Estimation of the growth curve parameters in Macrobrachium rosenbergii

Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideration

The von Bertalanffy growth curve: when a good fit is not good enough

The von Bertalanffy growth function is used for length based analysis of growth and mortality patterns for management of fisheries. However, certain fish have growth patterns that the VBGF may not be able to describe adequately.e.g. the Acanthurus lineatus in Samoa. In such cases a two phase VBGF may be a useful approach.

Estimating the girth of fish by applying an elliptic model

A new method for estimating the maximum girth of roundfish is proposed as illustrated; this is based on an elliptic approximation of the cross sections of the fish body. Results derived from a small sample horse mackerel, Trachurus trachurus, suggest that maximum girth estimates based on the elliptic model are more precise than the values estimated by applying a conventional method.

High-resolution computation of isotopic processes in northern California using a local climate model

EXTRACT (SEE PDF FOR FULL ABSTRACT): We describe a coupled local climate/isotope model that can calculate Rayleigh-type processes of distillation and fractionation of hydrogen isotopes along individual air mass flowlines in the western United States.This climate model is an extension of that detailed earlier by Craig and Stamm (1990). ... Volumetric effects of evapotranspiration (ET) are included. The model allows sensitivity studies of the influence of ET recycling.

A note on application of hills procedure for growth-curve analysis of Indian major carp, Labeo rohita (Ham.), during the gonodal development period at Shillong, Meghalaya

The present study deals with the length increment data of 15 adult Labeo rohita (Ham.) over a period of five months by the applicatin of finite difference method at an altitude of 1496 m above mean sea level at Shilllong, Meghalaya.