Characterizing Moisture Content and Gradients in Pinus radiata Soft Wood Using Electrical Impedance Spectroscopy

2010 ◽  
Vol 29 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Terry C. Chilcott ◽  
Dewi Halimanto ◽  
Tim A. G. Langrish ◽  
John M. Kavanagh ◽  
Hans G. L. Coster
2002 ◽  
Vol 12 (1) ◽  
pp. 17-29 ◽  
Author(s):  
T. Repo ◽  
D.H. Paine ◽  
A.G. Taylor

A method, electrical impedance spectroscopy (EIS), is introduced to study seed viability non-destructively. Snap bean (Phaseolus vulgaris L.) seeds were studied by EIS to determine the most sensitive EIS parameter(s) and the optimal range of moisture content (MC) for separation of viable and non-viable seeds. Hydrated seeds exhibited two impedance arcs in the complex plane at the frequency range from 60 Hz to 8 MHz, and impedance spectra of viable and non-viable seeds differed. The hydrated seeds were best-modelled by an equivalent electrical circuit with two distributed circuit elements in series with a resistor (Voigt model). Moisture content and seed viability had strong effects on the EIS parameters. The most sensitive EIS parameters for detecting the differences between viable and non-viable seeds were the capacitance log(C2), the resistance R2, the resistance ratio R2/R1 and the apex ratio, which all represent specific features of the impedance spectrum. The highest differentiation in the EIS parameters between the viable and non-viable seeds occurred in partially imbibed seeds between MC of 40 and 45% (fresh weight basis).


2013 ◽  
Vol 133 (12) ◽  
pp. 630-635
Author(s):  
Yasumasa Ando ◽  
Tsutomu Fujita ◽  
Naomi Amari ◽  
Tadashi Ebihara ◽  
Koichi Mizutani ◽  
...  

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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