scholarly journals Water quality, feeding management and cost-benefit analysis of a fish hatchery in Jessore district of Bangladesh

2016 ◽  
Vol 2 (3) ◽  
pp. 414-421
Author(s):  
Md Monirul Islam ◽  
Rashidul Hassan ◽  
BM Newaz Sharif ◽  
Md Mostafizur Rahaman ◽  
Md Aminur Islam ◽  
...  
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Benefit Analysis ◽  
Fish Hatchery ◽  
Feeding Management ◽  
Cost Benefit Ratio

The study was conducted at Ma-Fatema Fish Hatchery in Jessore from January to March, 2016. The present study was emphasized on water quality parameters, feeding management and cost- benefit analysis. The water quality parameters temperature (0C), pH, dissolved oxygen (DO) (mg/l) and transparency (cm) were measured by Celsius thermometer, pH meter, DO meter and secchi disk, respectively. The proximate composition of feed ingredients was determined by the Association of Analytical Chemists, 1980. Brood fishes were reared all year round in the brood ponds by supplying formulated feeds. Temperature was 19oC -26°C in brood ponds and 18oC-24oC in hatching jars; pH was 6.93–7.87 in brood ponds and 6.79-7.54 in the hatching jars; dissolved oxygen was 4.8-6.3 mg/l in brood ponds and 4.8-6.7 mg/l in hatching jars; transparency was 14-18 cm in the brood ponds. The percentage of farm made feed was protein (27.76%), lipid (4.9%), CHO (18.62%), ash (11.31%), fiber (6.4%), moisture (31.01%). The cost benefit ratios were 1.54, 1.32 and 1.23 and net profits were BDT 49911.67, BDT 24816.67and BDT 16366.67 respectively in January, February and March. Management of brood fish by providing quality feed and physico-chemical parameters of water were maintained in according to scientific procedure. Cost-benefit ratio of the hatchery in common carp production was satisfactory.Asian J. Med. Biol. Res. September 2016, 2(3): 414-421

scholarly journals Effects of Different Protein Level Feeds on the Fingerlings Production of Riverine Endangered Notopterus Chitala (Hamilton, 1882) in Ponds

2020 ◽  
Vol 7 (3) ◽  
pp. 553-563
Author(s):  
Mustafizur Rahman ◽  
Md Abdus Samad ◽  
Md Nahiduzzaman ◽  
Alpana Zaman Lata
Keyword(s):  
Water Quality ◽  
Weight Gain ◽  
Protein Level ◽  
Cost Benefit ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Highest Weight ◽  
Cost Benefit Ratio ◽  
Growth Production ◽  
The Cost

This study was aimed to evaluate the efficiency of three protein level feeds on the fingerlings production of riverine endangered Notopteruschitala (Hamilton, 1882) for a period of two months in ponds. Chital fry (Initial wt, 5.6±0.19 g) were randomly stocked at the rate of 7410 per hector. Feeding trials were conducted under 3 treatments (T1: feed contains 35% protein, T2: feed contains 30% protein, T3: feed contains 25 % protein) each with 3 replications. No significant (P<0.05) difference was observed for all the water quality parameters among the treatments. A suitable range of water quality parameters (temperature, water transparency (cm)), dissolved oxygen (mg/l), pH, alkalinity (mg/l), ammonia) were recorded with the environment of experimental ponds. The treatment had significant effects on weight gain, ADG, SGR among treatments. Highest weight gain (19.31 ± 0.23 g) was observed in T1, lowest (13.96 ± 0.15 g) in T3. SGR (1.65±0.02) and ADG (0.18±0.005) were significantly (P<0.05) highest in T1 followed by T2 and T3. The N chitala exhibited highest survival rate (96.66%) in T1 than T2 followed by T3 (88.89 %). The best FCR value (3.02±0.09) was recorded in treatment T1 with 35% protein contain feed. Relatively, highest benefits (138690±175.36 BDT/ha) were found from treatment T1 compared to other treatments. Similarly, the cost benefit ratio was highest in T1 (1:1.23) and lowest in T3 (0.95). Findings indicated that treatment T1 (35% protein containing feed) was found best in terms of growth, production and economics of N. chital for fingerling production in ponds. Res. Agric., Livest. Fish.7(3): 553-563,  December 2020

What's it Worth? Improving Surface Water Quality

1999 ◽  
Vol 40 (10) ◽  
pp. 153-159 ◽  
Author(s):  
D. H. Newsome ◽  
C. D. Stephen
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Surface Water Quality ◽  
Control Measures ◽  
Benefit Analysis ◽  
The Cost

Many countries are investing in measures to improve surface water quality, but the investment programmes for so doing are increasingly becoming subject to cost-benefit analysis. Whilst the cost of control measures can usually be determined for individual improvement schemes, there are currently no established procedures for valuing the benefits attributable to improved surface water quality. The paper describes a methodology that has been derived that now makes this possible.

scholarly journals Cladoceran abundance in relation to water quality parameters of Chakki Talab, Bodhan, Telangana

2018 ◽  
Vol 8 (01) ◽  
Author(s):  
Vasudha Lingampally ◽  
V.R. Solanki ◽  
D. L. Anuradha ◽  
Sabita Raja
Keyword(s):  
Water Quality ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Total Dissolved Solids ◽  
Quality Parameters ◽  
Biological Oxygen Demand ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Total Hardness ◽  
One Year

In the present study an attempt has been made to evaluate water quality and related density of Cladocerans for a period of one year, October 2015 to September 2016. Water quality parameters such as temperature, PH, total dissolved solids, dissolved oxygen, biological oxygen demand, total alkalinity, total hardness, chlorides, phosphates, and nitrates are presented here to relate with the abundance of Cladocerans. The Cladoceran abundance reflects the eutrophic nature of the Chakki talab.

scholarly journals Impacts of Coal Railroad Transportation Project on GDP Promotion and Unemployment Reduction in Bengkulu Province, Indonesia

2013 ◽  
Vol 216 ◽  
pp. 02-24
Author(s):  
PAULUS KURNIAWAN ◽  
KEMBAR SRI BUDHI ◽  
SUYANA UTAMA ◽  
MAHAENDRA YASA
Keyword(s):  
Significant Contribution ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Economic Indicator ◽  
Internal Rate Of Return ◽  
Benefit Analysis ◽  
Cost Benefit Ratio ◽  
Railroad System ◽  
The Unemployed ◽  
The Impact

massive, advanced and integrated railroad system for coal transportation (referred to hereafter as ?Project?) from Muara Enim, Sumatra Selatan Province to the new coal port at Pulau Baai, Bengkulu Province, Indonesia is developed by a private investor together with the local government (PEMDA) of Bengkulu Province to make the best use of abundant coal resources in the region. This paper analyzes the impact of this Project on the Bengkulu economy, which is currently considered low. The Gross Domestic Product (GDP) is adopted as the economic indicator. The study combines the theories of export base and economic base, economic and regional developments, cost-benefit analysis and economic impact study with the empirical data. The results show the Project?s financial feasibility with Cost-Benefit Ratio of 1.61, Internal Rate of Return of 21.1% and Payback Period of 5 years, which will provide a significant contribution to the Bengkulu GDP growth and a decrease of 821,600 people among the unemployed.

scholarly journals Potensi budidaya ikan di Waduk Embung Klamalu Kabupaten Sorong Provinsi Papua Barat: Kajian kualitas fisika kimia air

2013 ◽  
Vol 1 (3) ◽  
Author(s):  
Agustina Frasawi ◽  
Robert J Rompas ◽  
Juliaan Ch. Watung
Keyword(s):  
Carbon Dioxide ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Good Condition ◽  
Fish Farming ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Alkalinity ◽  
Physical Chemical ◽  
Papua Barat

The objective of this research was to measure and analyze the water quality parameters including temperature, brightness, pH, dissolved oxygen, total alkalinity, carbon dioxide and BOD in reservoir Embung Klamalu Sorong regency, and to know the factors that affected the water quality of Embung Klamalu. Measurement of water quality parameters was done in situ for temperature, brightness, pH and in laboratory for dissolved oxygen, total alkalinity, carbon dioxide, and BOD. The results showed the temperature at the five observation stations ranged from 26.2 to 29.8 0C, brightness 38 to 46 cm, pH 7.20 to 8.48 mg /L, dissolved oxygen from 7.20 to 8.48 mg / L, alkalinity 100 to 150 mg /L, carbon dioxide from 25.90 to 28.95 mg / L, BOD from 0.20 to 0.38. Refers to the standards of water quality according to the PP. 82, 2001, it could be concluded that water physical-chemical qualities in fish farming locations in the Village Klamalu were still in good condition. Keywords: Water physical-chemical quality, aquaculture, waduk Embung Klamalu

Neonatal Intensive Care: Cost-Benefit Analysis

PEDIATRICS ◽  
1985 ◽  
Vol 75 (4) ◽  
pp. 798-799
Author(s):  
DONALD N. MANGRAVITE
Keyword(s):  
Intensive Care ◽  
Neonatal Intensive Care ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Tertiary Level ◽  
Benefit Analysis ◽  
Costs And Benefits ◽  
Benefit Ratio ◽  
Comprehensive Examination ◽  
Cost Benefit Ratio

To the Editor.— I would like to commend Walker and colleagues1 for their comprehensive examination of the costs and benefits of neonatal intensive care for infants weighing less than 1,000 grams. However, examining only one group of infants served by a tertiary neonatal intensive care unit (NICU) can be misleading. By definition, a tertiary level NICU is designed to provide a broad range of services to infants with a wide variety of illnesses. As is true for any system expected to provide a broad range of services, some services will result in a more favorable cost-benefit ratio than others.

scholarly journals Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yashon O. Ouma ◽  
Clinton O. Okuku ◽  
Evalyne N. Njau
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Dissolved Oxygen ◽  
Multiple Linear Regression ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Monitoring

The process of predicting water quality over a catchment area is complex due to the inherently nonlinear interactions between the water quality parameters and their temporal and spatial variability. The empirical, conceptual, and physical distributed models for the simulation of hydrological interactions may not adequately represent the nonlinear dynamics in the process of water quality prediction, especially in watersheds with scarce water quality monitoring networks. To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. To understand the influence of the contributing factors to the DO variations, the model considered the inputs from the available water quality parameters (WQPs) including discharge, electrical conductivity (EC), pH, turbidity, temperature, total phosphates (TPs), and total nitrates (TNs) as the basin land-use and land-cover (LULC) percentages. The performance of the FNN model is compared with the multiple linear regression (MLR) model. For both FNN and MLR models, the use of the eight water quality parameters yielded the best DO prediction results with respective Pearson correlation coefficient R values of 0.8546 and 0.6199. In the model optimization, EC, TP, TN, pH, and temperature were most significant contributing water quality parameters with 85.5% in DO prediction. For both models, LULC gave the best results with successful prediction of DO at nearly 98% degree of accuracy, with the combination of LULC and the water quality parameters presenting the same degree of accuracy for both FNN and MLR models.

scholarly journals Can Decomposition Approaches Always Enhance Soft Computing Models? Predicting the Dissolved Oxygen Concentration in the St. Johns River, Florida

2019 ◽  
Vol 9 (12) ◽  
pp. 2534 ◽  
Author(s):  
Mohammad Zounemat-Kermani ◽  
Youngmin Seo ◽  
Sungwon Kim ◽  
Mohammad Ali Ghorbani ◽  
Saeed Samadianfard ◽  
...  
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Dissolved Oxygen ◽  
Soft Computing ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Performance Criteria ◽  
Input Combination ◽  
Do Concentration ◽  
Computing Models

This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron (MLP) neural network and cascade correlation neural network (CCNN), were proposed for estimating the DO concentration in the St. Johns River, Florida, USA. The DO concentration and water quality parameters (e.g., chloride (Cl), nitrogen oxides (NOx), total dissolved solid (TDS), potential of hydrogen (pH), and water temperature (WT)) were used for developing the standalone models by defining six combinations of input parameters. Results were evaluated using five performance criteria metrics. Overall results revealed that the CCNN model with input combination III (CCNN-III) provided the most accurate predictions of DO concentration values (root mean square error (RMSE) = 1.261 mg/L, Nash-Sutcliffe coefficient (NSE) = 0.736, Willmott’s index of agreement (WI) = 0.919, R2 = 0.801, and mean absolute error (MAE) = 0.989 mg/L) for the standalone model category. In the second stage, two decomposition approaches, including discrete wavelet transform (DWT) and variational mode decomposition (VMD), were employed to improve the accuracy of DO concentration using the MLP and CCNN models with input combination III (e.g., DWT-MLP-III, DWT-CCNN-III, VMD-MLP-III, and VMD-CCNN-III). From the results, the DWT-MLP-III and VMD-MLP-III models provided better accuracy than the standalone models (e.g., MLP-III and CCNN-III). Comparison of the best hybrid soft computing models showed that the VMD-MLP-III model with 4 intrinsic mode functions (IMFs) and 10 quadratic penalty factor (VMD-MLP-III (K = 4 and α = 10)) model yielded slightly better performance than the DWT-MLP-III with Daubechies-6 (D6) and Symmlet-6 (S6) (DWT-MLP-III (D6 and S6)) models. Unfortunately, the DWT-CCNN-III and VMD-CCNN-III models did not improve the performance of the CCNN-III model. It was found that the CCNN-III model cannot be used to apply the hybrid soft computing modeling for prediction of the DO concentration. Graphical comparisons (e.g., Taylor diagram and violin plot) were also utilized to examine the similarity between the observed and predicted DO concentration values. The DWT-MLP-III and VMD-MLP-III models can be an alternative tool for accurate prediction of the DO concentration values.

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