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Estimation of Moisture Ratio of a Mushroom Undergoing Microwave-vacuum Drying Using Artificial Neural Network and Regression Models
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Poonpat Poonnoy
Veröffentlicht/Copyright:
31. Oktober 2007
The drying rate of a mushroom undergoing microwave-vacuum (MV) drying (MVD) was controlled by moisture dissipation and was dependent on vacuum pressure levels. The main objective of this work was to develop artificial neural network (ANN) model to predict moisture ratio of MV-dried mushrooms. One-hidden-layer feed-forward ANN models were trained and validated with experimental data. The Levenberg-Marquardt algorithm was utilized in regulating the ANN model weights and biases. Inputs for ANN models were vacuum pressure and drying time. Output from ANN models was moisture ratio at a given drying time. Reduced chi-square (X 2) and root mean square error (RMSE), and residual sum of squares (RSS) of the results from ANN models were calculated and compared with those of a modified Page's model (an experimental-based mathematical model), which is commonly used in the literature. The X 2, RMSE, and RSS of the ANN model (2.272 x 10 -5, 4.023 x 10 -3, and 3.204 x 10 -3, respectively) were found to be lower than those of the modified Page's model (6.692 x 10 -4, 2.561 x 10 -2, and 12.98 x 10 -2, respectively). These results indicate that the feed-forward ANN model represented the drying characteristics of mushrooms better than the modified Page's model. Therefore, the ANN model could be considered as a better tool for estimation of the moisture content of mushrooms than by the modified Page's model.
Published Online: 2007-10-31
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Artikel in diesem Heft
- Article
- Mathematical Analysis of a Novel Formaldehyde Remediation Process
- A Multi-Level Methodology for Conceptual Reaction-Separation Process Design
- Forecasting Influent-Effluent Wastewater Treatment Plant Using Time Series Analysis and Artificial Neural Network Techniques
- Prediction of Biomedical Waste Load at Centralized Treatment Facility
- Hedge's Ultimate Numerical Technique (HUNT) for Steady State Diffusion Problem
- Crisp and Fuzzy Optimisation Approaches for Water Network Retrofit
- A MINLP Solution for Pellet Reactor Modeling
- Instrumentation Network Design for Solids Processes
- Sliding-mode Observer for Uncertainty Estimation in a Class of Chemical Reactor: A Differential-Algebraic Approach
- CFD Simulation of Fine Particle Gravity Separation in Hindered-settling Bed Separators
- Multirate Constrained Predictive Control: Algorithm and Experimental Results
- Development of Web Based Computer Package for the Simulation of Thermal Desalination Processes
- A Unified Approach for Modeling Three-Way Catalytic Converters and NOx Traps with a Minimum Set of Tunable Parameters
- Assessing the Deposition of a Water Spray on a Plate in a Simple Box Configuration Using Computational Fluid Dynamics (CFD)
- Mathematical Modeling of Supercritical Fluid Extraction of Fatty Acids from Trout Powder: Correlation of Mass Transfer Parameters
- Simulation and Analysis of Fluid Dynamic Behaviour of Foods during Filling Processes
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- Simulation of the Coke Calcining Processes in Rotary Kilns
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- Prediction of Deposition Patterns in a Pilot-Scale Spray Dryer Using Computational Fluid Dynamics (CFD) Simulations
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