Stock model and multivariate analysis for prediction of semi-intensive production of shrimp Litopenaeus vannamei as a function of water quality and management variables: A stochastic approach

Ruiz-Velazco, Javier M.J.; Estrada-Pérez, Margarita; Hernández‐Llamas, Alfredo; Nieto-Navarro, José T.; Peña-Messina, Emilio

doi:10.1016/j.aquaeng.2013.04.003

Cited by 11 publications

(17 citation statements)

References 20 publications

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“…Moreover, our equations are in general agreement with reports by other authors regarding the correlations between growth and survival parameters and water quality and management variables. Sadeh, Pardy, Griffin and Lawrence () and Ruiz‐Velazco, Estrada‐Pérez, Hernández‐Llamas, Nieto‐Navarro and Peña‐Messina () reported an adverse effect of stocking density on shrimp. In our study, we used correlation and regression analysis to determine the factors potentially affecting the final weight and survival of shrimp and found that stocking density was the only factor significantly influencing them.…”

Section: Discussionmentioning

confidence: 96%

Assessing uncertainty of semi-intensive production of whiteleg shrimp (Litopenaeus vannamei) using partial harvesting programs

et al. 2017

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We used stochastic models for analysis of the uncertainty involved in semi-intensive production of shrimp in Nayarit state, Mexico, incorporating partial harvests.Analysis of the database showed that increasing the number of harvests was associated with lower stocking densities, the use of larger ponds, longer cultivation periods, larger final weight of shrimp and total production. Equivalence tests showed that the models adequately fitted the primary data. Monte Carlo simulations indicated that improving management by controlling stocking density and the duration of cultivation increased mean production from 981 to 2573 kg/ha (one partial harvest), from 1808 to 3602 kg/ha (two partial harvests) and from 1364 to 3834 kg/ha (three partial harvests), closely approaching the yields reported in the database. When conducting one and three partial harvests, improved management increased production and the certainty in obtaining the crops, as indicated by diminishing values of the coefficient of variation in output probability distributions.When conducting two partial harvests, however, improved management increased yields, but also increased uncertainty because there was a lower control on production parameters. This does not necessarily imply more uncertainty when conducting two harvests, but that at this stage of knowledge, the primary data only allows detecting limited control on production. Results of a preliminary economic evaluation showed that net revenues ranged from USD$ 2361.1-3488.9, the benefit-cost ratio from 1.47 to 1.62 and that the best and worse results were obtained by conducting two and one partial harvests. We conclude that the models are useful for analysing uncertainty of semi-intensive shrimp production incorporating partial harvesting.

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Section: Discussionmentioning

confidence: 96%

Assessing uncertainty of semi-intensive production of whiteleg shrimp (Litopenaeus vannamei) using partial harvesting programs

et al. 2017

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“…In a previous study (Ruiz-Velazco et al, 2013), we developed and presented the stock model together with the relationships between its parameters and water quality and management variables. The corresponding equations are presented in Table 1.…”

Section: Stock Model and Feed Conversion Ratio Modelmentioning

confidence: 99%

“…Farmed shrimp in Mexico is typically sold according to a farm-gate base price, and the actual sale Table 1. Equations and functional dependence on water quality and management variables Ruiz-Velazco et al (2013) used for the stock and feed conversion ratio models.…”

Section: Economic Modelmentioning

confidence: 99%

“…In a previous work (Ruiz-Velazco et al, 2013), we determined the combinations of stocking density and duration of cultivation that minimize and maximize production of shrimp biomass in the seeding-harvesting schedules. The lowest stocking density and the shortest duration of cultivation minimize production, whereas the highest stocking density and longest duration of cul- production was calculated.…”

Section: Management Schemesmentioning

confidence: 99%

“…Previously, we conducted a study of semi-intensive production of shrimp in northwestern Mexico and determined that cultivation programs that seeded in spring resulted in higher production of shrimp biomass, compared with production using a cultivation program that seeded in summer (Ruiz-Velazco et al, 2013). Given the seasonality of shrimp market prices and the variability of costs among the alternative cultivation programs, the question arose whether higher production obtained when seeding in spring would also result in better economic performance, compared with seeding in summer.…”

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A bio-economic approach to analyze the role of alternative seeding-harvesting schedules, water quality, stocking density and duration of cultivation in semi-intensive production of shrimp in Mexico

Estrada-Pérez¹,

Ruiz-Velazco²,

Hernández‐Llamas³

et al. 2017

Lat. Am. J. Aquat. Res.

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We used a bio-economic model to analyze the role that alternative seeding-harvesting schedules, temperature, dissolved oxygen, stocking density, and duration of cultivation play in the economic performance of semi-intensive shrimp cultivation in Mexico. The highest production was predicted for the May-August schedule (1130-2300 kg ha-1), while the lowest yields were obtained for the March-June schedule (949-1300 kg ha-1). The highest net revenues were projected for the August-November schedule (US$354-1444 ha-1), while the lowest was projected for the May-August schedule (US$330-923 ha-1). The highest annual net revenues were predicted for the combination of the March-June and August-November schedules (US$1432-2562 ha-1). Sensitivity analysis indicated temperature and dissolved oxygen were the most important factors determining net revenues in March-June schedule. For the May-August and August-November schedules, stocking density was the most important factor. Duration of cultivation was the least sensitive variable. Break-even production analysis confirmed that the combination of the March-June and August-November schedules were more efficient from an economic perspective. We recommend test some ponds with higher stocking density in the March-June and August-November schedules, and in the latter case, seeding in June or July rather than August.

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Estimating the impact of COVID-19 pandemic on alternative semi-intensive shrimp (Penaeus vannamei) production schedules in Mexico: a stochastic bioeconomic approach

et al. 2022

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This study uses a stochastic bioeconomic approach to estimate the COVID-19 pandemic economic impact on shrimp farming in Mexico. Seeding-harvesting schedules — March–June, May–August, and August–November — were analyzed using shrimp prices and production costs corresponding to 2017–2019 (pre-pandemic) and 2020 (pandemic). The analyses estimated net revenue varied within 597.97–2758.88 USD$ ha −1 and 1262.40–1701.32 USD$ ha −1 under the pre-pandemic and pandemic scenarios, respectively. Significant decreases (38%) were estimated in net revenue values in March–June and May–August under the pandemic scenario. However, probability distributions estimated that uncertainty on the expected net revenues was not affected by the pandemic conditions, and the probability of losing was null or negligible in all the cases. Unfavorable conditions under the pandemic also required significantly higher break-even production for March–June (25.7%) and May–August (28.5%) schedules. The cost of post-larvae was the most important economic factor influencing net revenue. To conclude, although the operating conditions during the pandemic were conducive to worsening the economic outcome, no evidence still exists that uncertainty and economic risk increased compared with pre-pandemic conditions.

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Stock model and multivariate analysis for prediction of semi-intensive production of shrimp Litopenaeus vannamei as a function of water quality and management variables: A stochastic approach

Cited by 11 publications

References 20 publications

Assessing uncertainty of semi-intensive production of whiteleg shrimp (Litopenaeus vannamei) using partial harvesting programs

Assessing uncertainty of semi-intensive production of whiteleg shrimp (Litopenaeus vannamei) using partial harvesting programs

A bio-economic approach to analyze the role of alternative seeding-harvesting schedules, water quality, stocking density and duration of cultivation in semi-intensive production of shrimp in Mexico

Estimating the impact of COVID-19 pandemic on alternative semi-intensive shrimp (Penaeus vannamei) production schedules in Mexico: a stochastic bioeconomic approach

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