Effect Of Raw Material Quality On The Shelf Life Of Frozen Stored Fish And Fishery Products

Frozen storage characteristics and shelflife vary considerably among species as well as within the species (Powrie, 1973; Fennema. 1973). This can be attributed to the variation in the composition of fish among various species. In certain species like sardines and mackerel. wide seasonal variation in chemical composition occur within the species. These variations affect the quality and shelflife. The nutritional level of water. spawning, method of catching, struggling etc. are found to have profound influence on the condition of the fresh fish. Soon after death the deteriorative changes in fish start due to autolysis and bacterial growth. The rate of these changes depends mainly on temperature. The handling methods have great influence on bacterial contamination. Thus the type oi'handling. temperature control. period of chill storage. processing methods. type of freezing, condition of frozen storage and period of storage affect the quality and shelflife Of the fisho In the present study extensive investigations were carried out on various factors affecting the quality of fish as well as their effect on the physical. chemical and sensory qualities of fish during frozen storage and the shelflife

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.