. Nilai total dua fungsi diskriminan pertama sebesar 86,4 % sudah mampu untuk mengklasifikasikan secara baik berdasarkan grafik score plot.

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“…In this study, the e‐nose was able to differentiate the coffee aroma. Vietoris et al 21 investigated the relationship between the sensory assessment of the varietal coffee samples and their aromatic profiles measured using an e‐nose of alpha MOS. The temporal dominance sensation method, which allows the temporal sequence of the dominant sensory sensation, was chosen to describe a difference in flavoured coffee varietal profile.…”

Section: Introductionmentioning

confidence: 99%

Combination of metal oxide semiconductor gas sensor array and solid‐phase microextraction gas chromatography–mass spectrometry for odour classification of brewed coffee

Hardoyono,

Windhani

2023

Flavour & Fragrance J

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Odour analysis of coffee using low‐cost and portable instruments in coffee shops, restaurants and bars is essential to keep the loyalty of coffee consumers. This paper aimed to analyse the performance of a gas sensor array for odour classification of brewed coffee. Five grams of ground coffee sample from five different brands was brewed in 80 mL of hot water at a temperature of 90°C. The gas sensor array then measured the sensor's response to the brewed coffee odour. The recorded data were analysed using a principal component analysis (PCA), a hierarchical cluster analysis (HCA) and a support vector machine (SVM). Solid‐phase microextraction gas chromatography–mass spectrometry (SPME‐GC‐MS) was used to identify the five coffee samples' volatile organic compounds (VOCs). The visualisation of the PCA score plot shows that the gas sensor array efficiently classifies the brewed coffee based on different odours. The SVM classification using a polynomial kernel obtained an accuracy of 95.21% using training data sets and an accuracy of 96.94% using testing data sets. Meanwhile, for SVM classification using radial basis function kernel, the SVM obtained an accuracy of 100% for training data sets and 93.06% for testing data sets. The SPME‐GC‐MS analysis showed that the abundance of 2‐furanmethanol; 2‐methoxy‐4‐vinyl phenol; phenol, 4‐ethyl‐2‐methoxy‐ and acetic acid contributed to the separation of the first and the second clusters in the principal components coordinate. Based on data analysis, the gas sensor showed high performance as a low‐cost and portable instrument for odour analysis of coffee based on sensory technique.

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Comparison of Coffee Species by Sensory Panel and Electronic Nose

Abstract: Keywords: Sensory analysis, temporal dominance of sensations, volatile compounds, coffee origin

Cited by 6 publications

References 5 publications

Sensory and Microbial Characteristics of Civet Coffee

Sensory and Microbial Characteristics of Civet Coffee

Klasifikasi Pola Aroma Teh Hijau Menggunakan Hidung Elektronik (E-Nose) Berbasis Linear Diskriminan Analisis (LDA)

Combination of metal oxide semiconductor gas sensor array and solid‐phase microextraction gas chromatography–mass spectrometry for odour classification of brewed coffee

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