An Electrochemical Impedance Spectroscopy System for Monitoring Pineapple Waste Saccharification
[EN] Electrochemical impedance spectroscopy (EIS) has been used for monitoring the enzymatic pineapple waste hydrolysis process. The system employed consists of a device called Advanced Voltammetry, Impedance Spectroscopy & Potentiometry Analyzer (AVISPA) equipped with a specific software applic...
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Zusammenfassung: | [EN] Electrochemical impedance spectroscopy (EIS) has been used for monitoring the enzymatic
pineapple waste hydrolysis process. The system employed consists of a device called Advanced
Voltammetry, Impedance Spectroscopy & Potentiometry Analyzer (AVISPA) equipped with a specific
software application and a stainless steel double needle electrode. EIS measurements were conducted
at different saccharification time intervals: 0, 0.75, 1.5, 6, 12 and 24 h. Partial least squares (PLS)
were used to model the relationship between the EIS measurements and the sugar determination by
HPAEC-PAD. On the other hand, artificial neural networks: (multilayer feed forward architecture
with quick propagation training algorithm and logistic-type transfer functions) gave the best results
as predictive models for glucose, fructose, sucrose and total sugars. Coefficients of determination (R2
)
and root mean square errors of prediction (RMSEP) were determined as R2 > 0.944 and RMSEP < 1.782
for PLS and R2 > 0.973 and RMSEP < 0.486 for artificial neural networks (ANNs), respectively.
Therefore, a combination of both an EIS-based technique and ANN models is suggested as a
promising alternative to the traditional laboratory techniques for monitoring the pineapple waste
saccharification step
Financial support from the European FEDER and the Spanish government (MAT2012-34829-C04-04), the Generalitat Valenciana (PROMETEOII/2014/047) and the FPI-UPV Program funds are gratefully acknowledged.
Conesa Domínguez, C.; Ibáñez Civera, FJ.; Seguí Gil, L.; Fito Maupoey, P.; Laguarda-Miro, N. (2016). An Electrochemical Impedance Spectroscopy System for Monitoring Pineapple Waste Saccharification. Sensors. 16(188). https://doi.org/10.3390/s16020188 |
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