P. Mayer - Academia.edu (original) (raw)
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Papers by P. Mayer
Aquaculture Research, 2008
ABSTRACT The growth of gilthead sea bream (Sparus aurata) has been studied considering five multi... more ABSTRACT The growth of gilthead sea bream (Sparus aurata) has been studied considering five multiple exponential regression models using data from 20 lots of gilthead sea bream growing in 20 marine cages from a Mediterranean commercial fish farm. The final weight (Wf) of fish was predicted in relation to the initial weight (Wi), time (n) and temperature (T), or the sum of effective temperatures (∑Tef). The estimated weight results from the simulation using the five models have been compared with the real final weight values using the mean of the absolute values of the prediction errors in short and long term (the precision value). All models presented a high determination coefficient, above 96%, and good prediction values in the short term. Regression models were tested using data from six new cages. The best models for predicting the growth of sea bream long term were the ones where final weight is expressed in relation to the initial weight and the sum of effective temperature, and obtaining long-term prediction errors 12.9% and 10.7% respectively.
Aquaculture, 2012
ABSTRACT Several authors have proposed models to describe fish growth taking the influence of tem... more ABSTRACT Several authors have proposed models to describe fish growth taking the influence of temperature into account, and one of the most interesting is the “thermal unit growth coefficient” (TGC). Recent research has demonstrated that TGC varies throughout the growth cycle of fish, making it necessary to establish different stanzas. In this work, the original TGC model using 1/3 as an exponent was compared with a new model considering 2/3. Likewise, two stages for the growth of gilthead sea bream under commercial conditions in marine farms were detected by means of TGC seasonal models using the continuous temperature curve. A critical value for weight around 117 g was obtained, which could mark the transition between two growth dynamics. To describe the weight evolution during a complete production cycle, the two growth stages were described by two separate seasonal TGC models (1/3-TGC model and 2/3-TGC model), and with an integrated model named the Mixed-TGC model, which presents interesting properties
Aquaculture, 2009
Most mathematical models of fish growth on commercial farms use the evolution of average weight d... more Most mathematical models of fish growth on commercial farms use the evolution of average weight during the growth period, without considering weight distribution. In this paper, quantile regression techniques were used to describe the evolution of weight distribution in 20 batches of gilthead sea bream (Sparus aurata) growing on a commercial fish farm in the Spanish Mediterranean. Different Thermal-unit Growth
Aquaculture Research, 2008
ABSTRACT The growth of gilthead sea bream (Sparus aurata) has been studied considering five multi... more ABSTRACT The growth of gilthead sea bream (Sparus aurata) has been studied considering five multiple exponential regression models using data from 20 lots of gilthead sea bream growing in 20 marine cages from a Mediterranean commercial fish farm. The final weight (Wf) of fish was predicted in relation to the initial weight (Wi), time (n) and temperature (T), or the sum of effective temperatures (∑Tef). The estimated weight results from the simulation using the five models have been compared with the real final weight values using the mean of the absolute values of the prediction errors in short and long term (the precision value). All models presented a high determination coefficient, above 96%, and good prediction values in the short term. Regression models were tested using data from six new cages. The best models for predicting the growth of sea bream long term were the ones where final weight is expressed in relation to the initial weight and the sum of effective temperature, and obtaining long-term prediction errors 12.9% and 10.7% respectively.
Aquaculture, 2012
ABSTRACT Several authors have proposed models to describe fish growth taking the influence of tem... more ABSTRACT Several authors have proposed models to describe fish growth taking the influence of temperature into account, and one of the most interesting is the “thermal unit growth coefficient” (TGC). Recent research has demonstrated that TGC varies throughout the growth cycle of fish, making it necessary to establish different stanzas. In this work, the original TGC model using 1/3 as an exponent was compared with a new model considering 2/3. Likewise, two stages for the growth of gilthead sea bream under commercial conditions in marine farms were detected by means of TGC seasonal models using the continuous temperature curve. A critical value for weight around 117 g was obtained, which could mark the transition between two growth dynamics. To describe the weight evolution during a complete production cycle, the two growth stages were described by two separate seasonal TGC models (1/3-TGC model and 2/3-TGC model), and with an integrated model named the Mixed-TGC model, which presents interesting properties
Aquaculture, 2009
Most mathematical models of fish growth on commercial farms use the evolution of average weight d... more Most mathematical models of fish growth on commercial farms use the evolution of average weight during the growth period, without considering weight distribution. In this paper, quantile regression techniques were used to describe the evolution of weight distribution in 20 batches of gilthead sea bream (Sparus aurata) growing on a commercial fish farm in the Spanish Mediterranean. Different Thermal-unit Growth