S. Almonacid

Determination of Antioxidant Capacity, Total Phenolic Content and Mineral Composition of Different Fruit Tissue of Five Apple Cultivars Grown in Chile

Apples (Malus domestica Borkh.) have been identified as one of the main dietary sources of antioxidants, mainly phenolic compounds. These compounds vary in their composition and concentration, among cultivars and fruit tissues. In this research, the total phenolic content (Folin-Ciocalteau assay), antioxidant capacity (Ferric Reducing Antioxidant Power, FRAP assay) and mineral composition in three fruit tissues (peel, pulp and whole fruit), of apple cultivars commonly used for dried apple production in Chile, were studied. In addition, the physical-chemical characteristics (dry weight, pH, titratable acidity, soluble solids content and color) were also evaluated. The results indicated that the total phenolic content, the antioxidant capacity, and the mineral composition, of peel were substantially higher than those of whole fruit, and pulp for all the cultivars studied. Among cultivars, �Red Delicious� apple peels have a significantly much higher content of total phenolic (11.6 mg gallic acid equivalents [GAE] g-1 FW) and a higher FRAP (209.9 µmol Fe+2 g-1 FW). Additionally, a high correlation between total phenolic content and antioxidant capacity was found in all the cultivars and fruit tissues analyzed, except in the apple pulp. On the other hand, the physical and chemical composition differed among cultivars and fruit tissues. In conclusion, our results demonstrated that the total phenolic content, antioxidant capacity, mineral composition, and physical and chemical characteristics vary considerably depending on the apple cultivars and fruit tissues analyzed.

Development of an ingredient containing apple peel, as a source of polyphenols and dietary fiber.

Apple peel is a waste product from dried apple manufacture. The content of phenolic compounds, dietary fiber, and mineral are higher in apple peel, compared to other edible parts of this fruits. The objective of this study was to develop an ingredient from Granny Smith apple peel, using a pilot scale double drum-dryer, as drying technology. The control of all steps to maximize the retention of phenolic compounds and dietary fiber was considered. Operational conditions, such as drying temperature and time were determined, as well as important preprocessing steps like grinding and PPO inhibition. In addition, the physical-chemical characteristics, mineral and sugar content, and technological functional properties such as water retention capacity, solubility index, and dispersability among others, were analyzed. A simple, economical, and suitable pilot scale process, to produce a powder ingredient from apple peel by-product, was obtained. The drying process includes the application of ascorbic acid at 0.5% in the fresh apple peel slurry, drum-dryer operational conditions were 110 degrees C, 0.15 rpm and 0.2 mm drum clearance. The ingredient developed could be considered as a source of phenolic compounds (38.6 mg gallic acid equivalent/g dry base) and dietary fiber (39.7% dry base) in the formulation of foods. Practical Application: A method to develop an ingredient from Granny Smith apple peel using a pilot scale double drum-dryer as drying technology was developed. The method is simple, economical, feasible, and suitable and maximizes the retention of phenolic compounds and dietary fiber present in the raw matter. The ingredient could be used in the formulation of foods.

Mathematical model development, experimental validation and process optimization: retortable pouches packed with seafood in cone frustum shape

Abstract The aim of this research was to develop and validate a mathematical model coupled with an optimization technique for thermal processing of conduction-heated foods in retortable pouches in order to: (a) search for variable retort temperature profiles to minimize process time, and (b) search for variable retort temperature profiles to minimize quality gradient (thiamine) within the product. The model was validated utilizing Jack mackerel (Trachurus Murphyi) packed in retortable pouches. The conjugated gradient method was utilized as a search technique to find the best variable retort temperature profile to satisfy the specific objectives. The simulation results were in good agreement with the observed temperatures. The prediction errors obtained in the validation study were under 5%. Non-significant differences (P

Simultaneous heat and mass transfer applied to non-respiring foods packed in modified atmosphere

A mathematical model to predict heat and mass transport phenomena in non-respiring food packed in modified atmosphere (MAP) was developed and validated. The model incorporates simultaneous gas convection, sorption, diffusion, heat convection and conduction. The model was applied to MAP systems containing CO2 ,O 2 ,N 2 and H2O. Validation test was done with gelatin. The average errors between experimental and simulated values were low: <0.6 (C) for the temperatures, 3% for relative humidity and <1.43% for the headspace gas composition. Model predictions during heating and cooling phases indicate that temperature modification of the packaged product can be quite slow, reflecting the relevance of proper chilling in the packaging, transport and storage processes of MAP products. The model applied to shelf-life studies, for specific products, can be utilized to identify facility and product handling improvements to generate the greater positive impact on product quality. The development of this or similar mathematical tools would allow for more technical and informed management decisions. 2003 Elsevier Ltd. All rights reserved.

MULTIOBJECTIVE OPTIMIZATION APPROACH: THERMAL FOOD PROCESSING

The objective of this study was to utilize a multiobjective optimization technique for the thermal sterilization of packaged foods. The multiobjective optimization approach used in this study is based on the optimization of well-known aggregating functions by an adaptive random search algorithm. The applicability of the proposed approach was illustrated by solving widely used multiobjective test problems taken from the literature. The numerical results obtained for the multiobjective test problems and for the thermal processing problem show that the proposed approach can be effectively used for solving multiobjective optimization problems arising in the food engineering field.

A Comparative Study of Stout Beer Batch Fermentation Using Free and Microencapsulated Yeasts

Because many questions arise regarding the use of immobilization technology to consistently produce a high quality beer, this work focuses on the effects of using an immobilization matrix in the fermentation process. The aim of this study was to explore the feasibility and potential uses of immobilization on sensorial characteristics such as color, flavor, and headspace compounds of stout beer, when using batch fermentation. Batch production of beer was conducted as a standard ale process for stout beer production. For the immobilized yeasts fermentation, cells were microencapsulated in alginate, by using the Thiele modulus procedure for microcapsule design. Glucose concentration, cell multiplication, cell viability, specific gravity, pH, Brix, and ethanol were monitored throughout the fermentation process. Both, sensorial analysis (statistic triangle tests) and instrumental methods (gas chromatography to measure headspace compounds and visible spectrophotometer to quantify the color) were used to evaluate characteristics of the beer that was produced from immobilized and free yeast fermentations. Free and immobilized yeasts fermentation showed no significant difference (p > 0.05) for all variables of interest. The profile of headspace compounds was different, perhaps because of changes in yeast’s behavior and the presence of secondary metabolites. However, immobilization did not have a significant impact on the beer flavor, as detected by the sensorial triangle test.

Kinetic Parameter Determination for Enzyme Hydrolysis of Fish Protein Residue Using D-optimal Design

The objective of this work was to compare the quality of parameter estimation from experiments with protein hydrolysis of fish muscle carried out following a traditional versus D-optimal design of experiments. Traditional design was done from hydrolysis experiments using the rapid titration method, from which a large number of data points was obtained and made available for parameter estimation. D-optimal design is recommended under conditions when it would not be possible to use rapid titration with analytical tools. Such conditions would make it necessary to reduce the number of samples that would need to be taken as well as the error and variance in the estimated parameters needed for the kinetic model. Results have shown that D-optimal and traditional designs of experiments obtained accurate and reliable estimates of kinetic model parameters, with a great difference in the number of data points between both types of design: 18 points in traditional and 3 points in D-optimal design. Nevertheless, a few number of observations in D-optimal design impacted negatively the confidence interval because of a low degree of freedom. Confidence intervals ranging from 7.8% to 87% of the parameters values were obtained with D-optimal design method in contrast with traditional design where confidence intervals ranged from 6.2% to 15% of the parameters values. It is estimated that combining the advantages of both types of design will result in an optimal experimental design in terms of reliability, accuracy, and costs saving of analysis. This would be done by determining the number of observations required to achieve an appropriate confidence interval (about six or more experimental points) and, then, a selection of the best experimental points of a curve of hydrolysis by D-optimal design.

Measuring and Predicting Head Space Pressure during Retorting of Thermally Processed Foods

UNLABELLED Traditional metal cans and glass jars have been the mainstay in thermally processed canned foods for more than a century, but are now sharing shelf space with increasingly popular flexible pouches and semi-rigid trays. These flexible packages lack the strength of metal cans and glass jars, and need greater control of external retort pressure during processing. Increasing internal package pressure without counter pressure causes volumetric expansion, putting excessive strain on package seals that may lead to serious container deformation and compromised seal integrity. The primary objective of this study was to measure internal pressure build-up within a rigid air-tight container (module) filled with various model food systems undergoing a retort process in which internal product temperature and pressure, along with external retort temperature and pressure, were measured and recorded at the same time. The pressure build-up in the module was compared with the external retort pressure to determine the pressure differential that would cause package distortion in the case of a flexible package system. The secondary objective was to develop mathematical models to predict these pressure profiles in response to known internal temperature and initial and boundary conditions for the case of the very simplest of model food systems (pure water and aqueous saline and sucrose solutions), followed by food systems of increasing compositional complexity (green beans in water and sweet peas in water). Results showed that error between measured and predicted pressures ranged from 2% to 4% for water, saline, and green beans, and 7% to 13% for sucrose solution and sweet peas. PRACTICAL APPLICATION   Flexible packages have limited strength, and need more accurate and closer control of retort pressure during processing. The package becomes more flexible as it heats and might expand with increasing internal pressure that may cause serious deformation or rupture if not properly controlled and/or counterbalanced with external retort pressure. This article describes methods for determining exactly what the retort pressure profile will need to be to avoid this problem during retorting, and mathematical models to predict these pressures in response to known internal temperature and initial/boundary conditions.

Estimating Reaction Rates in Squid Protein Hydrolysis Using Artificial Neural Networks

In this study, the use of artificial neural networks (ANN) for estimating reaction rates in enzymatic hydrolysis of squid waste protein was investigated. This is a complex process because a number of inherent simultaneous inhibition and enzyme inactivation reactions occur during hydrolysis that make it difficult to develop a reliable kinetic model by more traditional deterministic approaches. A series of 12 enzyme hydrolysis experiments were carried out on samples of squid waste under specified conditions of temperature, pH, and initial enzyme and substrate concentrations. Experimental data in the form of substrate concentration over time were taken as real time course data (TCD), and divided into three groups for respective use in training, validating, and testing the model. A feed-forward architecture was utilized to construct the necessary predictive model. The network was trained until the mean squared error function between target and actual output values reached a desired minimum. Data sets from the remaining two groups were used for subsequent validation and testing of the model. The model performed well when tested against experimental data in the third group (not used in its development) and taken over a wide range of initial conditions. Maximum differences between experimental and predicted values of substrate concentration at any point in time ranged from 0.3 to 0.5 g L-1 (1% to 3% of initial substrate concentration), with correlation coefficients between predicted and experimental results ranging from 0.95 to 0.97.

Mathematical Estimations of Impact of Thermal Processing on Microbial Inactivation and Quality Retention

The basic principles of canning have not changed dramatically since Nicholas Appert and Peter Durand developed the process. The sterilization and pasteurization of foods have a long tradition, and this tradition will likely continue due to its convenience and advances in the technology as well as the packaging materials. Mathematical modeling has been gaining recognition in the food industry, particularly for applications such as thermal sterilization and pasteurization, helping the food industry to deliver safe processed products that also retain quality to a greater extent. In recent years, several researchers have been developing applications for multiobjective optimization in food processing, especially in the area of thermal food sterilization.