An approach for indirect monitoring of moisture content in rubberwood (Hevea brasiliensis) during hot air drying

Abstract

This study aimed to determine the equilibrium moisture content and to develop an indirect measurement technique for the moisture content (MC) by observing temperature and vapor pressure during hot air drying. The temperature and gas pressure were recorded during hot air drying at several points within wood sample specimens conforming to ASTM D 143 and AOAC, 1990. The moisture content was estimated from measured temperature and pressure. The accuracy of MC estimates was validated by oven-drying method. For validation, nine experiments at different temperatures of hot air drying were run and the indirect measurement was found to provide a good accuracy. The obtained statistics were R² = 82.5%, standard error (SE) ranging from 0.15 to 0.43, root mean square error (RMSE) ranging from 0.16 to 0.38 and mean absolute error (MAE) ranging from 0.4 to 1.1 respectively. It can be concluded that the air in wood was removed completely, especially when the MC was below the fiber saturation point. We have demonstrated an alternative moisture content monitoring method for potential adoption by the rubberwood industries.     

Continuous real-time monitoring and neural network modeling of apple slices color changes during hot air drying

A hot air drying system equipped with real-time computer vision system was used to investigate the effects of drying variables on apple slices color changes. Drying experiments were conducted at drying air temperatures of 50–70 °C, drying air velocities of 1–2 m/s, and samples thicknesses of 2–6 mm. A multilayer perceptron (MLP) artificial neural network (ANN) was also used to correlate color parameters and moisture content of apple slices with drying variables and drying time. The effects of drying air temperature and sample thickness on color changes were dominated over the effect of drying air velocity. However, non-linear and somewhat complex trends were obtained for all color parameters as function of moisture content. The MLP ANN satisfactorily approximated the color and moisture variations of apple slices with correlation coefficient higher than 0.92. Therefore, the computer vision system supplemented with ANN can be used as a non-invasive, low cost, and easy method for fast and in-line assessing and controlling of foodstuffs color and moisture changes during drying.     

Effect of infrared pretreatment on low-humidity air drying of apple slices

The dried apple is used in the preparation of weaning foods and bakery products. The current drying processes, especially hot air (HA) drying, still face the problem of longer processing time and product quality degradation. The low-humidity air (LHA) drying can be an option to retain product quality in heat-sensitive food such as apple. The present work focuses on the effect of pretreatment of apple slices with potassium metabisulfite and infrared (IR) waves on drying characteristics when subjected to LHA drying and comparing the product quality with conventional hot air and freeze drying (FD). Pretreatment with IR waves reduced the drying time by nearly 23 and 17% in LHA and HA drying, respectively. The results indicated that IR-treated and LHA-dried slices retained nearly 82–90 and 72–74% of ascorbic acid and total phenolic content, respectively and was comparable to FD slices. The drying time for LHA was nearly 37% lesser than that for HA drying. LHA-dried apple slices had better color and rehydration ratio compared to FD- and HA-dried slices.     

Use of hyperspectral imaging for the prediction of moisture content and chromaticity of raw and pretreated apple slices during convection drying

The feasibility of using spectral reflectance information in the visible—near infrared (400–1,000?nm) region to estimate moisture content (g_W/g_DM) and chromaticity (CIELAB) of apple slices was investigated during convection drying. Apple slices were pretreated with hot water blanching (50 and 70°C), acid application (citric and ascorbic), and combinations thereof before drying at 50 and 70°C. Prediction models for the space-averaged spectral reflectance curves were built using the partial least square regression method. A three-component partial least square regression (PLSR) model satisfied the minimal root mean square error (RMSE) criterion for predicting moisture content (avg. RMSEP?=?0.13, r²?=?0.99); importantly, the critical wavelengths remained the same across all pretreatments (540, 817, 977?nm). Similarly, PLSR modeling showed that the optimal set of wavelengths (in terms of RMSE) were invariant across pretreatment for CIELAB a* prediction (543, 966?nm) and CIELAB b* prediction (510, 664, 714, 914, 969?nm). The stability of the information content of these wavelengths across pretreatments indicates their independence of color changes. Additionally, the spatial information in the hyperspectral images was exploited to visualize the performance of the predictive models by pseudo-coloring their values for each pixel in a single apple slice across different drying times. This visualization of spatial distribution of predicted moisture content and chromaticity changes shows significant potential for use in online monitoring of the drying process.     

Effect of airflow rate on drying air and moisture content profiles inside a cross-flow drying column

Rice at 20.5 and 16.3% initial moisture contents (IMCs) was dried using 57°C/13% RH air at airflow rates (Qs) of 0.36, 0.46, and 0.56 (m³/s)/m² for 30, 60, and 90?min, respectively, in an experimentally simulated cross-flow drying column. Q significantly affected the drying air and rice moisture content profiles within the drying column; for a particular drying duration, the range of MCs within the column decreased as Q increased. Q also impacted the extents of intra-kernel material state gradients created and thus had potential impacts on kernel fissuring and consequent head rice yield reduction. In addition, the impact of Q on the above-mentioned profiles was dependent on the rice IMC.     

Estimation of total,open-, and closed-pore porosity of apple slices during drying

The purpose of this research was to develop an approach for porosity estimation in the process of convective air drying. Fresh apple slices were exposed to 80°C drying to equilibrium moisture content 0.2 g/g. Porosity at different stages of drying was estimated using three approaches: (1) direct volume and mass measurements, (2) pycnometer measurements, and (3) theoretical model. All three approaches were in good agreement in the range of moisture contents above 1.0 g/g. However, at moisture contents below 0.26 g/g, significant deviation of pycnometer measurements from both experimental estimates and theoretical model was observed. This difference could be explained by transformation of open pores into closed pores due to glass transition phenomenon. This study presents an example of separate quantitative estimation of total, open-, and closed-pore porosity.     

Impact of rewetting and drying of rough rice on predicted moisture content profiles during in-bin drying and storage

Accurate prediction of moisture content (MC) is vital for effective control of on-farm, in-bin drying and storage of rough rice, especially for systems using recently introduced technology to automate fan run time. The study used simulations, laboratory, and field experiments to investigate the extent to which rewetting and drying, during in-bin drying and storage, affect accuracy of predicted MC—a critical parameter for automated fan control. Vapor sorption analysis (VSA) was used to generate MC prediction models for rough rice. Simulations of in-bin drying and storage, using in-field weather data, were performed while segregating effects resulting from rewetting and drying of the rough rice and the type of fan control strategy used. Predicted MC profiles of rough rice and drying durations were compared with those resulting from using standard constants in the literature for modeling. The root mean square error associated with predicting the MC by model constants developed using the VSA was 0.54% MC and 1.32% MC dry basis (d.b.), for desorption and adsorption, respectively. Deviation in MC logged by in-bin built, field sensors and that simulated by taking into account the influence of rewetting and drying were generally within 1.5% point difference. Therefore, rewetting and drying did not affect drying duration. However, drying duration was significantly influenced by fan control strategy (p?相似文献   

Determination of moisture content and moisture content profiles in wood during drying by low-field nuclear magnetic resonance

In this article, the low-field nuclear magnetic resonance was used to measure the moisture content (MC) and MC profiles in poplar wood during real-time drying. The T₂ distribution curve at each drying stage measured using the Carr–Purcell–Meiboom–Gill pulse sequence provided detailed information in the dynamic change of free water as well as bound water of the whole wood sample. In addition, a new developed SE-SPI pulse sequence was first used to evaluate the spatially resolved T₂ distribution of the successive nondestructive sliced layer of wood. Combined with the area integration method, the moisture content in each layer was calculated, and the change of MC profiles within wood at the MC above and below fiber saturation point was well reflected.     

Computer vision for bulk volume estimation of apple slices during drying

The accuracy of imaging for bulk volume estimation of apple slices in the process of drying at temperatures from 40 to 80°C was investigated and compared with physical caliper measurements. The initial hypothesis was to estimate bulk volume of cylindrically shaped apple slices from diameter and thickness imaging. Imaging of diameter showed strong agreement with caliper measurements throughout the entire drying process, however imaging of thickness was not accurate due to the irregular shrinkage and bending phenomena. A linear model reflecting the relationship between diameter and bulk volume was developed and validated at temperatures of 40, 60, and 80°C. It showed good correlation between imaging diameter and bulk volume changes in the range of moisture contents from 9.1 to 0.25?g/g. The relative percentage error of the prediction model was approximately 6.45%, which suggests that imaging can be used as a robust tool for bulk volume estimation of apple slices during convective drying.     

Research on the nonenzymatic browning reactions in model systems based on apple slices dried by instant controlled pressure drop drying

ABSTRACT

In this study, the influences of reducing sugar, amino acids, ascorbic acids, and phenolic compounds on the nonenzymatic browning reactions in model systems based on apple slices were studied. The browning components in apple slices were removed using water and ethanol sequently, and then infiltrated with different solutions. The browning ratio (BR) of apple slice model measured by a computer vision-based image analysis system was used to evaluate the nonenzymatic browning reactions. Compared to the solution containing reducing sugar and amino acids alone, the results showed that the reducing sugar and amino acid solution with the addition of (+)-catechin, L-epicatechin, and phlorizin resulted in a remarkable increment of BR in the apple slices. L-lysine, L-arginine, and L-cysteine showed higher positive effects on the formation of BR in models based on apple slices. This study was contributed to better understand the chemical reaction in real dehydrated apple slices.     

Effects of gluten and moisture content on water mobility during the drying process for Chinese dried noodles

To investigate the water mobility during a drying process, noodles were prepared with different gluten contents (10.0%, 12.5%, 15.0%, 17.5%, 20.0%, 22.5%, or 25.0%) and moisture contents (30%, 32%, or 34%), and dried on a food moisture analysis technology platform. Three types of water were deduced from relaxation signals measured by low-field nuclear magnetic resonance (LF-NMR) spectroscopy. Peak time T₂₂ increased with gluten and moisture content but decreased with drying time from 4–6 to 1.0–1.7?ms after 1.5?h. Gluten content mainly affected the drying rate (DR) in the middle drying period, whereas initial moisture content had an influence in the middle drying period and final drying period.     

Influence of drying conditions on the moisture diffusion and fluidization quality during multi-stage fluidized bed drying of bovine intestine for pet food

In order to establish the influence of the drying air characteristics on the drying performance and fluidization quality of bovine intestine for pet food, several drying tests have been carried out in a laboratory scale heat pump assisted fluid bed dryer. Bovine intestine samples were heat pump fluidized bed dried at atmospheric pressure and at temperatures below and above the materials freezing points, equipped with a continuous monitoring system. The investigation of the drying characteristics have been conducted in the temperature range ?10 to 25 °C and the airflow in the range 1.5–2.5 m/s. Some experiments were conducted as single temperature drying experiments and others as two stage drying experiments employing two temperatures. An Arrhenius-type equation was used to interpret the influence of the drying air temperature on the effective diffusivity, calculated with the method of slopes in terms of energy activation, and this was found to be sensitive to the temperature. The effective diffusion coefficient of moisture transfer was determined by the Fickian method using uni-dimensional moisture movement in both moisture, removal by evaporation and combined sublimation and evaporation. Correlations expressing the effective moisture diffusivity and drying temperature are reported.Bovine particles were characterized according to the Geldart classification and the minimum fluidization velocity was calculated using the Ergun Equation and generalized equation for all drying conditions at the beginning and end of the trials. Walli's model was used to categorize stability of the fluidization at the beginning and end of the drying for each trial. The determined Walli's values were positive at the beginning and end of all trials indicating stable fluidization at the beginning and end for each drying condition.     

Real-time monitoring of milk powder moisture content during drying in a spouted bed dryer using a hybrid neural soft sensor

The direct measurement of the moisture content of dried products would be more interesting for process control purposes. However, the most common procedures for such measurement are either slow or expensive for industrial dryers. Alternatively, one might reduce the cost of an effective measurement procedure by using other sensors (which are less expensive and whose response is faster), which can provide information for a physical–mathematical model representing well the drying process. In this context, the objective of this work was the application of a previously developed soft sensor for the online measurement of milk powder produced in a spouted bed dryer. A hybrid neural model was used as part of a soft sensor and coupled to the data acquisition interface. The sensor was capable of estimating milk powder moisture content when the dryer was submitted to disturbances on air inlet temperature and paste inlet flow rate. On the other hand, the model failed to describe paste accumulation within the bed, which is the reason why the soft sensor tended to overestimate moisture content for longer operation times.     

Online measurement of moisture content,moisture distribution,and state of water in corn kernels during microwave vacuum drying using novel smart NMR/MRI detection system

Moisture content is unevenly distributed and hard to measure when agricultural products are dried using microwave drying. A low-field nuclear magnetic resonance/imaging (NMR/MRI) and microwave vacuum drying (MVD) combination equipment was developed. The residual moisture content, distribution, and state of water (free, immobilized, and bound) in fresh corn kernels during MVD were quickly measured in real time. NMR results indicated that the amplitude of free and immobilized water decreased very rapidly at the early stage of MVD, while the amplitude of bound water experienced a similar rapid decrease at the last stage. MRI results indicated that the moisture content was always distributed unevenly during MVD, especially at the early stage. The moisture distribution tended to become uniform when drying progressed and the bound water became dominant. The residual moisture content of corn kernels and integral (total) amplitude of NMR were found to fit well with a linear model (R²?>?0.991, P?相似文献   

Color changes,nitrite content,and rehydration capacity of edible bird's nest by advanced drying method

This article presents the authors’ first attempt to improve quality of edible bird’s nest through continuous and intermittent low-temperature drying (25 and 40°C) with infrared and ultraviolet C (UVC) treatments. The attributes of quality were compared in regard to quality of hot-air-dried samples at 70–90°C. Experimental results showed that a significant improvement in the quality of edible bird’s nest in terms of minimizing color changes and rehydration capacity using intermittent low-temperature drying with infrared and UVC drying profile. However, it was also found that any drying method has less significant effect on the nitrite content of edible bird’s nest.     

Global sensitivity analysis applied to drying models for one or a population of granules

The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring sensitivity in a broad parameter space, is performed to detect the most sensitive factors in two models, that is, one for drying of a single granule and one for the drying of a population of granules [using population balance model (PBM)], which was extended by including the gas velocity as extra input compared to our earlier work. β₂ was found to be the most important factor for the single particle model which is useful information when performing model calibration. For the PBM‐model, the granule radius and gas temperature were found to be most sensitive. The former indicates that granulator performance impacts drying behavior, the latter is informative with respect to the variables that primarily need to be controlled during continuous operation. In addition, several GSA techniques are analyzed and compared with respect to the correct conclusion and computational load. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1700–1717, 2014     

A differential shrinkage approach for evaluating particle formation behavior during drying of sucrose,lactose, mannitol,skim milk,and other solid-containing droplets

Particle formation process during drying of solid-containing droplets exerts profound influence on the property and quality of dried particles. A differential shrinkage approach is proposed to describe the particle formation behavior of different materials, by evaluating how the droplet shrinkage kinetics of the given material(s) deviates from the ideal shrinkage. Sucrose was selected as the reference material to establish ideal shrinkage kinetics, as its shrinkage at 10, 30, and 50?wt.% initial concentrations well followed the ideal shrinkage at all temperatures tested (70, 90, and 110?°C). Comparing the differential shrinkage kinetics of sucrose, lactose, and mannitol showed that mannitol has a strong crust-forming tendency, which could not be explained by the difference in the solubility of the three materials. By establishing a differential shrinkage curve for each material, this approach offers a straightforward and powerful method to evaluate the particle formation property of the material at various initial concentrations.     

A continuum‐approach modeling of surface composition and ternary component distribution inside low fat milk emulsions during single droplet drying

Surface composition of dairy powders plays an important role in determining the functionality. However, the surface composition may be different from the bulk composition because of component migration during drying. In this study, a comprehensive mathematical model has been developed to describe the phenomena. To the best of our knowledge, it is the first mathematical model which predicts the dynamics of surface composition during drying. The model consists of a set of equations of conservation of mass of water, lactose, protein, and fat as well as conservation of heat and momentum in which the effects of diffusion induced material migration and surface activity are incorporated. This model is applicable to describe the kinetics of surface composition of dairy droplets during drying. It suggests that both diffusion and protein surface activity govern the component segregation during drying. The study indicates that the model implementing the measured initial surface composition as the initial conditions generates more realistic profiles than the one using the bulk composition. The modeling confirms that the difference between the surface and bulk composition that occurs prior to drying is not primarily governed by diffusion, but the emulsion's atomization behavior seems to play an essential role in the overrepresentation of fat. © 2017 American Institute of Chemical Engineers AIChE J, 63: 2535–2545, 2017     

Enhanced methods for experimental investigation of single droplet drying kinetics and application to lactose/water

In this work, a suspension device is presented that can be used for the investigation of single droplet drying kinetics at temperatures from ambient to 200°C. Evaluation is hybrid, using both camera data and a water mass balance. In this way, drying kinetics can be captured for shrinking droplets and also after a constant diameter of the wet particle has been reached and during inflation/deflation periods. Results can be further enhanced by X-ray μ-CT investigation of the internal morphology of dried particles. It is proposed to read critical conditions for crust formation from a plot of evaporation flux over water mass fraction. Repeatability and accuracy of the experimental and evaluation methods were checked with pure water droplets. Moreover, the entire evaluation was conducted for aqueous solutions of lactose with various initial concentrations.     

Nonlinear model of pneumatic conveying dryer for economic process control

Abstract

This paper presents a nonlinear dynamic model, suitable for economic process control of pneumatic conveying dryer for drying of food grains. The dynamic model is developed by reshaping the process equations derived for the batch drying, dilute phase, and a negative-pressure conveying system. The dynamic model parameters are identified by numerically solving a nonlinear least squares optimization problem, subject to a set of differential and algebraic equality constraints that describe the system dynamics and bounds in the parameters. A detailed parametric uncertainty and sensitivity analysis are performed providing valuable insight into the influence of critical model parameters on observables, the interplay among various parameter-state-measured disturbances, and quantifying uncertainties in the model. Further, different process economic performance and product quality indicator of uncertain dryer model are studied. The model validation study as performed with the underlying process shows a very good agreement in understanding necessary dynamic characteristics and interplay between the various parameter of interest.