Veränderungen sensorischer und instrumenteller Parameter während der Gefrierlagerung von Ostseedorsch (Gadus morhua) bei unterschiedlichen Temperaturen

Changes in sensory and instrumental quality parameter sand in thawing drip, cooking drip and total drip loss of frozen stored Baltic cod fillets (Gadus morhua) at different storage temperatures were investigated. Cod fillets stored at –20 °C and –30 °C exhibited the lowest drip losses and obtained the highest sensory scores. Drip losses were found to be highest in cod fillets stored at –10°C and in double frozen fillets stored at –20 °C. These two experiments also gave the lowest sensory scores. The texture parameters increased during storage parallel with storage time. The waterbinding capacity was lowest at –10 °C and almost constant at –30 °C. There is a good correlation between the sensory scores for “tough” and the instrumental texture measurement for hardness and chewiness.

Determination and modelling of water quality parameter in Abuja metropolis

This research work involves the determination and modelling of water parameter such as pH, temperature, turbidity, chloride, hardness. The result of the analysis was used as important operating variables to generate a model equation of pH, hardness, temperature, turbidity and chloride. The values obtained from the model equation were compared with those from experiment. On an average bases the values were close. These parameters can be used to monitor the extent of pollution of pond water and to monitor stress and diseases of fish. The experimental data of pH was in the range of 6.7 to 6.9 while the modelled result was also between 6.7 to 7.0. The turbidity experimental value was close to the modelled value also. The chloride value for the experimental data was in the range of 25.32 to 35.0. The total hardness value ranges between 4.5 to 65.1 mg/l while the modelled result ranges between 11.025 to 68.402 mg/l. The result was within the acceptable limit of world health organization standard on water quality parameter.

Reference-growth rate – a simple and handy parameter summarizing the influence of environmental conditions

Abstract Environmental changes may have an impact on life conditions of the fish, e.g. food supply for the fish. The prevailing environmental conditions apply evenly to all age groups of one stock. Small fish have high growth rates, whereas large fish grow with low rates. But, it can be shown on the basis of the von Bertalanffy-growth model that it is sufficient to know only the growth rate of one single age group to compute the growth rates of all other age groups. The growth rate of a reference fish GRF (e.g. a fish with a body mass of 1 kg) was introduced as a reference growth describing the current food condition of all age groups of the stock. As an example a time series of the reference-growth rate of the northern cod stock (NAFO, 3K) was computed for the time span 1979 to 1999. For the northern cod stock it can be observed that environmental conditions caused growth rates below the long-term mean for seven years in a row. After a prolonged hunger period the fish stock collapsed in 1992 also by the impact of fisheries - and this was probably not a coincidence. Now, with the reference-growth rate GRF a simple and handy parameter was found to summarize the influence of the environmental conditions on growth and other derived models and therefore makes it easier to compute the influence of environmental changes within stock assessment. Zusammenfassung Veränderungen der Umwelt können Auswirkungen auf die Lebensbedingungen der Fische haben, z. B. auf das Nahrungsangebot der Fische. Die vorherrschenden Umgebungsbedingungen wirken gleichmäßig auf alle Altersgruppen eines Bestandes, wobei typischer Weise kleineFische hohe Wachstumsraten haben, während die großen Fische mit niedrigen Raten wachsen. Auf der Grundlage des von Bertalanffy-Wachstumsmodells kann gezeigt werden, dass es ausreicht, nur die Wachstumsrate von einer einzigen Altersgruppe zu kennen, um die Wachstumsraten von allen anderen Altersgruppen berechnen zu können. Die Wachstumsrate eines Referenz-Fisches (z.B. eines Fisches mit einer Körpermasse von 1 kg) wurde als Referenz-Wachstum GRF eingeführt, die den aktuellen Zustand des Nahrungsangebots füralle Altersgruppen des Bestandes beschreibt. Als Beispiel wurde einer Zeitreihe der Referenz-Wachstumsraten des nördlichen Kabeljaubestandes (NAFO, 3K) für die Zeitsraum 1979 bis 1999 berechnet. Für diesen Kabeljaubestand war zu beobachten, dass Umgebungsbedingungen für sieben Jahre in Folge Wachstumsraten unter dem langjährigen Mittelwert verursachten. Nach einer längeren Hungerperiode kollabierte dieser Fischbestand im Jahr 1992 auch durch den Einfluß der Fischerei - und dies war sicher kein Zufall. Jetzt, mit der Referenz-Wachstumsrate GRF, ist ein einfacher und handlicher Parameter gefunden, der es gestattet den Einfluss der Umweltbedingungen auf die Wachstumsbedingungen und andere davon abgeleitete Modelle zusammenzufassen. Dies macht es einfach, den Einfluss von Umweltveränderungen innerhalb der Bestandsabschätzungen zu berechnen.

Parameter estimates for fishes of the upper Paraná river floodplain and Itaipu reservoir (Brazil)

Estimates of the growth (K), natural mortality (M), consumption/biomass (Q/B) rate and trophic level (TL) for 35 species in the upper Paraná river floodplain and the Itaipu reservoir (interconnected ecosystems) are presented. A compilation of these biological statistics is made for comparison purposes and some general trends are briefly discussed.

On Malthusian overfishing

A brief examination is made of Malthus' works during the 1800s regarding population growth, considering applications to fisheries resources and their management.

Improving Shepherd's Length Composition Analysis (SLCA) method for growth parameter estimations

Shepherd's "weekly parametric" method for estimating the parameter L sub( infinity ) and K of the von Bertalanffy growth function from length-frequency data often fails to converge, and usually overestimates K. It is shown that this is due to overcounting of the frequencies associated with large, slow growing fish, and that both of these problems can be completely overcome by a simple change in the way the scoring function is formulated.