Electrical Impedance Spectroscopy for On-Line Estimation of Viable Biomass

2001 ◽  
Author(s):  
Jordi Elvira ◽  
Josep Bujan ◽  
Pilar Urpí ◽  
Ramon Bragós ◽  
Francesc Vayreda ◽  
...  
2015 ◽  
Vol 91 (6) ◽  
pp. 1755-1762 ◽  
Author(s):  
Enric Sarró ◽  
Martí Lecina ◽  
Andreu Fontova ◽  
Francesc Gòdia ◽  
Ramon Bragós ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Xin Zhao ◽  
Hong Zhuang ◽  
Seung-Chul Yoon ◽  
Yonggui Dong ◽  
Wei Wang ◽  
...  

Electrical impedance spectroscopy (EIS), as an effective analytical technique for electrochemical system, has shown a wide application for food quality and safety assessment recently. Individual differences of livestock cause high variation in quality of raw meat and fish and their commercialized products. Therefore, in order to obtain the definite quality information and ensure the quality of each product, a fast and on-line detection technology is demanded to be developed to monitor product processing. EIS has advantages of being fast, nondestructive, inexpensive, and easily implemented and shows potential to develop on-line detecting instrument to replace traditional methods to realize time, cost, skilled persons saving and further quality grading. This review outlines the fundamental theories and two common measurement methods of EIS applied to biological tissue, summarizes its application specifically for quality assessment of meat and fish, and discusses challenges and future trends of EIS technology applied for meat and fish quality assessment.


2018 ◽  
Vol 32 (2) ◽  
pp. 216-227 ◽  
Author(s):  
Laura Tomppo ◽  
Markku Tiitta ◽  
Reijo Lappalainen

Two types of natural fibre-polymer composite (NFPC) granules were measured with electrical impedance spectroscopy (EIS). The granules were immersed in water for 70 h, after which the excess water was removed and EIS measurements were conducted. Then, the granules were let dry in open containers at normal room temperature, and EIS measurements were repeated at increasing time intervals. The results show that the EIS response as a function of moisture content (MC) depends on the fibre content of the NFPC. In addition, the results indicate that the EIS could be used for the estimation of MC of certain type of granulate, especially at low MCs, which is relevant for the manufacturing of NFPCs. For single material type, a model with impedance modulus at a single frequency was able to predict 87–95% of the MC variation. Therefore, EIS as a non-destructive on-line technique would allow the evaluation of moisture in NFPC granules.


2021 ◽  
Vol 232 (2) ◽  
Author(s):  
Rakibul Islam Chowdhury ◽  
Rinku Basak ◽  
Khan Arif Wahid ◽  
Katy Nugent ◽  
Helen Baulch

2020 ◽  
Vol 28 ◽  
pp. 1679-1685
Author(s):  
Angeliki-Eirini Dimou ◽  
Ioanna Sakellariou ◽  
George M. Maistros ◽  
Nikolaos D. Alexopoulos

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1001
Author(s):  
Sooin Huh ◽  
Hye-Jin Kim ◽  
Seungah Lee ◽  
Jinwoo Cho ◽  
Aera Jang ◽  
...  

This study presents a system for assessing the freshness of meat with electrical impedance spectroscopy (EIS) in the frequency range of 125 Hz to 128 kHz combined with an image classifier for non-destructive and low-cost applications. The freshness standard is established by measuring the aerobic plate count (APC), 2-thiobarbituric acid reactive substances (TBARS), and composition analysis (crude fat, crude protein, and moisture) values of the microbiological detection to represent the correlation between EIS and meat freshness. The EIS and images of meat are combined to predict the freshness with the Adaboost classification and gradient boosting regression algorithms. As a result, when the elapsed time of beef storage for 48 h is classified into three classes, the time prediction accuracy is up to 85% compared to prediction accuracy of 56.7% when only images are used without EIS information. Significantly, the relative standard deviation (RSD) of APC and TBARS value predictions with EIS and images datum achieves 0.890 and 0.678, respectively.


Allergy ◽  
2021 ◽  
Author(s):  
Arturo O. Rinaldi ◽  
Angelica Korsfeldt ◽  
Siobhan Ward ◽  
Daniel Burla ◽  
Anita Dreher ◽  
...  

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