1. Samir Kumar Khanal, University of Hawaii at Manoa
Kartik Chandran, Columbia University
Clyde Tamaru, University of Hawaii at Manoa
Hye-Ji Kim, Purdue University
USDA-AFRI PD Meeting, Washington, D.C., October 12-13, 2016

2. Aquaponics is a soilless system in which recirculating aquaculture
is integrated with a hydroponic system.
N2O

3. 3
Research objectives
1. Quantify the impact of physical and chemical variables on
nitrogen transformations in an aquaponic system. 
2. Evaluate the transformations of different forms of nitrogen in an
aquaponic system under different conditions.  
3. Examine the ecology of functionally important living species and
assess microbial contributions to nitrogen transformations in an
aquaponic system. 
4. Investigate the greenhouse gases emissions from an aquaponic
system, with particular emphasis on nitrous oxide (N2O) emission. 

4. 4
Pak choi Lettuce
Tilapia

5. 5
Tomato Chive

6. 2-stage biofilter
(20 L)
Aquaponic system
pH was controlled in
a range of 6.8-7.2 by
adding Ca(OH)2 and
KOH solution.
Two-stage biofilter
Grow bed
Fish tank
Air
supply
Feed
Down-flow
with partial
aeration
Up-flow
Sediment
Fish tank (330 L)
Grow bed (300 L)
DO in fish tank was
about 6-7 mg/L.

7. 7
2
4
6
8
0 7 14 22 29 36
DO(mg/L)
Day
HLR 1.0 m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet) 2
4
6
8
0 7 14 22 29 36
DO(mg/L)
Day
HLR 1.5 m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet)
2
4
6
8
0 7 14 21 28 35
DO(mg/L)
Days
HLR 2.0 m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet)
2
4
6
8
0 7 14 21 28 35
DO(mg/L)
Days
HLR 2.5m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet)
DO dropped significantly in biofilters, due to sediment accumulations
2
4
6
8
0 7 14 21 28 35
DO(mg/L)
Days
HLR 2.0 m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet)2
4
6
8
0 7 14 21 28 35
DO(mg/L)
Days
HLR 1.5 m/d
Fish tank
Biofilters (outlet)
Grow bed (outlet)
Significantly different (Growbed outlet)
Not significantly different
Not significantly different

8. 8
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Feed
Fish
Feces
Sediment
NO3-Water
Roots
NO3-Roots
Stems
NO3-Stems
Leaves
NO3-Leaves
Fruits
NO3-Fruits
δ15N(‰)
Pak choi
Lettuce
Chive
Tomato
Natural abundance δ15N of bulk nitrogen and NO3
-
Σ (N x δ15N)before = Σ (N x δ15N)after
- Assimilation and redox pathways were identified by the isotopic fractionations.
However, The results were isotopically impossible. There should be at least one output
that has δ15N below the δ15N value of the feed (< 5.2 ‰) (Robinson, 2001).
- Gaseous nitrogen loss via denitrification caused the δ15N of gas loss below 5.2 ‰.
fN.Mf =
𝑑
𝑑𝑡
(CTAN + CNO2-N + CNO3-N + Corg-N)V + Nveg/T + Nfish/T + Nsed/T + Nloss/TMass balance:
Isotopic mass balance:

9. 17.5
18.0
18.5
19.0
19.5
20.0
20.5
0 3 6 9 12
δ15N(‰)
Days
DO affected denitrification and nitrogen loss via denitrification
Low DO
High DO
15.0
16.0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
0 3 6 9 12
δ15N(‰)
Days
Actual
No feeding
No denitrification
Note:
1. Denitrification caused the
enrichment in 15N and increase in
δ15N of nitrate.
2. Feed lowered δ15N of nitrate
during denitrification , but
denitrification was identified.

10. Parameters
Conditions
Feed 25g/d Feed 20 g/d Feed 15 g/d
1.5 m/d 1.0 m/d 1.5 m/d 0.25 m/d 1.5 m/d 0.5 m/d
TKN (mgN/L) 8.2 (2.9)* 10.6 (2.7) 9.4 (0.8) 8.9 (0.9) 10.3 (1.4) 11.5 (0.9)
TAN (mgN/L)
0.69
(0.37)
1.10
(0.29)
0.52
(0.16)
0.59
(0.15)
0.69
(0.09)
0.89
(0.10)
NO2
- (mgN/L)
0.155
(0.061)
0.255
(0.087)
0.303
(0.052)+
0.616
(0.161)+
0.227
(0.062)
0.284
(0.054)
NO3
-
accumulation
rate
(mgN/L/d)
0.723
(0.129)
0.534
(0.074)
0.814
(0.011)
0.996
(0.173)
0.905
(0.080)
0.897
(0.056)
COD (mg/L) 89.0 (8.5) 91.3 (6.4) 58.6 (4.0) 65.2 (4.5) 61.6 (4.3) 64.2 (4.2)
This is mean value of 15 samples; *represents standard deviation and + represents
significant difference. Statistical analyses of the collected data were carried out using
an analysis of variance (one-way ANOVA) at a confidence level of α = 0.05
Nitrite oxidation rate dropped at low HLR (below 0.25 m/d), but
ammonia oxidation was still active

11. HLR (< 0.1 m/d) decreased TAN oxidation rates
HLR (< 0.25 m/d) decreased nitrite oxidation rates
0.0
0.5
1.0
1.5
0 7 14 21 28
NO2
-(mgN/L)
Days
0.1 m/d
1.5 m/d
0.0
0.2
0.4
0.6
0 7 14 21 28
NO2
-(mgN/L)
Days
0.25 m/d
1.5 m/d
0.0
1.0
2.0
3.0
4.0
0 7 14 21 28
TAN(mgN/L)
Days
0.1 m/d
1.5 m/d
0.0
0.5
1.0
1.5
2.0
2.5
0 7 14 21 28
TAN(mgN/L)
Days
0.25 m/d
1.5 m/d
Not significant different
Significant different
Significant different Significant different

12. pH (<6.0) decreased TAN oxidation rates. pH 5.2 inhibited TAN oxidation
At low pH (<6.0), decrease in TAN oxidation rate caused the accumulation of TAN
and lowered nitrite substrate in nitrite oxidation. This does not mean nitrite
oxidation was improved at low pH.
0
5
10
15
20
0 7 14 21 28 35
TAN(mgN/L)
Days
pH 5.2
pH 6.8
0
2
4
6
8
0 7 14 21 28 35
TAN(mgN/L)
Days
pH 6.0
pH 6.8
0.0
0.1
0.2
0.3
0.4
0 7 14 21 28 35
NO2
-(mgN/L)
Days
pH 5.2
pH 6.8
0.0
0.1
0.2
0.3
0.4
0 7 14 21 28 35
NO2
-(mgN/L)
Days
pH 6.0
pH 6.8
Significant different
Significant differentSignificant different
Significant different

13. 130
150
170
190
210
0 5 10 15 20 25 30 35 40
NO3
-(mgN/L)
Days
weekly drained
monthly drained
Sediment draining improved NO3
- accumulation and reduced N loss in aquaponics
0
50
100
150
200
250
0 15 30 45 60 75 90
Nitrateconcentration
(mgN/L)
Days
Chive
Lettuce
Pak choi
Tomato
Nitrate accumulation/consumption for different plant species in aquaponicsTwo-stage biofilter
Grow bed
Fish tank
Air
supply
Feed
Down-flow
with partial
aeration
Up-flow
Sediment

14. Root system
Root surface
area
Pak choi Lettuce Chive Tomato
cm2/plant
724
(251)
474
(109)
227
(104)
6.01 x 104
(1.71 x 104)
This is mean value of 24 samples; *represents standard deviation
Pak choi
Lettuce Chive Tomato

15. 15
First month (NO3
- accumulation)

16. 16
Third month (NO3
- depletion)

17. 17
Nitrite
Oxidation
Nitrogen loss
(denitrification)
Nitrate
accumulation&
depletion rate
DO
Plant NUE
Feed
consumption
Feed Feed DO
DO ≤ 3.5 mg/L
Balance input
and output
HLR ≤ 0.25 m/d
DO ≤ 3 mg/L
TAN
Oxidation
TAN
Accumulation
pH ≤ 6.0pH ≤ 5.2
Reduced
Nloss
HLR ≤
0.1 m/d
Balance between input and outputs
Plant
species
Tomato > Lettuce &
Pak choi > Chive
pH DrainingHLR
Objective #1: Impact of physical and chemical variables
Increase
nitrate
accumulation

18. 18
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pak choi Lettuce Chive Tomato Input Input2
Nitrate input
Fish feed
N loss
Plant biomass
Nitrate accumulated
Sediment
Fish biomass
Contribution of nitrogen products by mass balance in aquaponic systems,
operated at HLR of 1.5 m/d, feeding rate of 35 g/d and high DO (~7 mg/L).
- NO3
- accumulation served as nitrogen output (NO3
- uptake rate < NO3
- generation rate) and
nitrogen input (NO3
- uptake rate > NO3
- generation rate).
- Nitrogen loss was found in aquaponic systems.

19. 19
TAN Nitrite
Nitrate
N2O & N2
(N loss)
Org N in
fish
Org N in
sediment
Org N in
plants
Fish
Nitrate
accumulation
Feed
DO
Plant
species
pH
HLR
Objective #2 Transformations of different forms of nitrogen
Output
Parameters affecting N transformations
Other N forms

20. 20
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
Feed
Fish
Feces
Sediment
NO3-Water
Roots
NO3-Roots
Stems
NO3-Stems
Leaves
NO3-Leaves
Fruits
NO3-Fruits
δ15N(‰)
Pak choi
Lettuce
Chive
Tomato
3. Ecology of functionally important living species
• Nitrate reductase could occur in the plant organs and the nitrate reduction occurs after the
translocation from recirculating water to leaves (Black et al., 2002).
• High efflux of NO3
- occurred in the root zone of plants, and NO3
- concentration exceeded the
plant requirements (Evans, 2001); resulting to the accumulation of NO3
-.
• This nitrate in recirculating water could subsequently cause the high nitrogen loss via
denitrification by nitrifiers (Ryabenko, 2013).
• Microbial results are still required to support the ecology and microbial contributions to
nitrogen transformations.

21. 21
Nitrifying
bacteria
Types of root
Pak choi Lettuce Chive Tomato
EU bacteria 7.57 x 109 2.91 x 1011 1.96 x 1010 2.32 x 1010
Nitrobacter spp. 7.02 x 106 4.09 x 106 6.88 x 106 8.84 x 106
Nitrospira spp. 1.16 x 109 7.74 x 108 9.70 x 108 3.22 x 109
Abundances of bacteria in different root systems
(Condition: HLR 1.5 m/d and pH 6.8)
(unit: copies).
High relative abundances of EU bacteria over Nitrobacter spp. and Nitrospira spp.
suggested the high abundance of denitrifiers, which contributed to nitrogen loss in
aquaponic systems.

22. 22
Nitrifying
bacteria
Tomato-based aquaponics Pak choi-based aquaponics
Root surface Water Root surface Water
AOB
3.97 ± 1.18
x 1011
6.85 ± 0.85
x 108
8.67 ± 0.71
x 1010
3.26 ± 0.79
x 109
NOB
Nitrobacter
spp.
4.13 ± 0.27
x 1012
4.49 ± 1.57
x 108
7.39 ± 0.26
x 1011
2.47 ± 0.05
x 1011
Nitrospira spp.
1.31 ± 0.06
x 1011
3.66 ± 0.65
x 108
3.59 ± 0.15
x 1010
4.55 ± 0.08
x 109
Abundance of nitrifying bacteria in different aquaponics
(unit: copies)
Higher NUE were obtained in tomato-based aquaponics, due to higher abundance
of nitrifying bacteria on root surface.
(Hu et al., 2015)

23. 23
4. Nitrous oxide (N2O) emission from fish tanks
Aquaponic types
N2O emission
(mgN/d)
N2O conversion
(%)
References
Tomato-based
aquaponics
58.3 (14.9) 1.5 (Hu et al., 2015)
Pak choi-based
aquaponics
72.5 (13.2) 1.9 (Hu et al., 2015)
Chive-based
aquaponics
29.6 (0.4) 1.2 Our study
Tomato-based
aquaponics
17.2 (7.7) 0.7 Our study
Aquaponics
without plants
11.9 (10.2) 0.5 Our study
We found that higher N2O emission from biofilters than that in the fish tanks.
* denotes standard deviation

24. 24
Summary
• The NO3
- accumulation in recirculating water occurred when NO3
- exceeded
the amount that the plants could utilize. NO3
- depletion suggested the
insufficient nitrogen input.
• When the NO3
- accumulation occurs, reducing the feeding rate can increase
NUE and decrease the denitrification in the systems.
• The growth of plants was dependent on HLR of 0.25 to 2.5 m/d; however,
NO2
- and TAN oxidizing rates were significantly dropped at HLR of 0.25 m/d
and 0.10 m/d, respectively.
• Low pH (< 5.2) inhibited ammonia oxidation, leading to TAN accumulation.
• The nitrogen mass balance and the isotopic mass balance suggested that
denitrification, affected by DO at the inlet of biofilters, was the major factor
of nitrogen loss in the floating-raft aquaponic systems.
• To reduce the nitrogen loss in aquaponic systems, higher rate of sediment
draining and higher plant-to-fish ratio are recommended.

25. 25
On-going research
3. Examine the ecology of functionally important living species and assess microbial
contributions to nitrogen transformations in an aquaponic system
4. Investigate the greenhouse gases emissions from an aquaponic system, with
particular emphasis on nitrous oxide (N2O) emission
• Quantitative polymerase chain reaction (qPCR) targeting:
• Eubacteria, ammonia monooxygenase subunit A (amoA), Anaerobic
ammonia oxidizing bacteria (AMX), Nitrospira spp., Nitrospira spp. and
Nitrobacter spp.
• 16S rRNA
• Measurement of N2O emissions from aquaponic systems
• Development of strategies to minimize N2O emission
2. Evaluate the transformations of different forms of nitrogen in an
aquaponic system under different conditions
• Labeling isotope study using ammonium 15N sulfate

26. Student training/Extension/Dissemination activities
• One Ph.D., one undergraduate and three high school students have been
trained.
• Aquaponic facility tour for farmers, students from Environ. Science, Nagasaki
University (Japan) and staffs from Kapiolani Community College (Hawaii).
Symposium:
Wongkiew, S. and Khanal. S.K. “Nitrogen transformations in floating-raft
aquaponic systems”, Poster presentation, 28th Annual CTAHR Symposium,
University of Hawaii at Manoa, April 8th, 2016. BEST POSTER AWARD.
Publications:
• Wongkiew, S., Hu, Z., Chandran, K., Lee, J.W., and Khanal, S.K. Nitrogen
transformations in aquaponic systems: A review. Aquacultural
Engineering (submitted).
• Wongkiew, S., Popp, B.N., Kim, H.J., and Khanal, S.K. Nitrogen transformations
in aquaponics: evaluation of physical and chemical factors (ready for
submission).

27. 27
Acknowledgments
• Ryan Kurasaki
• Bradley Kai Fox, Mari’s Gardens
• This project is being supported by Agriculture and Food Research
Initiative Competitive Grant no. 2013-67019-21376 from the
USDA National Institute of Food and Agriculture.