Discrimination between washedArabica, naturalArabicaandRobustacoffees by using near infrared spectroscopy, electronic nose and electronic tongue analysis

2014 ◽  
Vol 95 (11) ◽  
pp. 2192-2200 ◽  
Author(s):  
Susanna Buratti ◽  
Nicoletta Sinelli ◽  
Elisa Bertone ◽  
Alberto Venturello ◽  
Ernestina Casiraghi ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared ◽  
Electronic Tongue

ANALYSIS OF PEACHES RIPENESS BY AN ELECTRONIC NOSE AND NEAR-INFRARED SPECTROSCOPY

2002 ◽  
Author(s):  
S. CAPONE ◽  
C. DISTANTE ◽  
M. EPIFANI ◽  
R. RELLA ◽  
P. SICILIANO ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared

Rapid measurement of total polyphenols content in cocoa beans by data fusion of NIR spectroscopy and electronic tongue

2014 ◽  
Vol 6 (14) ◽  
pp. 5008-5015 ◽  
Author(s):  
Xingyi Huang ◽  
Ernest Teye ◽  
Livingstone K. Sam-Amoah ◽  
Fangkai Han ◽  
Liya Yao ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Data Fusion ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Electronic Tongue ◽  
Nir Spectroscopy ◽  
Cocoa Beans ◽  
Total Polyphenols ◽  
Rapid Measurement ◽  
Novel Approach

This work measures the total polyphenols content in cocoa beans by using a novel approach of integrating near infrared spectroscopy and electronic tongue, 110 samples of cocoa beans were analysed.

Application of a voltammetric electronic tongue and near infrared spectroscopy for a rapid umami taste assessment

2014 ◽  
Vol 157 ◽  
pp. 421-428 ◽  
Author(s):  
Lucia Bagnasco ◽  
M. Elisabetta Cosulich ◽  
Giovanna Speranza ◽  
Luca Medini ◽  
Paolo Oliveri ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Electronic Tongue ◽  
Umami Taste ◽  
Taste Assessment ◽  
Voltammetric Electronic Tongue

scholarly journals Authentication of Tokaj Wine (Hungaricum) with the Electronic Tongue and Near Infrared Spectroscopy

2019 ◽  
Vol 84 (12) ◽  
pp. 3437-3444 ◽  
Author(s):  
John‐Lewis Z. Zaukuu ◽  
János Soós ◽  
Zsanett Bodor ◽  
József Felföldi ◽  
Ildikó Magyar ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Electronic Tongue

Detection of Aspergillus spp. contamination levels in peanuts by near infrared spectroscopy and electronic nose

Food Control ◽  
2018 ◽  
Vol 93 ◽  
pp. 1-8 ◽  
Author(s):  
Fei Shen ◽  
Qifang Wu ◽  
Peng Liu ◽  
Xuesong Jiang ◽  
Yong Fang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared ◽  
Contamination Levels

Fusion of a Low-cost Electronic Nose and Near Infrared Spectroscopy for Qualitative and Quantitative Detection of Beef Adulterated with Duck

2022 ◽  
Author(s):  
FangKai Han ◽  
Xingyi Huang ◽  
Joshua Harington Aheto ◽  
Xiaorui Zhang ◽  
Marwan M.A. Rashed
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared ◽  
Low Cost ◽  
Nir Spectroscopy ◽  
Quantitative Detection ◽  
Qualitative And Quantitative ◽  
Convenient Technique ◽  
Colorimetric Sensors

A low-cost electronic nose (E-nose) based on colorimetric sensors fused with near-infrared (NIR) spectroscopy was proposed as a rapid and convenient technique for detecting beef adulterated with duck. The total...

scholarly journals Correction: Han et al. Detection of Spray-Dried Porcine Plasma (SDPP) Based on Electronic Nose and Near-Infrared Spectroscopy Data. Appl. Sci. 2020, 10, 2967

2020 ◽  
Vol 10 (18) ◽  
pp. 6433
Author(s):  
Xiaoteng Han ◽  
Enli Lü ◽  
Huazhong Lu ◽  
Fanguo Zeng ◽  
Guangjun Qiu ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared ◽  
Spectroscopy Data ◽  
Spray Dried

We, the authors, wish to make the following corrections to our paper [...]

scholarly journals Smart Detection of Faults in Beers Using Near-Infrared Spectroscopy, a Low-Cost Electronic Nose and Artificial Intelligence

Fermentation ◽  
2021 ◽  
Vol 7 (3) ◽  
pp. 117
Author(s):  
Claudia Gonzalez Viejo ◽  
Sigfredo Fuentes ◽  
Carmen Hernandez-Brenes
Keyword(s):  
Machine Learning ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Near Infrared ◽  
Low Cost ◽  
Regularization Algorithm ◽  
Quality Product ◽  
Brewing Process ◽  
Artificial Neural Network Ann

Early detection of beer faults is an important assessment in the brewing process to secure a high-quality product and consumer acceptability. This study proposed an integrated AI system for smart detection of beer faults based on the comparison of near-infrared spectroscopy (NIR) and a newly developed electronic nose (e-nose) using machine learning modelling. For these purposes, a commercial larger beer was used as a base prototype, which was spiked with 18 common beer faults plus the control aroma. The 19 aroma profiles were used as targets for classification machine learning (ML) modelling. Four different ML models were developed; Models 1 (M1) and M2 based on NIR (100 inputs from 1596–2396 nm) and M3 and M4 based on the e-nose (nine sensor readings as inputs) and 19 aroma profiles as targets for all models. A customized code tested 17 artificial neural network (ANN) algorithms automatically testing performance and neuron trimming. Results showed that the Bayesian regularization algorithm was the most adequate for classification rendering precisions of M1 = 98.9%, M2 = 98.3%, M3 = 96.8%, and M4 = 96.2% without statistical signs of under- or overfitting. The proposed system can be added to robotic pourers and the brewing process at low cost, which can benefit craft and larger brewing companies.

Electronic nose and visible-near infrared spectroscopy in fruit and vegetable monitoring

2017 ◽  
Vol 36 (4) ◽  
Author(s):  
Roberto Beghi ◽  
Susanna Buratti ◽  
Valentina Giovenzana ◽  
Simona Benedetti ◽  
Riccardo Guidetti
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Electronic Nose ◽  
Fruits And Vegetables ◽  
Process Management ◽  
Near Infrared ◽  
Human Life ◽  
Life Styles ◽  
Non Destructive ◽  
Non Destructive Techniques

AbstractIn recent decades, there has been a substantial increase in the consumption of fruits and vegetables due to their nutritional properties since they are known as sources of vitamins, minerals, fiber, and antioxidants. Moreover, a substantial growth in fresh-cut fruits and vegetables has been noticed because of their ease to use; in fact changes in human life styles have led consumers to move towards ready-to-eat products. In this context, product quality must be preserved at each step of product handling, processing, and storage, and therefore rapid methods should be available to provide useful information in process management. In this review an overview of the applications of widely used non-destructive techniques, namely, electronic nose and visible/near infrared spectroscopy, for measuring quality of fruits and vegetables is presented. A brief description of spectroscopic and electronic devices and a selection of applications are provided. Future perspectives about the simplification/application of these non-destructive techniques are finally explored.

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