Quality enhancement of the abundant under‐valued crustacean,lobster krill (Munida spp.), during its chilled storage

Lobster krill (Munida genus) represents an under‐valued crustacean frequently caught on European fishing banks. In this work, its sensory, microbiological and biochemical qualities were evaluated during chilled storage. Additionally, the effects of a prestorage antimelanosic treatment consisting of soaking in sodium metabisulphite (SMB) solutions at two different concentrations (0.25% and 0.75%) were also studied. SMB prestorage treatment provided lobster specimens that still exhibited acceptable sensory quality after 10 days of storage, while control specimens were unacceptable at that time. SMB treatment also resulted in a significant (P < 0.05) inhibition of microbial growth, mainly of Enterobacteriaceae, psychrotrophes and proteolytic bacteria. Low lipid oxidation levels were observed for all batches; however, a significantly higher (P < 0.05) retention of polyunsaturated fatty acids was found in SMB‐treated lobster, especially in the 0.75% SMB batch. The results presented here open the way to the potential commercialisation of currently under‐utilised lobster krill as a chilled product.     

Relationship Between the Thermodynamic Parameters,Structure, and Anticorrosion Properties of Al-Zr-Ni-Fe-Y Alloys

Metallurgical and Materials Transactions A - The influence of the chemical composition on the crystallization process, amorphous phase formation, and the anticorrosion properties of Al-Zr-Ni-Fe-Y...     

Multilevel Recording in Ge2Sb2Te5 Thin Films

Semiconductors - The current–voltage characteristics measured on Ge2Sb2Te5 thin films in the current mode are studied. The effect of multilevel recording is established when applying...     

Plasmon Resonances in Square and Rectangular Noble Metal Nanoplates

Journal of Communications Technology and Electronics - Abstract—The article considers the two-dimensional diffraction problem of a TM-type plane electromagnetic wave on a cylindrical silver...     

Effect of Railcar Wheel Tire Profiles on the Contact Stress Level in Subway Rails

Strength of Materials - The statistical analysis performed on the defectiveness of rails in the Kiev subway railway shows that the main cause of the occurrence of most defects is the contact...     

Effect of the Porous Skeletal Iron Structure on the Infiltration of Aluminum Melts

Powder Metallurgy and Metal Ceramics - The infiltration of aluminum melts into porous metal skeletons produced by powder metallurgy methods, including 3D printing, under a pressure gradient was...     

A Method of Transferring the Unit of Power of High-Intensity Laser Radiation

Measurement Techniques - A method is proposed for transferring the unit of mean power of laser radiation by means of measuring high-intensity power (kilowatts), with the possibility of constant...     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.