Application of Electronic Nose in Tea Quality Recognition

2011 ◽  
Vol 422 ◽  
pp. 43-46
Author(s):  
Hong Mei Zhang ◽  
Fen Ling Chang ◽  
Yong Chang Yu ◽  
Yu Jing He ◽  
He Li ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Quality Control ◽  
Electronic Nose ◽  
Rapid Detection ◽  
Principal Component ◽  
Component Analysis ◽  
Statistical Quality Control ◽  
Statistical Quality ◽  
Tea Quality ◽  
Electronic Nose Technology

The current study uses the electronic nose FOX 4000 to inspect Xinyang Maojian tea in three quality levels. Principal component analysis (PCA) and statistical quality control (SQC) are adopted to analyze and recognize the data. PCA shows that there is a certain difference in the odor of the tea samples in the three quality levels. PCA can evidently distinguish three kinds of samples. SQC analysis shows that X800 and X600 are located outside the controllable range, indicating that they differ from X1200 in odor. This result is consistent with the PCA result. The study shows that electronic nose technology is expected to be applied widely in the rapid detection of tea.

scholarly journals Deteksi Formalin Pada Buah Tomat (Lycopersicum esculentum Mill) Dengan Teknologi Hidung Elektronik (Electronic Nose)

2019 ◽  
Vol 4 (2) ◽  
pp. 359-366
Author(s):  
Irfan Maibriadi ◽  
Ratna Ratna ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Lycopersicum Esculentum ◽  
Olfactory Ability ◽  
Pca Method ◽  
The Difference ◽  
Electronic Nose Technology

Abstrak,  Tujuan dari penelitian ini adalah mendeteksi kandungan dan kadar formalin pada buah tomat dengan menggunakan instrument berbasis teknologi Electronic nose. Penelitian ini menggunakan buah tomat yang telah direndam dengan formalin dengan kadar 0.5%, 1%, 2%, 3%, 4%, dan buah tomat tanpa perendaman dengan formalin (0%). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 18 sampel. Pengukuran spektrum beras menggunakan sensor Piezoelectric Tranducer. Klasifikasi data spektrum buah tomat menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma formalin pada buah tomat pada detik ke-8.14, dan dapat mengklasifikasikan kandungan dan kadar formalin pada buah tomat pada detik ke 25.77. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksikandungan dan kadar formalin pada buah tomat dengan tingkat keberhasilan sebesar 99% (PC-1 sebesar 93% dan PC-2 sebesar 6%). Perbedaan kadar formalin menjadi faktor utama yang menyebabkan Elektronik nose mampu membedakan sampel buah tomat yang diuji, karena semakin tinggi kadar formalin pada buah tomat maka aroma khas dari buah tomat pun semakin menghilang, sehingga Electronic nose yang berbasis kemampuan penciuman dapat membedakannya.Detect Formaldehyde on Tomato (Lycopersicum esculentum Mill) With Electronic Nose TechnologyAbstract, The purpose of this study is to detect the contents and levels of formalin in tomatoes by using instruments based on Electronic nose technology. This study used tomatoes that have been soaked in formalin with a concentration of 0.5%, 1%, 2%, 3%, 4%, 5% and tomatoes without soaking with formalin (0%). The samples in this study were 18 samples. The measurements of the intensity on tomatoes aroma were using Piezoelectric Transducer sensors. The classification of tomato spectrum data was using the Principal Component Analysis (PCA) method with Gap Reduction pretreatment. The results of this study were obtained: the Electronic nose began to respond the smell of formalin on tomatoes at 8.14 seconds, and it could classify the content and formalin levels in tomatoes at 25.77 seconds. Electronic nose combined with the principal component analysis (PCA) method have successfully detected the content and levels of formalin in tomatoes with a success rate at 99% (PC-1 of 93% and PC-2 of 6%). The difference of grade formalin levels is the main factor that causes Electronic nose to be able to distinguish the tomato samples tested, because the higher of formalin content in tomatoes, the distinctive of tomatoes aroma is increasingly disappearing. Thereby, the Electronic nose based on  the olfactory ability can distinguish them. 

scholarly journals Deteksi Bubuk Kopi Luwak Murni dan Bubuk Kopi Luwak Campuran Dengan Teknologi Hidung Elektronik

2019 ◽  
Vol 4 (3) ◽  
pp. 105-114
Author(s):  
Mubarak Hulda ◽  
Fachruddin Fachruddin ◽  
Agus Arip Munawar
Keyword(s):  
Principal Component Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Powder Spectrum ◽  
Pca Method ◽  
Coffee Powder ◽  
Electronic Nose Technology ◽  
Spectrum Data

Abstrak. Kopi luwak merupakan kopi yang berasal dari hasil konsumsi hewan luwak (musang) yang  telah mengalami fermentasi di dalam pencernaan luwak selam 12 jam. Kopi luwak merupakan komoditi yang sangat diminati dan bernilai jual tinggi. Tujuan dari penelitian ini untuk membedakan bubuk kopi luwak murni dan bubuk kopi luwak campuran dengan memanfaatkan instrumen berbasis teknologi hidung elektronik (electronic nose). Penelitian ini menggunakan bubuk kopi luwak murni dan bubuk kopi arabika yang dicampurkan dengan perbandingan (50:50, 60:40. 70:30, 80:20 dan 90:10). Jumlah sampel yang digunakan pada penelitian ini adalah sebanyak 10 sampel. Pengukuran intensitas sinyal aroma bubuk kopi menggunakan sensor piezoelectric tranducers. Klasifikasi data spektrum bubuk kopi menggunakan metode Principal Component Analysis (PCA) dengan pretreatment nya adalah Gap Reduction. Hasil penelitian ini diperoleh yaitu: Hidung elektronik mulai merespon aroma bubuk kopi pada detik ke-5.64, dan dapat mengklasifikasikan bubuk kopi pada detik ke 11.09. Hidung elektronik yang dikombinasikan dengan metode principal component analysis (PCA) telah berhasil mendeteksi bubuk kopi luwak murni dan bubuk kopi luwak campuran dengan tingkat keberhasilan sebesar 100% (PC-1 sebesar 100% dan PC-2 sebesar 0%).Deteksi Murni Powder Kopi Luwak dan Campuran Kopi Luwak Bubuk Menggunakan Teknologi Hidung ElektronikAbstract. Civet coffee is coffee that comes from the consumption of civet animals (ferrets) that have undergone fermentation in the digestion of mongoose for 12 hours. Civet coffee is a commodity that is very popular and has a high selling value. The purpose of this study is to distinguish pure civet coffee powder and mixed civet coffee powder by using an instrument based on electronic nose technology. This study used pure civet coffee powder and arabica coffee powder mixed with comparisons (50:50, 60:40. 70:30, 80:20 and 90:10). The number of samples used in this study were 10 samples. The measurement of the intensity of coffee powder’s smell signals using piezoelectric tranducers. The classification of coffee powder spectrum data using the Principal Component Analysis (PCA) method with its pretreatment is Gap Reduction. The results of this study were obtained: The electronic nose starts responding to the smell of coffee powder at 5.85 seconds, and can classify coffee powder in 11.09 seconds. The electronic nose combined with the principal component analysis (PCA) method has succeeded in detecting pure civet coffee powder and mixed Civet coffee powder with a success rate of 100 % (PC-1 of 100% and PC-2 of 0%).     

scholarly journals Development of a Piezoelectric-Based Odor Reproduction System

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 870
Author(s):  
Tengteng Wen ◽  
Dehan Luo ◽  
Yongjie Ji ◽  
Pingzhong Zhong
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Electronic Nose ◽  
Principal Component ◽  
Component Analysis ◽  
Piezoelectric Transducers ◽  
Linear Discriminant ◽  
Reproduction System ◽  
Machine Olfaction

Odor reproduction, a branch of machine olfaction, is a technology through which a machine represents various odors by blending several odor sources in different proportions and releases them. In this paper, an odor reproduction system is proposed. The system includes an atomization-based odor dispenser using 16 micro-porous piezoelectric transducers. The authors propose the use of an electronic nose combined with a Principal Component Analysis–Linear Discriminant Analysis (PCA–LDA) model to evaluate the effectiveness of the system. The results indicate that the model can be used to evaluate the system.

scholarly journals Discrimination of Chinese Liquors Based on Electronic Nose and Fuzzy Discriminant Principal Component Analysis

Foods ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 38 ◽  
Author(s):  
Xiaohong Wu ◽  
Jin Zhu ◽  
Bin Wu ◽  
Chao Zhao ◽  
Jun Sun ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Electronic Nose ◽  
Nearest Neighbor ◽  
Principal Component ◽  
Component Analysis ◽  
K Nearest Neighbor ◽  
Knn Classifier ◽  
Extraction Algorithm ◽  
Leave One Out

The detection of liquor quality is an important process in the liquor industry, and the quality of Chinese liquors is partly determined by the aromas of the liquors. The electronic nose (e-nose) refers to an artificial olfactory technology. The e-nose system can quickly detect different types of Chinese liquors according to their aromas. In this study, an e-nose system was designed to identify six types of Chinese liquors, and a novel feature extraction algorithm, called fuzzy discriminant principal component analysis (FDPCA), was developed for feature extraction from e-nose signals by combining discriminant principal component analysis (DPCA) and fuzzy set theory. In addition, principal component analysis (PCA), DPCA, K-nearest neighbor (KNN) classifier, leave-one-out (LOO) strategy and k-fold cross-validation (k = 5, 10, 20, 25) were employed in the e-nose system. The maximum classification accuracy of feature extraction for Chinese liquors was 98.378% using FDPCA, showing this algorithm to be extremely effective. The experimental results indicate that an e-nose system coupled with FDPCA is a feasible method for classifying Chinese liquors.

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