Smart packaging: sensors for monitoring of food quality and safety

The development of chemical sensors and biosensors over several decades has been investigated resulting in novel and very interesting sensor devices with great promise for many areas of applications including food technology. The incorporation of such sensors into the food packaging technology has resulted what we call smart or intelligent packaging. These are truly integrated and interdisciplinary systems that invoke expertise from the fields of chemistry, biochemistry, physics and electronics as well as food science and technology. Smart packaging utilises chemical sensor or biosensor to monitor the quality & safety of food from the producers to the costumers. This technology can result in a variety of sensor designs that are suitable for monitoring of food quality and safety, such as freshness, pathogens, leakage, carbon dioxide, oxygen, pH, time or temperature. Thus, this technology is needed as on-line quality control and safety in term of consumers, authorities and food producers, and has great potential in the development of new sensing systems integrated in the food packaging, which are beyond the existing conventional technologies, like control of weight, volume, colour and appearance.     

Influence of Eriophyid mites (Aculus olearius Castagnoli and Aceria oleae (Nalepa) (Acarina: Eriophyidae)) on some physical and chemical characteristics of Ayvalık variety olive fruit

BACKGROUND: Aculus olearius Castagnoli is a recently recorded species that damages olive fruits in the Mediterranean basin of Turkey. Thus, the effects of Eriophyid mites (Aculus olearius Castagnoli and Aceria oleae (Nalepa) (Acarina: Eriophyidae) on the olive fruits from Ayval?k variety in southern Turkey were studied for the first time in terms of some physical parameters and chemical constituents including some individual phenolics. RESULTS: The Eriophyid damaged fruits had higher L* values (lighter colour) and tyrosol level (37.53 mg kg^?1) than the undamaged fruits (28.51 mg kg^?1) in August. In contrast, Eriophyid damaged fruits were darker in colour and had lower levels (25.77 mg kg^?1) of tyrosol than those of undamaged fruits (79.14 mg kg^?1) in October. Eriophyid damaged samples had higher values of vanillic acid than the undamaged samples. An increase in the average concentrations of hydroxytyrosol and p‐coumaric acid was observed in the fruits harvested in August, whilst the oleuropein content decreased. CONCLUSION: The harvest in October can be recommended regarding the higher dimensional values, total oil, dry matter and oleuropein contents. But the interaction between harvest time and Eriophyid damage was found effective in terms of tyrosol content and skin colour; as tyrosol values were lower in the fruits harvested in October and the fruits were darker. The resistance of undamaged fruits against Eriophyid damage can be linked to high tyrosol content of these fruits. Copyright © 2010 Society of Chemical Industry     

Sensitivity Analysis on Neural Network Algorithm for Primary Superheater Spray Modeling

ABSTRACT

Nonlinear, large inertia with long dead time is always associated with the main steam temperature parameter in coal fired power plant. Successful control of the main steam temperature within ±2°C of its setpoint is the ultimate target for coal-fired power plant operators. Two of the most common main steam temperature circuit are primary superheater spray and secondary superheater spray. Various methods were used to model the primary superheater spray control valve opening, and the neural network remains one of the most popular choices among researchers. It remains inconclusive which neural network algorithm types, setup, number of layers, and training algorithm will give the best result. As such, the paper shows the best setup for the neural network algorithm based on sensitivity analysis methodology for one hidden layer. The inputs selected for the neural network are generator output, main steam flow, total spray flow, and secondary superheater outlet steam temperature, while the output selected is primary spray flow control valve opening.     

The effect of magnetic and optic field in water electrolysis

Hydrogen production via water electrolysis was studied under the effect of magnetic and optical field. A diode solid state laser at blue, green and red were utilized as optical field source. Magnetic bar was employed as external magnetic field. The green laser has shown a greatest effect in hydrogen production due to its non-absorbance properties in the water. Thus its intensity of electrical field is high enough to dissociation of hydronium and hydroxide ions during orientation toward polarization of water. The potential to break the autoprotolysis and generate the auto-ionization is the mechanism of optical field to reveal the hydrogen production in water electrolysis. The magnetic field effect is more dominant to enhance the hydrogen production. The diamagnetic property of water has repelled the present of magnetic in water. Consequently the water splitting occurs due to the repulsive force induced by the external magnetic field. The magnetic distributed more homogenous in the water to involve more density of water molecule. As a result hydrogen production due to magnetic field is higher in comparison to optical field. However the combination both fields have generated superior effect whereby the hydrogen yields nine times higher in comparison to conventional water electrolysis.     

Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework

Sustainability has become a necessity, partly due to the threats created by traditional manufacturing practices, and due to regulations imposed by stakeholders. Performance evaluation is an important component of sustainability initiatives in manufacturing organizations. This study proposes a sustainability evaluation method for manufacturing SMEs using integrated fuzzy analytical hierarchal process (FAHP) and fuzzy inference system (FIS) approach. The performance indicators are identified from literature considering the characteristics of SMEs. Balanced scorecard framework is used to categorize the indicators among its four aspects. The linguistic variables are used to collect the opinions of decision makers about the performance ratings and importance of the aspects and corresponding indicators. The FAHP method is applied to determine the relative weights of measures and indicators. The performance ratings of the organization with respect to indicators and relative weights of indicators are combined to obtain the weighted performance ratings. The weighted performance ratings are considered as inputs to FIS. The hierarchal FIS is applied to derive the overall sustainability performance. Using a case study of manufacturing SME, the sustainability score of the organization was elicited in accordance with this procedure. Consequently, a sensitivity analysis of the proposed method reveals the most important basic indicators affecting overall sustainability, identifying areas which decision makers should place special attention. This method can also assist managers of larger enterprises to assess the effectiveness of their sustainability strategies, especially when dealing with suppliers from the SMEs.