Murat O. Balaban

Physicochemical and Phytochemical Properties of Cold and Hot Water Extraction from Hibiscus sabdariffa

UNLABELLED Hibiscus cold (25 °C) and hot (90 °C) water extracts were prepared in various time-temperature combinations to determine equivalent extraction conditions regarding their physicochemical and phytochemical properties. Equivalent anthocyanins concentration was obtained at 25 °C for 240 min and 90 °C for 16 min. Total phenolics were better extracted with hot water that also resulted in a higher antioxidant capacity in these extracts. Similar polyphenolic profiles were observed between fresh and dried hibiscus extracts. Hibiscus acid and 2 derivatives were found in all extracts. Hydroxybenzoic acids, caffeoylquinic acids, flavonols, and anthocyanins constituted the polyphenolic compounds identified in hibiscus extracts. Two major anthocyanins were found in both cold and hot extracts: delphynidin-3-sambubioside and cyanidin-3-sambubioside. In general, both cold and hot extractions yielded similar phytochemical properties; however, under cold extraction, color degradation was significantly lower and extraction times were 15-fold longer. PRACTICAL APPLICATION Hibiscus beverages are prepared from fresh or dried calyces by a hot extraction and pasteurized, which can change organoleptic, nutritional, and color attributes. Nonthermal technologies such as dense phase carbon dioxide may maintain their fresh-like color, flavor, and nutrients. This research compares the physicochemical and phytochemical changes resulting from a cold and hot extraction of fresh and dried hibiscus calyces and adds to the knowledge of work done on color, quality attributes, and antioxidant capacity of unique tropical products. In addition, the research shows how these changes could lead to alternative nonthermal processes for hibiscus.

Effects of Dense Phase Carbon Dioxide Pasteurization on the Physical and Quality Attributes of a Red Grapefruit Juice

Red grapefruit juice was treated with continuous dense phase carbon dioxide (DPCD) equipment to inactivate yeasts and molds and total aerobic microorganisms. A central composite design was used with pressure (13.8, 24.1, and 34.5 MPa) and residence time (5, 7, and 9 min) as variables at constant temperature (40 degrees C), and CO(2) level (5.7%) after experimentally measuring CO(2) solubility in the juice. Five log reduction for yeasts and molds and total aerobic microorganisms occurred at 34.5 MPa and 7 min of treatment. A storage study was performed on the fresh juice DPCD treated at these conditions. degrees Brix, pH, titratable acidity (TA), pectinesterase (PE) inactivation, cloud, color, hue tint and color density, total phenolics, antioxidant capacity, and ascorbic acid were measured after the treatment and during 6 wk storage at 4 degrees C. During storage, the DPCD-treated juice showed no growth of total aerobic microorganisms and yeasts and molds. Cloud increased (91%) while percent PE inactivation was partial (69.17%). No significant (alpha= 0.05) differences were detected between treated and untreated samples for degrees Brix, pH, and TA. Treated juice had higher lightness and redness and lower yellowness. No significant differences (alpha= 0.05) were detected for the hue tint values while the color density value was higher for the treated samples compared to the untreated. The treatment and the storage did not affect the total phenolic content of the juice. Slight differences were detected for the ascorbic acid content and the antioxidant capacity. The experimental results showed evidence that the treatment can maintain the physical and quality attributes of the juice, extending its shelf life and safety.

Transportability of data between electronic noses: mathematical methods

Abstract Accumulation of databases containing volatile attributes of foods measured by electronic noses requires transportability of data between machines. Due to differences in each machine, or sensor drift, the same sample may result in slightly different readings. Three functions (coefficient, F1; coefficient with intercept, F2; matrix, F3) and two neural network configurations (NN1, NN2) were tried to assess their suitability for acceptable transformation. Two EEV electronic noses with identical sensors were used to read milk samples stored for up to 12 days. Six replicate readings were separated to ‘calibration’ (four replicates) and ‘unknown’ (two replicates) sets. Discriminant function analysis was applied to evaluate ‘unknowns’ in ‘calibration’ sets. When ‘old unknowns’ were converted and classified in ‘new calibrations’, correct classification rates (CCR) were 2/12, 3/12 and 7/12 for F1, F2 and F3, respectively. Also, neural networks were used to either transform one ‘calibration’ set to another (CCR=8/12 and 9/12), or to evaluate the ‘unknown’ sets in the ‘calibration’ sets (CCR=7/12). More research is needed in this area.

Enabling the utilization of wool as an enzyme support: Enhancing the activity and stability of lipase immobilized onto woolen cloth

An improved, simple, effective and superior protocol has been developed to immobilize amano lipase from Pseudomonas fluorescens on woolen cloth using polyethyleneimine (PEI) with glutaraldehyde (GA) cross-linking. The success of immobilization was confirmed by FTIR and confocal laser scanning microscope (CLSM), the latter proving that enzyme is well distributed across the wool fiber surfaces throughout the cloth. Woolen cloth therefore provides a large outer and inner fiber surface area for immobilization with minimal mass transfer resistances during immobilization. The optimal protocol (GA at 0.5% and pH 6, lipase solution pH 6) gave an enzyme load of 46.6 mg g(-1)dry cloth with expressed activity of 178.3 U, 46.8% immobilization yield and 30.2% retained activity. Zeta potential measurements showed that PEI significantly enhanced the positive charge on woolen cloth and shifted the isoelectric point to approximately 7. Therefore at a lipase solution pH of around 6, the wool-PEI and lipase are oppositely charged, leading to a maximal adsorption of lipase to the wool surface. The immobilized lipase also had a good stability and 81% of its original activity was maintained after 10 runs in tributyrin emulsion hydrolysis. This protocol provides a significant improvement in terms of retained activity and lipase stability compared to previous immobilizations on wool and opens up the possibility of using wool as a cheap and effective lipase support material for continuous lipase reactions/reactors and possibly enzyme enhanced woolen fabrics.

Astaxanthin Extraction from Crawfish Shells by Supercritical CO2 with Ethanol as Cosolvent

Abstract Astaxanthin is an important pigment in fish and shellfish aquaculture and increases the market value of fish such as salmon and trout. Commercially synthesized astaxanthin costs about

Prediction of the Weight of Alaskan Pollock Using Image Analysis

1,000/kg. Carotenoids have been extracted from crustacean wastes with organic solvents, but in many of the methods the pigments are degraded. Astaxanthin extraction yield from crawfish tail shells by supercritical CO2 was optimized for temperature, pressure, and moisture. The cosolvent ethanol (10% w) increased yield significantly. Temperature, pressure, and moisture content were other important independent variables. These were studied using an incomplete 33factorial (Box-Behnken) design. The equation of the model fitted to the data was extracted astaxanthin (mg/kg dry shell) = -169.3 + 5.36 T + 0.061 P + 7.32 M -0.0003 T P -0.10 T M + 0.0003 M P -0.02 T2 -0.000006 P2 -0.033M2, where T = temperature; P = pressure (psi); M = moisture. The maxima for moisture, pressure, and temperature were 13, 24 MPa, and 75, respectively.

Analysis of Skin Color Development in Live Goldfish Using a Color Machine Vision System

Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A · X(B)) gave the highest R(2) for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. Practical Application: The weight of Alaskan Pollock can be predicted automatically by taking the image of the fish and using it in one of the correlations developed in this study. The removal of the fins or the fins and the tail did not increase the prediction accuracy of the method. Therefore, intact fish images should be used.

Prediction of the Weight of Aquacultured Rainbow Trout (Oncorhynchus mykiss) by Image Analysis

Abstract A color machine vision system (CMVS) was used to measure and quantify color development in the skin of live goldfish Carassius auratus raised in pond or well water and fed rations of different commercial feeds. Goldfish were of the ornamental Red Oranda variety, 3 months of age, 0.15 ± 0.01 g (mean ± SD) in body weight and 1.38 ± 0.22 cm in total length. Data on color development were acquired through a charge-coupled display color video camera and an image capture card attached to a personal laptop computer. We used a color analysis program developed at the University of Florida, Department of Food Science and Human Nutrition, to interpret the skin color patterns. Pixels from the computerized image were compared and matched to one of 64 color blocks (standards) representing the entire color spectrum. Pixel groupings were represented and recorded as a frequency (percentage) of occurrence for each color standard. The CMVS provided an objective method for measuring the skin color of goldfish and al...

Modeling of heat conduction in elliptical cross section : II. Adaptation to thermal processing of shrimp

Prediction relationships between weight and image features were established with a high correlation for whole aquacultured rainbow trout. Three hundred fish from three different farms were used. The fish were temporarily removed from the raceway, anesthetized, and their picture was taken by a digital camera. A reference square of known surface area and color was placed beside the fish. The fish were then returned to the raceway alive. The image was analyzed, and the view area of the fish was calculated using the area of the reference square. The average color of the fish was also determined (L*, a*, and b* values). The following equations were used to fit the view area (X) vs. weight (Y) data: linear, power, and second order polynomial. The R2 values for the used equations were: linear = 0.98; power = 0.99; polynomial = 0.98. Image analysis can be used reliably to predict the weight of whole aquacultured rainbow trout. In addition, color and other visual attributes can be objectively determined by image analysis to sort by visual quality.

Carbon monoxide treatments to impart and retain muscle color in tilapia fillets.

The quality of processed shrimp is partly determined by microbiological and textural attributes, and yield loss is economically important. Temperature is the most important variable that affects the above. A mathematical model was developed for the prediction of temperature distribution during cooking of shrimp. To develop the model, experimental cross-sectional areas of shrimp at different segments were compared with circular and elliptical cross-sectional area assumptions, and the circular cross-sectional area assumption was found to be a valid assumption for the model for its simplicity. The model used a finite difference approach with non-capacitance surface nodes (NCSN), and assumed variable thermal conductivity, specific heat, density, as well as changes in dimensions due to shrinkage. The mathematical model accurately predicted the temperature distribution in shrimp.