Improving feeding strategies for shrimp farming using fuzzy logic, based on water quality parameters

2018 ◽  
Vol 81 ◽  
pp. 38-45 ◽  
Author(s):  
R.A. Bórquez-Lopez ◽  
R. Casillas-Hernandez ◽  
J.A. Lopez-Elias ◽  
R.H. Barraza-Guardado ◽  
L.R. Martinez-Cordova
2017 ◽  
Vol 65 (3) ◽  
pp. 495-508
Author(s):  
William Bauer ◽  
Paulo Cesar Abreu ◽  
Luis Henrique Poersch

Abstract Water quality, chlorophyll a, phytoplankton, proto and mezo-zooplankton abundance were spatiotemporally evaluated in an estuary receiving effluents from a Pacific white shrimp Litopenaeus vannamei farm in Patos Lagoon estuary, Southern Brazil. Samples were taken before (BD) and; 1 day (1 PD) 5 days (5 PD), 10 days (10 PD), 20 days (20 PD) and 30 days (30 PD) after the effluents discharge. Some water quality parameters were affected by the effluents discharge; however, these changes were restricted to a distance of 20 m from the effluent discharge channel for a period of 5 days. The microbial community was dominated by chlorophyceae, followed by diatoms, cyanobacteria and ciliates. There was an increase in the abundance of different groups on the 1 PD sampling compared to BD. The zooplankton abundance was low in practically all sites, except for 30 PD sampling. The meso-zooplanktonic organisms were represented by copepods, mostly Acartia tonsa. Despite some effects on water quality and phytoplankton and protozooplankton abundance until 5 PD sampling, these alterations dissipated in a short period of time. We conclude that the environment quickly assimilated the effluents discharge, and the water quality parameters remained within the limits stipulated by standard guidelines.


2014 ◽  
Vol 955-959 ◽  
pp. 3310-3313
Author(s):  
Qiao Ling Du ◽  
Zeng Hua Ren ◽  
Zhen Ze Liu ◽  
Yi Ding Wang

In this paper a fuzzy logic prediction method is proposed to assess water quality status of a reservoir in northeast China through wireless sensor networks. This model was used to analyze the historical data that were collected monthly by local monitoring stations and predict water quality level. Six water quality parameters of BOD5, COD, fluoride, ammonia, total phosphorus (TP), and total nitrogen (TN) were monitored from 2011 to 2012. This result indicated that the methodology adopted in this study was basically an attractive alternative, offering a relatively fast algorithm to predict the water quality parameters.


2021 ◽  
Vol 12 (1) ◽  
pp. 18-28
Author(s):  
Heri Ariadi ◽  
Abdul Wafi ◽  
Muhammad Musa ◽  
Supriatna Supriatna

Water quality parameters play an important role in intensive pond ecosystems. The purpose of this study was to determine the relationship between of water quality parameters in intensive shrimp farming of L. vannamei. This research was carried out for 95 days of intensive shrimp farming in PT. Menjangan Mas Nusantara Company, Banten, with the physical, chemical, and microbiological parameters of water as the main reference object of observation. The results showed that during the shrimp culture period the pond water quality parameter concentration was considered to be quite optimal with a stable fluctuation trend, except for the salinity and TOM parameters whose values ​​were above the water quality standard. Correlation test results state that between the physical chemical parameters have a strong and heterogeneous relationship, with the strongest parameters of pH, phosphate, nitrite, and TOM. As for the microbiological variables, the correlation of physical chemistry parameters of water is considered to be very weak, because from the correlation test results, only DO parameters showed the correlation with microbiological parameters. The conclusion of this study, that during intensive shrimp culture period, the physical and chemical parameters of water have a strong correlation of association between one another and the highest are pH, phosphate, nitrite, and TOM, but only dissolved oxygen parameters that show the relationship correlation with microbiological parameters.


Author(s):  
Le The Truyen ◽  
Le Thanh Long

The development of new technologies in automation to increase labor productivity has been increasingly enhanced in recent decades. The problem of cleaning water in shrimp ponds greatly affects the quality as well as shrimp production. Environmental pollution of shrimp farming is a matter of concern because the current waste treatment solutions are not yet thorough. A waste remover of shrimp waste combined with the pond bottom siphon method has been researched and developed to increase the ability to thoroughly handle waste generated in the culture environment. This device helps to automate the manual cleaning of the pond bottom by farmers. The device performs operations to clean waste, suck, filter, and remove waste from the culture environment. This device is self-propelled or manually controlled and operates in all weather conditions. This article introduces the process of testing and evaluating the efficiency of waste extraction equipment in shrimp ponds. The device was tested at a super-intensive shrimp farm and evaluated for operational efficiency. The experimental model consists of a shrimp pond operating a waste suction device, a control pond, an automatic monitoring system of water quality parameters (DO, H2S, NH3, pH, and temperature). Experimental ponds operating waste disposal equipment, control ponds are manually cleaned, other farming conditions of the two ponds are similar. The impacts of waste on the shrimp culture environment are determined through analyzing the results of measuring water quality criteria in the pond, thereby assessing the efficiency of waste removal of the equipment. The measurement results show that water quality parameters reach a value within the threshold if operating a waste suction device once per day. The benefits of waste remover operate to help save the cost of labor to clean the pond bottom, protect workers' health.


2015 ◽  
Vol 8 (1) ◽  
pp. 85-89
Author(s):  
F Zannat ◽  
MA Ali ◽  
MA Sattar

A study was conducted to evaluate the water quality parameters of pond water at Mymensingh Urban region. The water samples were collected from 30 ponds located at Mymensingh Urban Region during August to October 2010. The chemical analyses of water samples included pH, EC, Na, K, Ca, S, Mn and As were done by standard methods. The chemical properties in pond water were found pH 6.68 to 7.14, EC 227 to 700 ?Scm-1, Na 15.57 to 36.00 ppm, K 3.83 to 16.16 ppm, Ca 2.01 to 7.29 ppm, S 1.61 to 4.67 ppm, Mn 0.33 to 0.684 ppm and As 0.0011 to 0.0059 ppm. The pH values of water samples revealed that water samples were acidic to slightly alkaline in nature. The EC value revealed that water samples were medium salinity except one sample and also good for irrigation. According to drinking water standard Mn toxicity was detected in pond water. Considering Na, Ca and S ions pond water was safe for irrigation and aquaculture. In case of K ion, all the samples were suitable for irrigation but unsuitable for aquaculture.J. Environ. Sci. & Natural Resources, 8(1): 85-89 2015


2018 ◽  
Vol 69 (8) ◽  
pp. 2045-2049
Author(s):  
Catalina Gabriela Gheorghe ◽  
Andreea Bondarev ◽  
Ion Onutu

Monitoring of environmental factors allows the achievement of some important objectives regarding water quality, forecasting, warning and intervention. The aim of this paper is to investigate water quality parameters in some potential pollutant sources from northern, southern and east-southern areas of Romania. Surface water quality data for some selected chemical parameters were collected and analyzed at different points from March to May 2017.


1982 ◽  
Vol 14 (4-5) ◽  
pp. 43-58 ◽  
Author(s):  
M Rizet ◽  
J Mouchet

This study was conducted in order to understand the taste and odour problems that occurred in the Seine and the Marne rivers during the severe drought of 1976. Samples were taken every 15 days from several locations in the rivers themselves and from storage reservoirs upstream from Paris. Algae and actinomycetes were identified and counted. Metabolite concentrations were measured. These data were correlated with threshold odor numbers and bacteriological water quality parameters.


Water ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 507 ◽  
Author(s):  
Iván Vizcaíno ◽  
Enrique Carrera ◽  
Margarita Sanromán-Junquera ◽  
Sergio Muñoz-Romero ◽  
José Luis Rojo-Álvarez ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document