Influence of Alevinage Time in the Optimization of Tambaqui Biomass Production in Semi-Intensive Fish Farming in the Northern Region of Amazonas

Abstract

Objective: To evaluate the weight mix for the market obtained with variation in the pre-fixed fingerlings time, for the cultivation of tambaqui (Colossoma macropomum) in a semi-dug tank. Theoretical framework: The parameters evaluated regarding resources are, the tanks, each of which has its own capacity, its own state variable, which includes fish biomass, growth function and mortality rate. And identifying potential alternatives and making better decisions that optimize biomass production are important, but that take into account the reduction of its environmental impact. Method: The model incorporates two types of input variables. The discrete event variable, which comprises the number of fish in each batch, the number of tanks available, the time between the arrival of fingerlings in the system and the frequency of classification by weight for the market. The second refers to the continuous time variable, involving the weight of the fish, dissolved oxygen (DO) available to the fish, and feed consumption. Results and conclusions: The analysis showed that the decision variables are the quantities of fish, with the premise of final weight of 0.5 kg, 1 kg and 2 kg which are related to the hatching time pre-fixed at entry as “30, 40, 50, 60, 70, 80, 90, 100 days” in phase I, results in the optimization of production, target weight for the market as a function of time, in layout scenarios of 5 and 10 tanks, with the premise of harvesting in both, with Mix weight with 0.5kg, 1kg and 0.5kg, 1kg, 2kg to maximize net profit. Considering that the transition between growth phases is a stochastic process, which satisfies the Markov property. It was possible to define the balance between the input and output of the system. Research implications: The study is of great relevance, as it describes a sequential queue through the growth phases in relation to time, capable of determining the optimization of production with weight mix to maximize net profit. Originality/value: The research reveals that it is possible to use queuing theory analyzes in stochastic processes, evaluating the transition between time phases, which satisfies the Markov property.