Volume 14, Issue 4 July/August 2011 GLOBAL ...

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Andrew J. Ray, M.S.; Jeffrey M. Lotz, Ph.D.;. Jeffrey F. Brunson, M.S.; John W. Leffler, Ph.D. 16 Oyster Output Affected By Environmental. Features Of Farm Site.


Volume 14, Issue 4

July/August 2011

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DEPARTMENTS From The Director From The Editor GAA Activities Industry News Advocate Advertisers

12 Liming Materials For Aquaculture

Claude E. Boyd, Ph.D.

14 Shrimp Sampling Method Improves Stocking Process

Andrew J. Ray, M.S.; Jeffrey M. Lotz, Ph.D.; Jeffrey F. Brunson, M.S.; John W. Leffler, Ph.D.

16 Oyster Output Affected By Environmental Features Of Farm Site

Darien D. Mizuta, Nelson Silveira Júnior, Christine E. Fischer, Daniel Lemos

2 3 5 85 88

On the cover:

Nutrition research has led to reduced fishmeal use in diets for amberjack and other emerging species. Photo courtesy of Kona Blue Water Farms.

19 Uncharted Waters: Kenya Takes Dramatic Leap In Aquaculture

Jeff Hino

Page 19

22 India’s Fish Feed Industry – Growing Sector Can Support Aquaculture Diversity, Development

Kenya Backs Aquaculture

Kenya’s officials are counting on aquaculture to relieve pressure on fisheries and supply a more sustainable source of protein – and cash – for Kenyans.

P. E. Vijay Anand, Ph.D.; Michael C. Cremer, Ph.D.

26 Tilapia Farming Faces Expansion Issues In Thailand

Ram C. Bhujel, Ph.D.; Mark Woollard

30 Working With Fish – Limit Zoonotic Diseases Through Prevention

Stephen A. Smith, DVM, Ph.D.

34 Bacterial Diseases Cause Granulomas In Fish – Varied Staining Methods Identify Pathogens


Over twenty years of cold chain experience working with world renowned seafood and frozen food companies.


PFS has established a competitive advantage through the aggressive use of engineering and technology. We employ the most sophisticated hardware and software systems; constantly improving our service offerings to you.

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37 Boston Session Examines ‘What Fish Eat’

Kelly Coleman

40 American Fisheries Society Calls For Immediate-Release Fish Sedatives

James Bowker, M.S.; Jesse Trushenski, Ph.D.

We design state-of-the-art temperature controlled warehouses allowing us to provide flexible customer solutions.


46 Common Off-Flavors In Channel Catfish Following Partial Pond Harvest

PFS is recognized as the fourth largest temperature controlled warehouse company in the world with expansion in North America and Asia.

Dong-Fang Deng, Ph.D.; Zhi Yong Ju, Ph.D.; Warren G. Dominy, Ph.D.; Peter J. Bechtel, Ph.D.; Scott Smiley, Ph.D.

Kevin K. Schrader, Ph.D.; Craig S. Tucker, Ph.D.

50 U.S. Catfish Industry Production Shifts Continue

James A. Steeby, Ph.D.

52 Survey Examines Perceived Barriers, Strategies For U.S. Aquaculture Development

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Saba Siddiki; Christopher M. Weible, Ph.D.

55 Figures Confirm: Chilean Salmon Is Back

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Shrimp Resist WSSV

In a recent challenge test, resistance to WSSV was shown in shrimp supplied by the Camaronera de Coclé, S.A. L. vannamei genetics program.

65 Testing Finds Resistance To WSSV In Shrimp From Panamanian Breeding Program

Jorge Diaz Salinas

56 Off-Flavors In Aquacultured Products – Part II: Environmental, Endogenous Factors

George J. Flick, Jr., Ph.D.

58 Diversification Of The Aquaculture Sector – Seaweed Cultivation, Integrated Multi-Trophic Aquaculture, Integrated Sequential Biorefineries

Mark Rottman

72 Single-Cell Detritus: Fermented Bioenriched Feed For Marine Larvae

Dr. S. Felix, P. Pradeepa

74 Novel Soy Proteins, Oils Replace Fishmeal To Achieve FIFO Under 1:1 In Amberjack

Jennica Lowell, M.S.; Neil Anthony Sims, M.S.; Tom Clemente, Ph.D.

76 Photo-Based Color Evaluation Can Enhance Catfish Fillet Quality

David Cline

78 Nitrifier Product Improves Nitrification In RAS

Dr. T. Chopin, Dr. A. Neori, Dr. A. Buschmann; Dr. S. Pang, M. Sawhney


Shrimp Disruptions Continue, Supply Delays Expected Whole Salmon, Fillet Imports To U.S. Down Whole Tilapia Stay Low, Costa Rica Fillets Drop Pangasius Imports Grow As Replacement Costs Rise

Paul Brown, Jr.; Janice Brown; Angel Rubio

Asbjørn Drengstig, Yngve Ulgenes, Helge Liltved, Asbjørn Bergheim

70 New Techniques, Peptide Treatments Aid Intensive Shrimp Farm In Ecuador

Jorge Cuéllar-Anjel; Roberto Chamorro; Brenda White-Noble; Paul Schofield; Donald V. Lightner, Ph.D.

67 Norweigian Salmon Smolt Farms Embracing RAS To Raise Production


Our expertise and systems deliver the quickest, most accurate, and cost-effective fulfillment and delivery experience for every customer.

Page 65

42 Potassium Diformate Doesn’t Affect Shrimp Growth, Survival; Reduces Nutrient Digestibility

For more information about PFS, please contact: Daniel DiDonato - Vice President of Sales One Main Street, 3rd Floor Chatham, New Jersey 07928 [email protected] Phone: 973-820-4070 July/August 2011 global aquaculture advocate ii

Wes A. Baumgartner, DVM, Dipl. ACVP; John Hawke, Ph.D.

David D. Kuhn, Ph.D.; David J. Drahos

80 Essential Oils Increase Weight Gain In Channel Catfish Brian C. Peterson, Ph.D.; Brian G. Bosworth, Ph.D.; Monica L. Wood; Menghe H. Li, Ph.D.; Ruben Beltran, M.S.

83 Labomar Study Defines Optimal Dietary Lipid, Energy Content For Fat Content

Alberto J. P. Nunes, Ph.D.; Ricardo C. C. Pinto, M.S., Marcelo V. C. Sá, Ph.D.

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Table 1. Typical organization for a spreadsheet used to monitor confidence bounds around the mean.

Shrimp Sampling Method Improves Stocking Process

Sample Number

Andrew J. Ray, M.S.

Jeffrey M. Lotz, Ph.D.

University of Southern Mississippi Gulf Coast Research Laboratory

Jeffrey F. Brunson, M.S. John W. Leffler, Ph.D.

South Carolina Department of Natural Resources Waddell Mariculture Center Bluffton, South Carolina, USA


Accurate estimates of shrimp populations and size variability can help managers make informed decisions that reduce feeding costs and improve system performance. The mean weight of multiple groups of shrimp is commonly used to determine the quantity of shrimp needed to stock at a particular density. However, knowing the number of samples needed to overcome nursery size variability can substantially increase accuracy. Accurate estimation of the number of shrimp in a culture unit is critical for managers to administer appropriate feed rations and predict harvest size. If the population is underestimated, the animals will be underfed, leading to poor growth. If the system is overfed due to an overestimation of the population, unnecessary nutrients can cause oxygen depletion and toxic inorganic nitrogen accumulation, in addition to significant economic losses caused by wasted feed. To estimate the population size of a growout system, an accurate approximation of the number of shrimp stocked must first


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be made. One of the advantages to operating a nursery prior to the growout cycle is that the number of shrimp can be reassessed between the two stages. The mean weight of multiple groups of shrimp is commonly used to determine the quantity of shrimp, by weight, needed to stock at a particular density. However, knowing the number of samples needed to overcome nursery size variability and arrive at a statistically sound approximation of the weight needed can substantially increase accuracy.

Shrimp Sampling Method

To arrive at an accurate estimate of shrimp weight, a statistics-based sequential sampling method is routinely used at the Gulf Coast Research Laboratory in Mississippi, USA, and the Waddell Mariculture Center in South Carolina, USA. Groups of animals from all areas of the nursery are collected, and care is taken to avoid crowding animals in nets. Approximately 200 animals are included in each sample. Samples are then carefully weighed, and the exact numbers of shrimp are counted. The sample weight and number of shrimp in each sample are recorded in an electronic spreadsheet. The formulas used to calculate each subsequent value are preprogrammed into the spreadsheet before

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Size Variability, Stocking Density

To assess whether variation in shrimp size at the end of a nursery phase can be attributed to nursery stocking density, the

277 270 274 200 258 252 226 262 283 306 287 267 251 260 291

Degrees of Freedom

T-Value (two-tale, α = 0.05)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

12.706 4.303 3.182 2.776 2.571 2.447 2.365 2.306 2.262 2.228 2.201 2.179 2.160 2.145 2.132 2.120 2.110 2.101 2.093 2.086 2.080 2.074 2.069 2.064 2.060 2.056 2.052 2.048 2.045 2.042

Standard Deviation

Standard Error

Confidence Bound

Confidence Bound CB/Mean

1.309 1.329 1.238 1.244 1.246 1.226 1.235 1.252 1.275 1.280 1.281 1.278 1.278 1.282

0.034 0.042 0.184 0.160 0.143 0.142 0.134 0.136 0.146 0.140 0.134 0.128 0.123 0.120

0.024 0.024 0.092 0.072 0.058 0.054 0.047 0.045 0.046 0.042 0.039 0.036 0.033 0.031

0.304 0.105 0.293 0.199 0.150 0.131 0.112 0.104 0.105 0.094 0.085 0.078 0.071 0.066

0.232 0.079 0.237 0.160 0.121 0.107 0.091 0.083 0.082 0.073 0.066 0.061 0.056 0.052

authors examined data from 15 recent nursery harvests at the Waddell Mariculture Center. They compared the coefficient of variation in the size of shrimp at the time of nursery harvest to the original stocking density of those respective nurseries. Using regression analysis, it was determined that stocking density was a strong predictor of the coefficient of variation in shrimp weight. This finding implies that with higher stocking density comes greater size variability when nurseries are harvested.


By sampling a nursery system in the manner described, the statistical confidence bounds around the mean shrimp weight are monitored closely as samples are collected. This allows a system manager to arrive at a point in sampling where 95% confidence bounds around the mean are established. Equation 1

Standard Standard Deviation = Number of Samples Error


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Confidence Standard Error = * T-Value Bound Shrimp Stocked Desired = Equation 3 Shrimp Weight Mean Shrimp/g Figure 1. Error and confidence equations. Confidence Bound:Mean Standard Error

0.15 0.10 00.5 0

This project demonstrated that the amount of variation in shrimp size can be a product of the nursery stocking density. This may be an important consideration in determining the number of shrimp that should be stocked into a nursery system. Stocking shrimp of uniform size reduces the initial variability of growout systems. It should be evaluated whether this reduction in variability results in a decrease of size variability at the end of the production cycle.

Equation 2

0.25 0.20

Cumulative Mean Shrimp/g

1.285 1.333 1.369 0.967 1.264 1.260 1.101 1.298 1.391 1.477 1.336 1.295 1.238 1.278 1.339

Table 2. αT-values used to calculate confidence bounds with equation 2.

Sample Values

Calculations based on multiple samples of 200 shrimp taken at the nursery stage can lead to more accurate stocking in the growout phase.

sampling begins. A completed example spreadsheet file is depicted in Table 1. From the number of shrimp in each sample and the weight of that sample, a shrimp per gram value is calculated. In the following column, a cumulative mean shrimp per gram value is calculated with each new sample. From that, standard deviation and standard error values are calculated as in equation 1 in Figure 1. The standard error value is used in equation 2 to calculate the confidence bound (C.B.). The C.B. is then divided by the latest cumulative mean value to determine whether the limits of the C.B. are within 5% of the mean. The t-value used in equation 2 (Figure 1) to calculate the C.B. comes from a table of t-distributions typically found in statistics books. The value needed is from a two-tale t-distribution where α = 0.05. The t-value used depends on the number of samples weighed, where degrees of freedom = N-1. The t-values are presented in Table 2. When at least 10 samples have been measured, and the C.B.:mean ratio is 0.05 or less, that latest cumulative mean value is accepted. Shrimp can then be stocked by weight using equation 3 (Figure 1), with the accuracy of the number of shrimp stocked within 5% (Figure 2). For example, using the data in Table 1, if a system manager would like to stock 50,000 animals from the sampled nursery, 39,001.6 g of shrimp (50,000/1.282) are needed.

215.6 202.6 200.1 206.8 204.1 200.0 205.3 201.8 203.4 207.2 214.9 206.2 202.7 203.5 217.4

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

University of Southern Mississippi Gulf Coast Research Laboratory 703 East Beach Drive Ocean Springs, Mississippi 39564 USA [email protected]

Weight Number (g) of Shrimp Shrimp/g

Figure 2. The standard error and confidence bound/mean ratio values from Table 1 change with sequential sampling. As the ratio converges toward the desired level of probability, the mean shrimp weight falls within the confidence bound.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Sample Number global aquaculture advocate

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