VARIOUS ANTIBROWNING AGENTS AND GREEN TEA EXTRACT DURING PROCESSING AND STORAGE

The production of bottled green tea beverage has encountered a browning problem mainly caused by the autoxidation of flavanols (catechins). Five antibrowning agents, ascorbic acid, kojic acid, citric acid, L-cysteine, and glutathione, were tested for their effectiveness on preventing the color changes of green tea extract during processing and storage. One-tenth percent of the antibrowning agents were individually added to the freshly prepared green tea extracts, heat processed at 121C for 1 min, and then stored in a 50C oven for up to 12 days. Samples of fresh, processed, and stored tea extracts were measured for their color maintenance and (-)-epigallocatechin gallate (EGCG) content to compare the antibrowning and antioxidant effects of these agents, respectively. Results indicated that the antibrowning activity and antioxidant effect of individual agents often did not correlate with each other, but citric acid showed both significant antibrowning and antioxidant effects on green tea extract.     

Branched Oligosaccharides Concentrated by Yeast Fermentation and Effectiveness as a Low Sweetness Humectant

A branched oligosaccharides (BOS) mixture was prepared from liquefied corn starch using Bacillus lichenifrmis maltogenic amylase (BLMA). A highly concentrated BOS was prepared by removing glucose and maltose through yeast fermentation, which increased the BOS content. Water activity (a_w) of bread went from 0.87 to 0.82 when 10% (w/w) or to 0.78 when 20% (w/w) BOS was added. BOS lowered a_w more effectively as concentration of BOS increased. The water sorption isotherm of BOS was much higher than that of sucrose at a_w, 0.1–0.8. BOS also prevented starch retrogradation in bread, probably due to steric hinderance and to the state of water retained by BOS. Relative sweetness of BOS was ± 17.5% of sucrose. The BOS mixture produced by BLMA might provide a new type humectant for foods that is low in sweetness and retards retrogradation.     

TEMPERATURE-TOLERANT FISH PROTEIN GELS USING KONJAC FLOUR

Shear stress and strain values of surimi gels made from Alaska pollock and Pacific whiting were measured upon cooling, reheating, and freeze/thawing. Konjac flour was introduced to investigate its ability to maintain fracture properties of surimi gels against various temperatures. Gel colors (CIE L*,a*,b*) were also measured as affected by various levels of konjac flour. Konjac flour (5%) showed its ability to reinforce shear stress of gels 8-10 times in both whiting and pollock surimi. Gels with 4% konjac flour were the most heat-tolerant in both surimi. Surimi gels with konjac flour exhibited an ability to maintain consistent shear strain values against repeated freeze/thaw abuse. Konjac flour, up to 2%, increased lightness of gels, while yellow hue increased gradually up to 5%.     

Functional Properties and Shelf Life of Fresh Surimi from Pacific Whiting

Total aerobic plate count (APC), shear stress, shear strain, and color of fresh Pacific whiting surimi stored at 5°C were determined at day 0, 1, 3, 5, and 7. Frozen surimi was prepared with four levels of cryoprotectams (0, 3, 6, and 9%) and was compared with fresh surimi for gelforming ability. Fresh Pacific whiting surimi had a shelf life of 5 days. The gel functionality remained unchanged throughout the storage time. Strain values of fresh surimi were not different from those of frozen surimi with 9% cryoprotectants, but stress values of fresh surimi were almost three times higher than those of frozen surimi.     

Palatability and Texture of Ground Meat Patties Made with Varying Amounts of Pork and Turkey

Meat mixtures were prepared containing pork lean and turkey lean in ratios of 0/100, 33/67, 100/0 and a constant fat content. Blends were prepared with and without a commercial seasoning-antioxidant mixture (SA) and evaluated after 0, 3, 6 or 9 days (4°C) storage or 0, 14 or 28 days (-20°C) storage. Flavor intensity scores for blends containing up to 67% turkey were not different (P > 0.05); however, 100% turkey patties had lower flavor intensity scores. Off-flavor and firmness scores were not affected by blend for products containing between 33% and 100% pork lean, while storage had no effect on off-flavor in products containing SA. Juiciness was not affected by blend or storage. Results indicate acceptable patties can be made from blends of pork and turkey containing relatively high levels of turkey.     

PURIFICATION AND CHARACTERIZATION OF A SERINE PROTEINASE FROM THE TUNA PYLORIC CAECA

A 15.0 kDa serine proteinase with collagenase activity from pyloric caeca of tuna, Thunnus thynnus, was purified in four steps; acetone precipitation, gel filtration chromatography on a Sephadex G‐100, ion‐exchange chromatography on a DEAE‐Sephadex α‐50 and gel filtration chromatography on a Sephadex G‐75 column. The purification and yield were 30.5‐fold and 0.023%, respectively, as compared with those in the starting crude extract. The optimum pH and temperature for the purified collagenolytic enzyme were around pH 7.5 and 55C, respectively. The purified proteinase was strongly inhibited by metal ions (Hg²⁺ and Zn²⁺) and serine proteinase inhibitors (PMSF, TLCK and soybean trypsin inhibitor) suggesting it is a serine protease. The K_m and V_max of the purified enzyme for collagen type I were approximately 3.82 mM and 851.5 U, respectively.     

Electrodeposited Ni,Fe,Co and Cu single and multilayer nanowire arrays on anodic aluminum oxide template

The Ni, Fe, Co and Cu single and multilayer nanowire arrays to make perpendicular magnetic recording media were fabricated with nanoporous anodic aluminum oxide (AAO) templates from Watt solution and additives by the DC electrodeposition. The results show that the diameters of Ni, Fe, Co and Cu single and multilayer nanowires in AAO templates are 40–80 nm and the lengths are about 30 μm with the aspect ratio of 350–750. The magnetic properties of the prepared nanowires are different under different electrodepositing conditions. The remanences (B_r) of Ni/Cu/Fe multilayer nanowires are lower than those of others multilayer nanowires, and coercivity (H_c) of Ni/Cu/Fe multilayer nanowires are lower than those of others multilayer nanowires. These are compatible with the required conditions of high density magnetic media devices that should have the low coercivity to easily success magnetization and high remanence to keep magnetization after removal of magnetic field.     

SEQUENTIAL LOOP CLOSING IDENTIFICATION OF MULTIVARIABLE PROCESSES USING THE BIASED RELAY FEEDBACK METHOD

Each controller in multiloop control systems for multivariable processes can be tuned sequentially with the ultimate information for the paired input and output while former loops have been closed, and hence, single-input single-output autotuning methods can be applied. In this sequential autotuning for multiloop control systems, several iterations are usually required for better control performances. Especially when pairings are undesirable, the autotuning sequences should be repeated with correct pairings, which result in long field experiments. Here, to avoid this drawback, a simple method to identify process models while loops are being sequentially tuned is proposed. The identified models can be used to correct pairings of multiloop control systems and to improve tuning performances without several field iterations. In addition, they can be used to obtain model-based control systems such as decoupling control systems.     

Highly ordered monolayer formation of silica beads assisted by ultra-sound and microscopic barrier at air/water interface

We fabricated closely packed monolayer of hydrophobically modified non-porous silica (NPS) beads at air/water interface. Hydrophilic silica beads were modified by hydrocarbon that render hydrophobic on their surface. Ultra-sound applied to the water subphase, inducing large scaled two-dimensional ordering of the beads by reducing three-dimensional irregular cluster formations while spreading solvent evaporated. Furthermore, surface pressure generated by polymeric surface micelle effectively pushes the silica beads and reduces voids between the 2D silica clusters.     

Prediction of deformations of steel plate by artificial neural network in forming process with induction heating

To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses on the plate to obtain deformations during the heating process are then performed with a commercial FEM program for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs. The predicted outputs from the neural network are compared with those of the experiments and the numerical results. They are in good agreement. This paper was recommended for publication in revised form by Associate Editor Youngseog Lee Truong-Thinh Nguyen received the B.S and M.S degrees from Ho Chi Minh city National University, Viet Nam, in 1997 and 2000, respectively. Now, he is a doctoral candidate in the Department of Mechanical Engineering at Chonnam National University, Korea. His research interests are Induction Heating, Thermal deformations, applications of Neural Network and Fuzzy logic in Industry, intelligent control. Young-Soo Yang received a B.S. degree in Mechanical Engineering from Sungkyunkwan University in 1985. He then went on to receive his M.S. and Ph.D. degrees from KAIST in 1987 and 1991, respectively. Dr. Yang is currently a Professor at the School of Mechanical Engineering at Chonnam National University in Gwangju, Korea. He research interests are in the area of weld structure. Kang-Yul Bae is a Professor of Mechatronics Engineering Department at Jinju National University in Jinju, Korea. He received a B.S. degree in Mechanical Engineering from Busan National University in 1984. He also holds the following degrees of M.S. in Production Engineering and Ph.D. in Mechanical Engineering from KAIST in 1986 and 1994, respectively. He has industrial experience from 1986 to 1998 at Hyundai Heavy Industries, Co. Ltd. as a senior researcher. His teaching and research areas include manufacturing processes, automation, and mechatronics. Sung-Nam Choi received a B.S. and a M.S. degree in Department of Mechanical Engineering from Chonnam National University in 1989 and 1991. He then complete doctor course from the same University in 2006. He is currently a Senior Researcher at Non-Destructive Evaluation Center at Korea Electric Power Research Institute in Daejon, Korea. His research interests are in the area of weld integrity, fracture mechanics, and automated ultrasonic examination.