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Raul Perez Gallardo

CIMAT



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Ignacio Mendez Gomez-Humaran

CIMAT



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Rafael C. Perez-Abreu

CIMAT



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421 – Contributed Poster Presentations: Quality and Productivity Section

Prediction of Shrimp Size Distribution Reared Inside Submersible Sea Cages

Sponsor: Quality and Productivity Section
Keywords: Shrimp, No-Normal Regression, Extreme Value, Sea Cages, Models, Shrimp

Raul Perez Gallardo

CIMAT

Ignacio Mendez Gomez-Humaran

CIMAT

Rafael C. Perez-Abreu

CIMAT

We developed a non-normal regression model to characterize the growth of shrimp and the shrimp‘s weight distributions throughout the fattening process. The experiment was conducted in the Baja California Gulf in 2010 where shrimp producers built submersible sea cages to breed shrimp. During the fattening process, producers took samples and performed biometric analyses in order to observe characteristics of the shrimp in the growth process. We analyzed the information from the samples using several distributions of probability to study the behavior of shrimp growth. To find the best mathematical model to characterize this behavior, we applied techniques that are used in reliability engineering and data lifetime studies.

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