Optimization of drying food products: application to fruits

Air drying is one of the most used unit operation in food processing. Simulation or designing the air-drying operation requires the mathematical description of food moisture evolution during the process, known as drying kinetics. The structure of the food materials goes through deformations due to the simultaneous effect of heat and mass transfer during the drying process. These deformations lead to changes in many quality attributes and directly affect physical properties (i.e. the mass diffusion coefficient). Changes in volume, “shrinkage”, negatively impact the quality perception of dried products by consumer. The knowledge of the changes in the properties of foods that occur during drying is hence needed for better designing the process. The aim of this study is to understand the effect of drying on quality of fruit which typically has high moisture content (i.e. pear and grape) and to develop a mathematical model which quantify the drying of this food matrix. To this purpose the drying kinetics, shrinkage and structure modifications (through SEM analysis) were experimentally evaluated. During drying, the macroscopic transport of water through the cellular tissue constituting the fruit is largely controlled by the microscopic distribution of water and air on a cellular and subcellular distance scale and by membranes permeability. 1H pulsed low resolution NMR allows to obtain quantitative information on water distribution and diffusion by detecting the proton signal predominantly due to H2O contained in vegetable tissue. Therefore, portable-NMR was used to determine the drying moisture profile and thickness reduction of pears. Portable-NMR also allowed to investigate water mobility in fresh and dried pears by measuring the longitudinal and transverse relaxation times, and the self-diffusion coefficient. For fruit, such as grape, drying is a slow and very energy intensive process because the waxy peel has low permeability to moisture. In order to enhance the drying rate, pretreatments are used. In this thesis, both chemical (by dipping in an ethyl oleate solution) and physical (by abrasion) pretreatments were analysed. It was found that ethyl oleate and abrasion pretreatments have the same effect in reducing the drying time, but the second one is to be preferred because it avoids the use of chemical additives and permits safer raisin to be produced. Moreover, the samples pretreated by peel abrasion showed less shrinkage and no cracks on the peel surface with respect to those pretreated with ethyl oleate solution. To obtain a detailed prediction of moisture distribution during drying, in the thesis, a diffusion model with Fickian moisture transfer was coupled with an empirical law which considers the effect of shrinkage. A numerical solution technique, based on the method of finite elements, is used with an adaptive mesh. The results match well with the experimental results. In particular, a good agreement between experimental and theoretical data of moisture ratio during drying was found for both fruits. The model also well predicted the moisture profile along the pear thickness obtained by NMR

Numerical solution of coupled mass and energy balances during osmotic microwave dehydration

The mass and energy transfer during osmotic microwave drying (OD-MWD) process was studied theoretically by modeling and numerical simulation. With the aim to describe the transport phenomena that occurs during the combined dehydration process, the mass and energy microscopic balances were solved. An osmotic-diffusional model was used for osmotic dehydration (OD). On the other hand, the microwave drying (MWD) was modeled solving the mass and heat balances, using properties as function of temperature, moisture and soluble solids content. The obtained balances form highly coupled non-linear differential equations that were solved applying numerical methods. For osmotic dehydration, the mass balances formed coupled ordinary differential equations that were solved using the Fourth-order Runge Kutta method. In the case of microwave drying, the balances constituted partial differential equations, which were solved through Crank-Nicolson implicit finite differences method. The numerical methods were coded in Matlab 7.2 (Mathworks, Natick, MA). The developed mathematical model allows predict the temperature and moisture evolution through the combined dehydration process.Facultad de Ingenierí

Study of the Drying Kinetics of Pears from cultivar D. Joaquina

Drying is one of the most widely used methods for preserving foods allowing extending their shelf life by minimizing the moisture content in the food so that the deterioration reactions will not be able to occur. The objective of the present work was to determine the drying kinetics of pears from cultivar D. Joaquina, and then use the experimental data to model the drying kinetics by means of different thin layer equations found in the literature. For that two temperatures were tested (60 and 70 ºC) and seven models were analysed. The results obtained allowed concluding that while some models were very adequate to predict the drying behaviour like Newton, Page, Modified Page, Henderson & Pabis and Logarithmic, others were not so good, such as Wang & Singh and Vega-Lemus

Microwave and ultrasound pre-treatments for drying of the “Rocha” Pear: impact on phytochemical parameters, color changes and drying kinetics

The objective of this research was to evaluate the effect of drying temperature and innovative pre-treatments (i.e., microwave and ultrasound) on “Rocha” pear drying behavior and quality characteristics, such as color, total phenolic content and antioxidant activity. Experiments were carried out with pear slabs subjected to microwaves (2450 MHz, 539 W, 4 min, microwave oven) and ultrasounds (35 kHz, 10 min, in an ultrasonic bath) as well as control samples. The drying process was conducted in a tray dryer at three different temperatures (50, 55 and 60 °C) and a fixed air velocity of 0.75 m/s. Microwave technology resulted in a higher quality deterioration in dried pear samples compared to those of controls and ultrasound pre-treated samples. The combined application of ultrasound pre-treatment and the higher drying temperature of 60 °C was characterized by the lowest color changes (ΔE = 3.86 ± 0.23) and higher preservation of nutritional parameters (total phenolic content, TPC = 345.60 ± 8.99; and antioxidant activity, EC50 = 8.80 ± 0.34). The drying characteristics of pear fruits were also analyzed by taking into account empirical models, with the Page model presenting the best prediction of the drying behavior. In conclusion, ultrasound application is a promising technology to obtain healthy/nutritious dried “Rocha” pear snacks as dietary sources for consumers.info:eu-repo/semantics/publishedVersio

Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Mathematical Modeling of Sun and Solar Drying Kinetics of Fermented Cocoa Beans

In this study, thin layer drying experiments were conducted to compute drying characteristics of fermented cocoa beans in open sun and indirect natural convection solar dryer. The drying experiments were conducted at the same time for comparison. Three different thin layers drying of the fermented beans were examined under field conditions for Akure, Nigeria. The drying process took place only in the falling rate period. The drying curves obtained from the experimental data were fitted to thirteen (13) different thin layer mathematical models. All the models were compared according to three evaluation parameters. These include coefficient of determination (R2), Root mean square error (RMSE) and Chi-square (X2).The results showed that increasing drying air temperature resulted to shorter drying times. The Vermal et al. model was found to be the most suitable for describing the drying curve of the convective indirect solar drying process of cocoa beans with R2 = 0.9562, X2=0.0069 and RMSE=0.0067; while, the Midilli and Kucuk model, best described the drying curve of fermented cocoa beans under open sun with R2 = 0.9866, X2=0.0024 and RMSE=0.0023

Computational fluid dynamics (CFD) modelling and experimental validation of thermal processing of canned fruit salad in glass jar

In this paper the heat transfer of a fruit salad during the pasteurization treatment was investigated. The objective of the paper was to develop and validate a computational fluid dynamics (CFD) model for predicting the temperature profiles during the thermal processing of this sample. Samples of a commercial fruit salad, composed of five different fruits with different shapes, sizes and thermal properties, submerged in water/sugar syrup, were submitted to thermal treatments in a pilot plant and temperature profiles at different locations were experimentally recorded. Results showed that the slowest heating point (SHP) was positioned at 19–20% of the can height: fruit closest to the SHP such as pear presented the lowest F value. Moreover, F values resulted to be influenced by the distance from the jar bottom as function of natural convection motion of the syrup. CFD model simulations data were then successfully validated against the experimental ones: results, expressed as RMSE, showed a good fitting between calculated and experimental data, both for syrup (mean RMSE 1.47 C) and fruit pieces (mean RMSE 1.63 C). In addition, F values calculated from both experimental and simulated temperatures resulted very similar with only little differences. In conclusion, the proposed approach and mathematical model can thus be usefully applied for the simulation and prediction of thermal processes of canned fruit salad for process design and optimization

Collapsing granular suspensions

A 2D contact dynamics model is proposed as a microscopic description of a collapsing suspension/soil to capture the essential physical processes underlying the dynamics of generation and collapse of the system. Our physical model is compared with real data obtained from in situ measurements performed with a natural collapsing/suspension soil. We show that the shear strength behavior of our collapsing suspension/soil model is very similar to the behavior of this collapsing suspension soil, for both the unperturbed and the perturbed phases of the material.Comment: 7 pages, 5 figures, accepted for publication in EPJ