Efecto de La Fuente de C en Biofloc

8/18/2019 Efecto de La Fuente de C en Biofloc

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Effects of carbon source and particle size on nitrogen

cycling in aggregated “Bio-Floc” microbial communities Chelsea Westra

Hampshire College893 West Street, Amherst MA 01002

Advisor: Dr. Joe Vallino

Marine Biological Laboratory7 MBL St Woods Hole, MA 02543

Semester in Environmental Science

Independent Project, 2013


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AbstractThe addition of a carbon source in aquaculture systems can stimulate microbial flocs which take

up fish waste and subsequently convert it into a protein source for fish. Microbes utilize nitrogenin different ways depending on the carbon source used; past studies have reported higher rates of

N immobilization in flocs treated with glycerol rather than glucose. The proposed hypothesis

aims to investigate the effects C sources may have on respiration rates, which would affect Nconversion pathways. In this experiment I observed the effects of C source and particle size onrespiration rates and nitrogen cycling. I measured oxygen uptake rates (OUR) and N forms NH4,

NO3, TDN, and PON to complete a mass balance and find N2 by difference. I also ran a proteinassay to confirm higher protein concentration in the glycerol treatment. While results replicated

past studies and the glycerol treatment increased protein content, differences between respiration

rates and denitrification rates were difficult to determine between treatments during the given

time period. Results did show significant protein increase and NH4 removal by glycerol andsuggests further research on the mechanism behind this. Microscopy images show stark

differences in floc composition between treatments, with hyphal growth dominating glyceroltreatments, which may be key to understanding the role of carbon in nitrogen uptake.

Keywords: Biofloc technology, organic carbon source, bioreactor, nitrogen removal,

denitrification process, protein concentration, bacterial aggregates

Introduction

Flocculated microbial communities — aggregated microbial communities

composed of heterotrophic bacteria, dead cells and polymers — have long been

implemented in biological wastewater treatment, and this technique is now being used to

treat nutrient buildup in aquaculture systems. Biofloc Technology (BFT) aquaculture is

the cohabitation of microbial communities and fish that aims to solve two major issues in

fish production: wastewater treatment and protein addition. Conventional aquaculture

requires constant replacement of freshwater to prevent toxic waste buildup, utilizing a

scarce resource and producing polluted effluent (Schryver et al 2008). The second major

input into aquaculture systems is the need for high-quality protein, and fisheries are

generally dependent on external fishmeal to provide necessary nutrients (Tacon and

Metian 2008). As the aquaculture industry continues to expand, pressure on fishmeal

production will increase at an unsustainable rate (Hardy 1996; Carter & Hauler 2000).


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the system could promote the presence of anoxic pockets within floc. These anoxic

micro-niches within floc could support denitrifying bacteria that produce N2 gas, an

anaerobic process that removes N from the system. This export of N from the system into

the atmosphere leads to lower immobilization rates and decreased protein within flocs.

Particle size could also affect denitrification, as larger particles are more likely to host

anoxic pockets and promote N2 production.

My project observes the relationship between respiration rates and N conversion.

My hypothesis centers around the idea that glucose addition leads to higher respiration

rates than glycerol, increasing denitrification rates and N export from the system. I also

manipulate particle size to observe N cycling and respiration rates with varied particle

size.

MethodsI set up eight two-liter graduated cylinders each with a working volume of 1.5

liters. Four treatments were run in duplicate with two carbon sources, glucose and

glycerol, and small and large particle size. Weighted air stones placed at the bottom of

each graduated cylinder ensured constant suspension of floc particles and aerobic

conditions. The bioreactors were kept in a dark growth chamber to discourage growth of

photosynthetic organisms and temperature was kept at 30 C.

The systems were initially inoculated with 100 mL of biofloc from a BFT tilapia

system at the Woods Hole Oceanographic Institution. Initial N concentration of each

system was 1.8 mM NH4.

The systems were run as pulse chemostat, which entailed 10% volume exchange

daily. Added media was composed of 18 mM (NH4)2SO4 and corresponding C


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concentration to attain a C:N ratio of 11. KH2PO4 and 60 mL of water from John’s Pond

in Falmouth, MA were also added to provide trace minerals and avoid nutrient

limitations. I monitored pH three times a day, adding 1 N HCl and sodium bicarbonate as

needed to maintain pH levels around 8.5. I used an immersion blender to agitate the

unflocculated systems twice daily to discourage flocculation and decrease particle size.

Removed water was filtered through ashed 47 GF/F filters. Filters were dried at 50 C for

24 hours and stored in a desiccator. Ammonium samples were preserved with 5N HCl

and samples were frozen for nitrate (NO3) and Total Dissolved Nitrogen (TDN) analyses.

Samples were periodically analyzed under a Zeiss microscope to determine particle size

distribution.

I determined oxygen uptake rates (OUR) using a WTW Dissolved Oxygen probe

throughout the experiment. Rates were determined by monitoring O2 decrease in the

absence of oxygenation, which was collected 5 hours after media input.

I used uptake rates to determine steady state and nutrient analyses were focused

on 5 days, from November 27 to December 2. GF/F filters were run on the CHN

elemental analyzer (Perkin-Elmer) to determine particulate organic N and C.

NH4 analysis followed methods modified from Strickland and Parsons and

samples were run on the Shimadzu UV-1601 spectrophotometer at 200:1 dilution

(Strickland and Parsons 1972). NO3 was run on the Lachat via automated colorimetric

flow injection analysis following the QuikChem Method at 20:1 dilution (Diamond

2008). These two analyses comprised dissolved inorganic N measurements.


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To determine TDN, I added potassium persulfate to samples diluted 50:1, which

were then autoclaved for 1.5 hours. Once nitrogen was fully oxidized into nitrate,

samples were run on the Lachat using nitrate methods listed above.

I determined protein concentrations by sonicating samples for three minutes to

encourage cell lysis for a protein assay (Sigma Aldrich 51254). Samples were dyed with

Coomassie Brilliant Blue G (CBB) and run in a 96 well microplate on the Spectramax

Plus 384 with bovine serum albumin (BSA) as the standard.

Respiration rates were determined from rate of oxygen uptake by finding the

slope of initial curve, as described by Hagman and Jansen (2007) (Fig. 1). N mass

balance was completed using PON, DIN and TDN measurements. N2 production was

found via the difference. Rates of ammonium uptake, nitrification, denitrification and N

immobilization were extrapolated from this data given Equations 1 & 2.

Results

Both carbon sources were able to uptake the majority of ammonium. Figure 2

shows projected ammonium concentrations given a sterile system scenario, and

treatments had converted >11 mM NH4 at initial analysis. Flocculated glycerol had the

highest removal rate, with an average of 95.4 0.4% NH4 removal over the 5 day period.

Flocculated glucose removed the least NH4 with an average of 88.3 1.9% NH4 removal.

Ammonium concentrations were therefore lowest in the flocculated glycerol treatment

throughout the 5 day sampling period, with an average ammonium concentration of 0.66

0.05 mM NH4 (Fig. 3). Flocculated glucose systems had the highest initial ammonium

levels and displayed ammonium buildup, increasing from 1.37 to 2.03 mM over 5 days.


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Protein concentrations are displayed in Figure 4. Unflocculated glycerol treatment

had the highest protein content, with 135.5 15.5 µg/ml. Unflocculated treatments in

both C sources displayed higher protein content than their flocculated counterparts — 33.8

8 compared with 88.3 23.5 µg/ml for glucose and 65.9 9.7 to 135.5 15.5 µg/ml

for glycerol.

Respiration rates throughout the experiment and within the steady state period are

displayed in Figures 5a and 5b. Although initial glucose respiration rates were

significantly higher than glycerol — 177.2 17 mmol O2 liter -1 d-1 in glucose-F compared

with 21.5 7.5 mmol O2 liter -1 d-1 on day 1 — respiration rates varied greatly as

microcosms established. Respiration rates ranged from 12.1 1 to 77.5 56.3 mmol O2

liter -1

d-1

during the analysis period — fluctuations between duplicates and microcosms did

not allow for any detectable trends or distinctions between treatments.

Particulate organic N concentration was significantly higher in flocculated

glycerol than glucose, with an average 241.5 15.4 compared with 162.4 38.8 µg/ml

(Fig. 6). Unflocculated glucose treatments had the lowest concentrations with an average

59.3 21.1 µg/ml. Molar C:N ratios were lowest in glycerol treatments and decreased

throughout the analysis in all treatments (Fig. 7).

Nitrate levels were nearly undetectable during the sampling period, although were

initially highest in glycerol treatments before decreasing over time (Fig. 8). Total

dissolved N concentrations reflected NH4 data, suggesting majority of dissolved N was in

the form of NH4.

N mass balance results derived from rate calculations are shown in Figure 9.

Negative NH4 rates denote ammonium uptake, while positive PON and N2 rates convey


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N immobilization and denitrification rates. All treatments show consistent ammonium

uptake and occurrence of denitrification. Unflocculated glycerol treatments had highest

rates of N immobilization with 1.57 mmol PON liter -1 d-1. Figure 10 shows the

relationship between denitrification rate and protein content.

Particle size distribution is compared between treatments in Figure 11. Particles

sized between 101-300 µm were most abundant in flocculated glucose treatments,

whereas glycerol treatments had more particles in the 401-600 µm range (Fig. 11a).

Unflocculated treatments had similar distributions between C treatments and were

clustered between 0-200 µm (Fig. 11b). Microscopy images are displayed in Figures 12

and 13 to show differences in floc composition between carbon sources.

Discussion

All systems proved to be efficient at NH4 removal. Decreasing C:N ratios among

all treatments shows increasing N immobilization throughout the sampling period.

Results from the protein assay confirm that findings in Crab et al (2010) were replicable

and glycerol had higher protein concentrations. Particulate N data also supports this, as

glycerol treatments had higher levels of N accumulation. Glycerol also displayed higher

rates of NH4 uptake than glucose. This suggests that glycerol addition promotes increased

microbial N uptake and immobilization.

While glucose initially had higher respiration rates, it is difficult to make any

conclusive remarks given the variability between duplicates and treatments. The systems

may have still been reaching steady state, and running the experiment for longer might

produce more clear trends. Although it is not possible to determine a relationship between

respiration and denitrification rates, results from mass balance calculations suggest


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denitrification is likely occurring in most treatments. This supports the idea that

anaerobic microniches are present within the floc. However, variations throughout

treatments suggest that the C source did not have a large effect on denitrification rates.

Although total Particulate N was higher in flocculated treatments, protein

concentration and immobilization rates were higher in unflocculated treatments for both

C sources. Despite the most total NH4 removal in flocculated glycerol, unflocculated

glycerol had the highest N immobilization rate, highest protein concentration, and lowest

denitrification rates. This could support the current hypothesis; smaller particle size might

discourage development of anaerobic pockets, thereby decreasing denitrification rates.

Most related research has been done on sequencing batch reactors (SBRs) in

wastewater treatment plants that support aerobic/anaerobic stages, so future research

could focus on micro-habitats within floc that are influenced by microbial respiration

rather than external oxygen supply.

The most obvious difference between carbon sources was observational data

taken from microscopy analysis. Glycerol treatments showed hyphal structures

dominating flocs that were mostly absent in glucose. Crab et al (2010) suggest that C

sources may affect microbial composition which affects N immobilization; glucose may

promote floc that expend more energy in producing exopolysaccharides while glycerol

encourages bacteria that immobilize more N as protein. Future research should

concentrate on the effects of C sources on floc community composition.

Understanding how small differences among the carbohydrate source could

greatly affect community composition would give insight into nutrient cycling dynamics


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within microbial communities. This would help inform decisions to optimize the use of

flocculated microbes for biological remediation of wastewater.

AcknowledgementsFirstly to Joe Vallino for all the guidance and troubleshooting along the way. The project

wouldn’t have materialized without the knowledge and inoculant from Bill Mebane, whoalso helped keep the big picture in mind. Thanks to Sarah Nalven and Rich McHorney

because I don’t think I would have finished without their support and reassurancethroughout. Alice Carter and Fiona Jevon for engaging in biofloc discussions towards the

end and helping me pull it all together. Thanks to Ken Foreman for directing such a great program and to everyone involved in the SES program.

References:

Avnimelech, Y. 2009. Biofloc Technology: a practical guidebook. World AquacultureSociety. pp 1-42

Carter, C G & Hauler R C. 2000. Fish meal replacement by plant meals in extruded feedsfor Atlantic salmon, Salmo salar L. Aquaculture 185, 299-311.

Crab R, Defoirdt T, Bossier P, Verstraete, W. 2012. Biofloc technology in aquaculture: beneficial effects and future challenges. Aquaculture. 351-356.

Crab R, Chielens B, Wille M, Bossier P, Verstraete W. 2010. The effect of differentcarbon sources on the nutritional value of bioflocs, a feed for Macrobrachium

rosenbergii postlarvae. Aquaculture Research. 41, 559-567Diamond D. 2008. Determination of nitrate and/or nitrite in brackish or seawater by flow

injection analysis colorimetry. Lachat Instruments. Loveland, CO.Hardy, R. W. 1996. Alternate protein sources for salmon and trout diets. Animal Feed

Science and Technology.59, 71-80.Hagman, M & Jansen J. 2007. Oxygen uptake rate measurements for application at

wastewater treatment plants. Water and Environmental Engineering. 63, 131-138.Paul, E.A., van Veen, J.A., 1978. The use of tracer to determine the dynamic nature of

organic matter. Proceedings of the 11th International Congress of Soil Science,Edmonton, Canada. 3, 61 – 102.

Schryver, P D, Crab R, Defoirdt T, Boon N, Verstraete W. 2008. The basics of bio-flocstechnology: the added value for aquaculture. Aquaculture 277, 125-137.

Strickland, J D H & Parsons T R. 1972. A Practical Handbook of Seawater Analysis.Fisheries Research Board of Canada. 2

nd ed. Ontario, Canada.

Tacon A G, Metian M. 2008. Global overview on the use of fish meal and fish oil inindustrially compounded aquafeeds: trends and future prospects. Aquaculture.

285, 146-158.


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Fig. 1 Oxygen data from Glyc-UF2 on Dec 2 exemplifies how oxygen uptake rates (OUR) were

determined. Dissolved oxygen concentration generally decreased in a linear fashion so that theslope constituted OUR.

y = -0.3144x + 6.6458R² = 0.9993

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6.1

6.26.3

6.4

6.5

6.6

6.7

0 0.5 1 1.5 2 2.5 3

D i s s o l v e d O x y g

e n ( m g / l )

Time (min)


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Fig. 2 Projected NH4 concentration in sterile scenario where no ammonium is taken up.

0

2

4

6

8

10

12

14

16

18

13-Nov 18-Nov 23-Nov 28-Nov 3-Dec

N H 4 c o n c e n t r a t i o n ( m M )


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Fig. 3 Actual NH4 concentrations across treatments throughout the steady state period.

0.00

0.50

1.00

1.50

2.00

2.50


N H 4 C o n c e n t r a t i o n ( m M

)

Glu-F

Glu-UF

Glyc-F

Glyc-UF


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Fig. 4 Results from the protein assay show higher concentrations in unflocculated treatments.

0

20

40

60

80

100

120

140

160

Glucose Glycerol

P r o t e i n c o n c e n t r a t i o n ( µ g / m l )

Flocculated

Unflocculated


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Fig. 5 Respiration rates throughout the entire experiment (5a) and during steady state analysis

(5b).

0

20

40

60

80

100

120

140

160

180

200


R e s p i r a t i o n R a t e ( m m o l O 2 l i t

e r - 1

d a y - 1 )

Glucose-F

Glucose-UF

Glycerol-F

Glycerol-UF

0

20

40

60

80

100

120

140

160

26-Nov 28-Nov 30-Nov 2-Dec

R e s p i r a t i o n R a t e ( m m o l O 2 l i t e r - 1 d

a y -

1 )

Glucose-F

Glucose-UF

Glycerol-F

Glycerol-UF


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Fig. 6 Particulate N concentrations across treatments.

0

50

100

150

200

250

300

26-Nov 27-Nov 28-Nov 29-Nov 30-Nov 1-Dec

P O N ( µ g / m l )

Glucose-F

Glucose-UF

Glycerol-F

Glycerol-UF


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Fig. 7 Molar C:N ratio throughout steady state which shows increasing N content over time.

0

1

2

3

4

5

6

7

8

9

10


M o l a r C : N r a t i o

Glucose-F

Glucose-UF

Glycerol-F

Glycerol-UF


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Fig. 8 Nitrate levels were very low throughout steady state in all treatments (note concentrations

are in µM).

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6


N O 3 c o n c e n t r a t i o n ( µ M )

Glucose-F

Glucose-UF

Glycerol-F

Glycerol-UF


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Fig. 9 Visual representation of the N mass balance, showing steady ammonium uptake rates anddenitrification likely occurring in all treatments.

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

Glucose-F Glucose-UF Glycerol-F Glycerol-UF

Δ N

( m m o l N l i t e r - 1 d

a y - 1 )

ΔNH4

ΔNO3

Δ PON (Immobilization)

ΔN2 (Denitrification)

Δ DON


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Fig. 10 The relationship between denitrification rates and protein content is unclear, but glycerol-

UF displayed the highest protein concentration and lowest denitrification rate.

0

0.05

0.1

0.15

0.2

0.25

0 50 100 150

D e n i t r i f i c a t i o n r a t e ( m m o l N 2 l - 1 d

- 1 )

Protein concentration (µg/ml)


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Fig. 11 Particle size distributions across treatments. 11a shows the differences in size betweenflocculated glucose and glycerol, while 11b displays the particle size uniformity in unflocculated

systems.

0

2

4

6

8

10

1214

16

18

20

F r e q u e n c y

Particle Size (µm)

Glucose-F

Glycerol-UF

0

5

10

15

20

25

30

35

40

F r e q u e n c y

Particle Size (µm)

Glucose-UF

Glycerol-UF


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Fig. 12 Microscopy image of flocs with glucose addition.


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Fig. 13 Flocs in glycerol treatments were dominated by hyphal structures that were mostly absentwith glucose addition.

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