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JOURNAL

OF

THE

WORLD AQUACULTURE

SOCIETY

Vol.

25, No.2

June,

1994

An Analysis

of

Biological, Economic, and Engineering Factors

Affecting the Cost of Fish Production in Recirculating

Aquaculture Systems

THOMAS

. U S O R D O

Department of Zoology and Biological & Agricultural E ngineering,

North Carolina State University, Raleigh, North Carolina 27695 USA

PHILIP

W.

WESTERMAN

Department

of

Biological & Agricultural E ngineering,

North Carolina State University, Raleigh, North Carolina 27695 USA

Abstract

Aquaculture production in recirculating systems has been the focus of research and development

efforts for decades. Although considerable resources have been expended on these systems in the

private sector, there is a scarcity of data on the economic or engineering performance of commercial

scale recirculating production systems. This paper presents the results of a computer simulation of

tilapia production in a small recirculating production system. Much of the performance data has

been developed at a demonstration facility at North Carolina State University. Given the assump-

tions of the base case simulation, the cost of producing a kilogram of tilapia in the recirculating

system described is estimated to be 2.79 ( 1.27/lb). The results of a model sensitivity analysis

indicate that while improvements n the performance efficiency of system components did not greatly

affect fish production costs, reductions in feed costs and improvements in the feed conversion ratio

caused the greatest reduction of production cost of all of the operational variables investigated. The

analysis further indicates that the greatest gains to be realized in improving profitability are those

associated with increasing the productive capacity or decreasing the investment cost of a recirculating

fish production system.

Recirculating aquaculture production

systems have stirred a great deal of interest

in the aquaculture community worldwide.

There is little doubt that most fish grown in

ponds, floating net pens, or raceways can be

reared in commercial scale recirculating

systems, given enough resources. Unfortu-

nately, the economic viability of growing

commonly cultured species in recirculating

systems is not as certain. The question of

system economics has not always been ad-

equately addressed prior to the develop-

ment of an aquaculture business based on

recirculating technology. Although there are

numerous corporations and entrepreneurs

selling “package turnkey” systems, there are

relatively few reports of profitable com-

mercial aquaculture recirculating produc-

tion systems in operation (Losordo et al.

1989).’ Currently most commercial recir-

culating production systems in the United

States are small, less than

45,000

kg of pro-

duction per year, providing fresh high qual-

ity product at premium prices to niche mar-

kets. Although there have recently been a

number of large scale efforts in commercial

system development, only two large scale

systems remain operating in the United

States with long term production of whole-

sale quantities of fish.

Given the level of interest and activity in

commercial recirculating production sys-

tems, there is a scarcity of data and system-

Mention

of

a specific product or tradename does

not constitutean endorsement by North Carolina State

University nor imply its approval to the exclusion of

other suitable products.

Copyright by the

World

Aquaculture

Society

1994

193

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194

LOSORDO AND

WESTERMAN

TABLE.

Simulated change in production cost

of hy-

brid striped

b ss

in a recirculating system due to a

10 change

in

selected input variables.

96

change in

Changed input variable oroduction cost

System capacity

Feed conversion ratio

Feed cost

Labor rate of pay

Mortality rate

Cost o f electricity

Cost o f liquid oxygen

5.0

4.1

2.8

1.8

1.4

1.4

0.5

After Losordo

I99 1.

atic evaluations of the economic aspects of

these systems in the literature. To reduce

the number of future economic failures and

aid in the design and development of suc-

cessful production systems, non-biased and

non-proprietary studies of the biological,

economic and engineering aspects of recir-

culating systems must be completed.

As part of a study of the feasibility of

recirculating aquaculture production sys-

tems, the authors developed a computer

model to simulate the biological, engineer-

ing and economic performance of closed

systems. The preliminary results were pre-

sented in Losordo et al. (1989). The findings

concluded that while it was not economical

to grow catfish in recirculating systems,

striped bass hybrids showed promise. A

sensitivity analysis of the simulation of the

production cost of hybrid striped bass to

changes in selected input costs was reported

in Losordo 199 1). In each simulation, only

one selected input was adjusted by 10%and

the resulting fish production cost was re-

corded. The selected input variables includ-

ed the cost of bulk oxygen, cost of electricity,

cost of feed, cost of labor, production mor-

tality, feed conversion ratio, and system

carrying capacity. Table

1

contains the re-

sults of the 7 simulations.

Interestingly enough, a

1

OYo intensifica-

tion of the production capacity of the sys-

tem (without a corresponding increase in

the fixed investment) produced the largest

decline ( 5 ) in production cost. These re-

sults suggested that future efforts in recir-

culating production system development

should be in the intensification of systems

without making them more expensive.

This paper will investigate this conclu-

sion and describe the results of simulations

of the production of tilapia in a recirculating

system. The computer model was upgraded

to more realistically represent a functioning

recirculating production system and where

possible, the model utilized verified input

data from a recirculating fish production

demonstration system at North Carolina

State University. The sensitivity of produc-

tion costs to changes in the variable and

fixed input costs and the biological and en-

gineering performance of the system are re-

ported.

Computer Simulation Methods

A general dynamic simulation model of

recirculating aquaculture systems was de-

veloped, using a commercially available

modelling language called STELLAB as a

framework in which to determine the en-

gineering, economic and biological perfor-

mance of recirculating fish production sys-

tems. While the model will not be described

in detail in this paper, a description of the

input and output variables and general

model structure follows.

STELLA model overview.

The computer

software package referred to as STELLAB

is a product of High Performance Systems,

Inc. The computer language was developed

for use only on the Apple Macintosh com-

puter. For a description of the programming

language, the reader is referred to Rich-

mond et al. 1987).

The model was originally developed to

simulate the growth and production of hy-

brid striped bass or channel catfish. The

model was expanded for this study to in-

clude the production of tilapia. Many of the

engineering simulation functions were also

expanded and refined for this study. Fish

growth rate algorithms were selected from

the literature as listed in Table 2. To run

the simulation, the user enters the appro-

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FISH PRODUmON COSTS IN RECIRCULATING SYSTEMS

195

TABLE

.

Recirculatingfish production system model

input variables.

Input variable Selection and/or units

Species cultured Hybrid Striped Bass

(Brown

19898)

Catfish (Boyd 1978)

Tilapia (Soderberg

1990)

Continuous or Batch

ode of operation

Cost of fingerlings each

Fingerling length mm

Fingerling weight

g

each

Fish harvest weight kg each

Fish survival

System capacity kg

Nursery decimal fraction

Growout decimal fraction

Production cycle length

Nursery d

Growout d

Feed cost

Fry %/kg

Juvenile feed %/kg

Grower feed S

Finishing feed

%/kg

Fry feed

%

Juvenile feed %

Grower feed %

Finishing feed

%

Feed protein content

Expected feed conversion dimensionless

Electricity costs

ratio

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196 LOSORDO ND WESTERMAN

TABLE. Selected recirculatingjishproduction system

model output variables.

Output variable Selection and/or un it s-

Total production cost

Feed cost

Labor cost

Fingerling cost

Heating costs

Water recirculating power

Water costs

Oxygen cost

Cost

of

borrowed capital

Cost of operating capital

Opportunity cost of equi-

Maintenance cost

Depreciation cost

Fish weight g/fish

System biomass kilograms

Recirculating flow rate Ipm

Make-up water flow rate Ipm

Feed rate kg/d

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg

of

fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

/kg of fish produced

costs

ty capital

and a production cost breakdown for each

input variable such as feed cost or water cost

per kg of fish produced. The output vari-

ables used for the system analysis in this

report are listed in Table

3.

Tilapia Production Simulation

The recirculating production system sim-

ulation model was configured to simulate

the production of tilapia in a small

43,500

kglyr

(96,000

lbs/yr) production system. The

following are details of the production sys-

tem simulated and the simulation model

assumptions.

Production system description. The pro-

duction system was modelled as a contin-

uous production unit consisting of

3

juve-

nile nursery tanks and 8 growout tanks. Each

nursery tank was capable of growing up to

6,560 83

g tilapia from

3

g

(50.8

cm,

2“

long) animals in

90

d. With the harvest of

one nursery tank each month, the

3

nursery

tanks provide enough 83 g tilapia to restock

2

growout tanks per month. Each growout

tank provides for the production of ap-

proximately 3,200 567 g (1.25 lb) tilapia in

approximately 120d. With

8

growout tanks,

2

harvests per month can be scheduled to

TABLE

.

Growout system compon ent cost and depre-

ciation estimates.

Compo-

Cost nent

installed life

System component

0 )

(Yr)

Fiberglass production tank

Floating bead filter

Rotating biological contactor

Aeration or oxygen delivery sys-

Pipes and valves

Pumps (3 each

@

120)

Solenoid valves

&

timers

Heater and controller

Feed delivery system

tem

Total cost

3,800

4 000

4,000

1,500

400

360

1,000

240

1,000

16,300

15

10

1 . 5

15

10

3

5

5

5

yield an overall yearly tilapia production of

slightly over

43,500

kg

(96,000

lb).

Systems design and cost. The cost esti-

mates in this section are derived from the

development of a demonstration “Fish

Barn” and recirculating production systems

at North Carolina State University. The

components described here are, for the most

part, of the same scale and similar to those

currently in use at the North Carolina Fish

Barn project.

The simulated production system is

housed within a

28

m x 11 m

(92’

x

36’)

metal clad, wooden post and beam barn with

minimal insulation and an earthen floor.

Each tank is configured with an individual

water renovation system consisting of an in-

line resistance type electric water heater, a

0.57

m3

(20

ft3) floating bead filter as de-

scribed by Losordo (199 1) and a V4 hp ro-

tating biological contactor (total surface area

=

418

m2) used in series (Fig. 1). Dissolved

oxygen additions to the culture tanks were

provided by either in tank diffised aeration

or whole recycle stream oxygenation with

pure oxygen (depending on the simulation

input selections). Each growout system con-

sists of a

4.25

m diameter,

1.45

m deep

fiberglass tank. Total cost of each growout

tank system with all associated support

equipment installed was modelled to be

16,300. The individual component costs

and estimated useful life are listed in Table

4.

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FISH

PRODUCTION COSTS IN RECIRCULATING SYSTEMS

197

Rotating Biological Contactor

2

(surface area

=

418 m )

d

4.24m

Culhut Tank

23.375

liters

Foam

Fractionator

FIGURE

Typical simulated growout system component layout.

The nursery tank systems were modelled

as 3 m diameter, 1.25

m

deep fiberglass

tanks. Water and wastewater treatment for

all three nursery tanks are provided for by

one bead filter and one RBC as described

above. Total cost of the nursery production

system is $18,490 (Table

5 ) .

A

depreciation rate for each system was

estimated by the “straight line” method as-

suming a salvage value of zero dollars at the

end of the useful component life. The au-

thors chose to assign a salvage value of zero

for each asset due to the specialized (in many

cases custom fabrication) nature and the

limited market for used recirculation sys-

tem components. The yearly rate of depre-

ciation was estimated by calculating the dol-

lar value per year of depreciation for each

component (cost installedlcomponent life),

then summing the yearly depreciated value

for each component and dividing by the to-

tal system cost (Yearly Depreciation Rate

= ((L: (cost installed/component life))/total

system cost)).

Building cost, including water and elec-

trical service installation, was valued at

$129.10 per square meter ($12/f t2) or

$39,744. The total production system

equipment cost was valued at an additional

$148,890 or approximately $3.42 of fixed

investment per kg of annual production ca-

pacity ($1.55/lb). The total investment cost

for the fish production system including the

TABLE

. Nursery system component cost and depre-

ciation estimates.

Com-

Cost ponent

System installed life

component

( 1

(Yr)

Fiberglass tanks

(3

@ 2,000)

Floating bead filter

Rotating biological contactor

Aeration or oxygen delivery sys-

Pipes and valves

Pumps (3 each @ 120)

Solenoid valves

&

timers

Heater and controls

Feed delivery system

tem

Total cost

6,000

4,000

4,000

1,500

400

360

1,000

230

1,000

18,490

15

10

7.5

15

5

3

5

5

5

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FISH

PRODUCTION COSTS IN RECIRCULATING SYSTEMS

199

1 m

FIGURE

. Simulated recirculatingfrsh production system layout,

8

growout tanks and 3 nursery tanks.

lation indicate that under the given condi-

tions, overall fish production cost will be

approximately $2.79/kg ($1.27/lb). Given

the same set of assumptions, except with

pure oxygen as the oxygen source, the cost

of production was estimated to be $2.86/kg

($1.30/lb). Subsequent modelling runs de-

termined that the cost of bulk oxygen would

need todecrease to $0.18/m3 ($0.51/100 ft3)

for the overall fish production cost to equal

that of the simulation of a system with at-

mospheric aeration. The cost of bulk liquid

oxygen in the United States ranges from ap-

proximately $0.09-$0.28/m3 ($0.25- 0.801

100 ft3)depending on the distance from the

source of liquid oxygen and quantity used.

The production costs simulated in the base

case analysis for the system as described are

generally too high to be economically com-

petitive in the wholesale fish fillet market.

Currently, only the local markets for live or

whole fresh tilapia on ice product would

support such production costs. However,

there are production and engineering im-

provements that could be made to improve

the economic viability ofthese systems. The

sensitivity analysis of the modelled system

that follows provides a means for estimating

the impact of changes within the system.

The results of the sensitivity analysis can be

used to assist in identifying areas in need of

further research and development where

improvements to recirculating systems can

have their greatest performance and eco-

nomic impacts.

System Sensitivity Analysis

total of 12 model input variables were

selected for study in the sensitivity analysis

of the simulated system. The 12 variables

are grouped and reported as biological vari-

ables, variable operating cost inputs, engi-

neering performance variables, and system

or fixed cost variables. Twelve modelling

“runs” were executed each time only one

of the variables was changed by 10%. In

most cases the variables were changed to

provide a simulated improvement in the

system performance. Some simulated vari-

able values, such as fish survival, used in

the base case simulation were so good (based

on North Carolina Fish Barn performance

experience) that a 10% change for the better

was judged as not being realistic. In these

cases the variables were changed for the

worse. In all cases, changes in fish produc-

tion costs were monitored. The overall re-

sults of the sensitivityanalysis can

be

viewed

in Table 7.

Biological variables. The model input

variables that directly affect the biological

performance of the cultured product are feed

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200 LOSORDO AND WESTERMAN

(

Production Cost = 2.79 /

kg

( 1.27 / lb)

FIGURE

.

Simulated base case production cost

of

tilapia in a recirculating system.

conversion ratio (FCR) and fish mortality

rate. When the FCR was reduced from 1.3

to

1.17

(a

10%

change) the overall cost of

producing tilapia changed by O.OSS/kg

($0.04/lb), a

3.2%

change. Analysis of the

production cost breakdown yielded inter-

esting results. In initiating he modelling run,

the user specifies the harvest size and total

weight of fish at harvest. When a lower FCR

is specified, the model simulates a more ef-

ficient conversion of feed to fish flesh and

calculates that less feed is used to produce

the same mass of fish. While one could ex-

pect the cost of feed per

kg

of fish to be less,

the simulation results also indicated that

changes in new water use, heating require-

ments, recirculation rate, aeration rate and

electric demand charges also occurred. While

the changes in water recirculation rate, new

water addition rate and aeration rate were

a direct result of less feed being added to

the system in the simulation (e.g., a lower

TAN production rate, lower nitrate nitrogen

production rate, lower oxygen consumption

rate), the change in heating requirement was

caused by the reduced water exchange rate.

The electric demand charge decreased as a

result

of

decreased water pumping and heat-

ing rates.

The mortality rate of fish is considered a

biological variable and was increased for the

sensitivity analysis by 10%. The 1

Ooh

change

in mortality rate yielded only a

2.3%

change,

or a O.O66/kg($0.03/lb) difference in over-

all production cost. The detailed simulation

results showed that although some changes

occurred in almost all production cost cat-

egories, the major changes occurred in feed

cost and fingerling cost per kgof production.

The reader should note that mortality was

simulated as a fractional constant loss over

the entire growth cycle. Losses later in the

growth cycle would have a greater effect on

production costs than losses occumng ear-

lier in the cycle. This type of mortality could

be simulated as a timed pulsed input van-

able change during a simulation run.

Operating cost variables. The modelled

operating cost input variables that were

changed (decreased

10%)

in this sensitivity

analysis were the cost of feed, electricity,

liquid oxygen, and labor. As in the previous

study (Losordo

1991),

the greatest change

in the cost of fish production among these

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FISH PRODUCTION COSTS IN RECIRCULATING SYSTEMS

input variables was caused by a change in

feed cost (2.1%). This may not be totally

unexpected as feed costs are the largest sin-

gle production cost in the base case simu-

lation (Fig.

3).

The sensitivity analysis in-

dicates that changes in the electricity rate,

labor rate of pay, and oxygen cost rate caused

changes in production costs of

1.5%, 1.4%

and 0.1% respectively.

These results, in concert with the FCR

sensitivity results, suggest that significant

production cost savings could be realized if

a feed that produced a better FCR were

available at a reduced cost. Feed manufac-

turers market improved feed conversion ra-

tios as a reason to pay more for specialized

feeds. The sensitivity analysis results

sug-

gest that production cost savings from a

1OYo

reduction in the FCR will in fact outweigh

the increase in production costs due to a

10%

increase in feed cost. In reality, im-

provements in the overall physical and bi-

ological performance of recirculating sys-

tems are realized when using higher quality

feeds. The model, as configured, could not

account for these changes.

It is also interesting to note that while

recirculating systems have been assumed to

be energy intensive, a 10% change in the

electric cost rate effected only a 1.5% change

in the total production cost of fish.

Engineering performance variables. The

modelled engineering performance vari-

ables that were investigated in this study

were recirculating pump efficiency, biolog-

ical filter efficiency, oxygen injection system

transfer efficiency, and aeration system ox-

ygen transfer efficiency. Surprisingly,

10%

changes in these variables produced no more

than a

0.5%

change in total production cost.

It may be hard to justify expending a great

deal of research and development time im-

proving the performance efficiency of each

of these components given these results. The

reader should not misunderstand this state-

ment, however. The authors are suggesting

only that biological filters that “remove”

100% of the ammonia nitrogen per pass, or

pumps that run at 80% efficiency, may not

TABLE Results

of

he simulation sensitivity analysis:

The change in production cost due to a

10

change

in

selected input variables.

% change in

Changed input variable production cost

System capacity

System cost

Feed conver sion ratio

Mortality rate

Feed cost

Cost o f electricity

Labor

rate

of

pay

Aeration efficiency

Pump efficiency

Cost of liquid oxygen

Filter efficiency

Oxygen transfer efficiency

4.1

3.5

3.2

2 .3

2.

1.5

1.4

0.5

0 . 2

0.1

0.1

0.1

be the key to economic viability. On the

other hand, a great deal of development ef-

forts are needed in improving the reliability

of biological filters. Indeed, the unexpected

failure of a biological filter or undetected

failure of an oxygen injection system can do

major damage in a short period of time to

the economic viability of a commercial fish

production system.

System andjixed cost variables. The re-

sults of this sensitivity analysis support the

findings described in Losordo 1 99 1).

Changes in either the system capacity or

overall system cost had greater impacts on

the total production cost than changes in

any other variable. A 10% increase in sys-

tem capacity was simulated without an as-

sociated change in investment. That is to

say that the physical production system was

not altered although the stocking rate (car-

rying capacity) was increased by

10%.

This

change caused a

4.19’0

decrease in the total

production cost. The reduction in the cost

of production due to an increase in carrying

capacity was essentially due to more pro-

duction for the same fixed investment. To

increase capacity, the model simulated pro-

portionally higher rates of use for feed, elec-

tricity, pumping, aeration and operating

capital. The savings come in the form of

more production for the same loan, equity

and labor costs.

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202 LOSORDO

AND WESTERMAN

Similarly,

a

10°h reduction in the overall

investment for the same production capac-

ity yielded a 3.5% change in production cost.

Insight into this finding may be gained by

reviewing the results from the base case pro-

duction analysis in Fig. 3. Over 4 l0h of the

costs associated with the production of the

fish are directly related to the initial in-

vestment cost of the system. In changing

the cost of the system, the calculated costs

of maintenance, depreciation, interest pay-

ments and cost of equity are all directly af-

fected.

Discussion

The simulated production results out-

lined above point out areas in production

technology where improvements can im-

pact the financial viability of recirculating

production systems. The reader should note

that the changes in the model input vari-

ables were accomplished without concur-

rent changes in the costs associated with

making these changes within the system. In

most cases improvements in any variable

will have an associated cost incurred in

making the change. For example, feeds that

provide a higher FCR will most likely cost

more. Similarly pumps that are more effi-

cient will also cost more.

The results of this study point to one area

that may provide substantial production cost

savings. The authors believe that these cost

savings can result from reducing the overall

cost of recirculating production systems

while maintaining component reliability and

longevity. These results can be viewed from

another perspective. While component de-

sign criteria are considered by performance

only, the results of the performance effi-

ciency sensitivity analysis suggest that this

alone is not of primary importance. The

results of this study suggest that perhaps

component performance should be com-

bined with the cost of ownership of these

components (which ultimately make up the

total cost of the system) into a “perfor-

mance/cost” factor. For example, a biolog-

ical filter could be evaluated according

to the total grams of ammonia nitrogen re-

moved per day per cost ofannual ownership

((g

TAN/yr) ($/yr)

= g

TAN/$). The costs

associated with ownership on an annual ba-

sis would include annual interest and equity

cost for the purchase of the component

combined with depreciation and mainte-

nance costs. Given a basic reliability factor,

one should seek to maximize the calculated

value of this variable. For example, the ro-

tating biological filter at the North Carolina

Fish Barn had an average TAN removal

capacity of 129 g/d during a study described

by Westerman et al. (1 993). Given an actual

purchase price of $3,000, and assuming a

component life of

7.5

yr, a maintenance cost

rate

of 5 ,

an interest rate of 13%, equity

interest rate of 9.5 , and a debt to equity

ratio of

1

, the performance/cost factor can

be estimated to be 53

g

TAN/$. The floating

bead filter utilized at the North Carolina

Fish Barn removed an average of

46 g

TAN/d over the same test period. With an

actual purchase price of $3,200, an assumed

component life of 10 yr and similar eco-

nomic cost rate assumptions, the perfor-

mance cost factor would be calculated to be

20

g

TAN/$. Additionally a fluidized bed

sand filter was evaluated over the same pe-

riod during the study (Westerman et al.

1993). The monitoring results indicated that

an average of 37

g

TAN/d was oxidized to

nitrite. Given the actual purchase price of

$1,000, a 10 yr life and similar economic

cost rate assumptions, the performance/cost

factor was calculated to be

5 1 g

TAN/$. If

it is assumed that these components have

similar performance reliabilities, then the

fluidized bed filter or the RBC filter would

be a better value based upon this evaluation

criterion. However, the reader should not

lose sight of the fact that the floating bead

filter performed a suspended solids removal

function as well as nitrification. To “nor-

malize” the results of this analysis, perhaps

the performance/cost factor must account

for all functions to be performed by the fil-

tration system.

While the ultimate criteria for evaluating

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FISH PRODUmION COSTS N RECIRCULATINGSYSTEMS

203

the cost of producing fish in a system is the

cost per unit weight of production, evalu-

ation criteria as outlined above may provide

designers with economic measures to com-

pare individual components and compo-

nent performance. Engineering perfor-

mance and economic performance must be

balanced to provide an optimum produc-

tion system for the specific site, species, and

operating personnel requirements.

Conclusions

The challenges for recirculating systems

designers and engineers are many. Recir-

culating systems and system components

must be designed to be manufactured at a

lower cost or to utilize components that are

currently available to other industries at

lower prices. Where possible the carrying

capacity of a system must be increased with-

out increasing cost or sacrificing system re-

liability.

The following specific conclusions may be

reached as a result of the data presented in

this study:

1) Given the assumptions of the base case

simulation, the cost of producing a kilogram

of tilapia in the small recirculating system

described is estimated to be

$2.79

( 1.271

lb).

2) Changes in the engineering perfor-

mance efficiency of the system components

did not greatly change the total production

cost.

3) Changes in the feed cost had the great-

est impact on production cost of all of the

operational variables investigated.

4) Improvements in the feed conversion

ratio can have a significant impact on pro-

duction costs. However, these savings could

be offset by associated increases in feed

prices.

5)

The greatest gains to be realized in im-

proving profitability are those associated

with increased production capacity or de-

creased system investment cost.

Acknowledgments

The research and demonstration program

in recirculating aquaculture technology at

North Carolina State University is sup-

ported by the Agricultural Research Service

and the Cooperative Extension Service of

the College

of

Agriculture and Life Sciences

of North Carolina State University and the

Energy Division of the North Carolina De-

partment of Commerce.

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