1. Model-based Irrigation Control
for Potted Plant Production in
Nutrient-flow Wick Culture
Plant Environment Control Lab.
Sung Kyu Kim
2. Concept of radiation-based irrigation system
Radiation-based irrigation system Timer-based irrigation system
3. Water movement in NFW system
Qp
Q = Qp + Qm
Qm
Wc = Wp - Q
Wc
Q = total water loss
Wp Qp = water loss from the plant
Qm = water loss from the media
Wp = water absorption
Wc = water content
4. Models for evapotranspiration and water absorption
Variable Model R2 Pr > F
Evapotranspiration 0.000162×(LA+2.5275×EA)×
(VPD+0.000352×RAD-0.548) 0.9106 <.0001
(ET)
×e-0.124514×Wi
Absorption 76.35 - (76.35 – Wi)×℮-0.000261×Wi × Ti 0.9476 <.0001
(WP)
WI = Initial water content, TI = irrigation time, LA = leaf area, EA = shade area,
VPD = vapor pressure deficit, RAD = radiation integral, Water holding capacity = 76.35
WP ET WP TI, WI
ET LA, EA, RAD, VPD
Modeling
5. Objectives
Development of automatic irrigation system
Application of model-based irrigation system
Characteristic of solar radiation-based system
Comparison of automatic irrigation systems
6. Application of model-based irrigation system
Model Automation system
Application Realization
Experiment 1
Irrigation system using soil water potential sensors
Experiment 1
7. Layout of an automatic irrigation system
Timing, Set point
Position, Value
Model, Algorism
Agricultural Water Management 55 (2002) 183-201
Experiment 1
8. Soil water potential measured at 0.2m depth
Computers and Electronics in Agriculture 48 (2005) 183-197
Experiment 1
9. Flow diagram of controller program for irrigation
Model
Program
Computers and Electronics in Agriculture 48 (2005) 183-197
Experiment 1
10. Experiments
1. Settlement of irrigation schedule
· Term of watering, water movement
2. Regulation of maximum and minimum set point
· Plant materials, seasons, physical problem
3. Decision of sensor position and measured value
· Calibration, division, reliability of data
4. Programming for irrigation control using model
· Algorism, facility
Experiment 1
11. Expected results
Fig 1. Layout of an automatic irrigation system
Fig 2. Flow diagram of controller program for irrigation
Fig 3. Change in soil water content under solar radiation
Experiment 1
12. Characteristic of solar radiation-based system
Investigation of specific physiology
Fluctuation of soil water content
Experiment 2
Effect of plant physiology by system
Addition of various physical parameters
Experiment 2
13. Fluctuation of soil water content
Physical property Physiological property
60
50
Water content (%)
40
NFW(5), 1:1
30 NFW(5), 7:3
NFW(2), 1:1
20 NFW(2), 7:3
NSW, 1:1
NSW, 7:3
10 EBB, 1:1
EBB, 7:3
0
0 6 12 18 24 30 36 42 48 54
Time (h)
Soil moisture in soil EC-based Change in water content of medium
system in various subirrigation systems
Agricultural Water Management 45 (2000) 145-157
Experiment 2
14. Plant growth
Fresh weight of shoot and fruit at different water contents
Treatment Shoot fresh weight (kg) Fruit fresh weight (kg)
D-50 0.45 0.92ab
D-40 0.46 0.98a
D-30 0.46 0.95ab
D-20 0.44 0.88b
z
Soil water content setting point were 50, 40, 30 and 20 %.
y
Mean separation within column by Duncan’s multiple range test at 5% level.
J. Kor. Soc. Hort. Sci. 44 (2003) 146-151
Experiment 2
15. Addition of various physical parameters
45 4
42
3
Water Content (%)
Irrigation (mL)
39
2
36
1
33
30 0
0 6 12 18 24 30 36 42 48
Time (h)
Substrate, pot size, wick size
Multi-metric chart
Experiment 2
16. Experiments
1. Investigation of plant growth at different fluctuations
of water content
· Maximum and minimum set point, number of times
2. Modeling of physical parameter
· Correlation analysis, non-linear regression
3. Programming for metric chart
· Substrate, pot size, wick size
Experiment 2
17. Expected results
Table 1. Fresh weight of shoot at different water contents
Table 2. Change in plant growth at different fluctuations
of water content
Fig 1. Change in water content of medium in model-based
irrigation system
Fig 2. Flow diagram of multi metric chart
Experiment 2
18. Comparison of automatic irrigation systems
A Soil moisture status in soil electrical
conductivity (a) and leaf-air
temperature differential (b) base
system
B
Experiment of3
Difference property
among systems
Agricultural Water Management 45 (2000) 145-157
Experiment 3
19. Comparison of automatic irrigation systems
Influence of subirrigation systems on kalanchoe growth at 10 weeks after short-
day treatment
Irrigation Dry weight (g) Fresh weight (g) Height Leaf area No. of No. of Water
system (cm) (cm2/plan flower flowers content
Shoot Root Shoot Root t) buds (%)
NFW(4) 2.73 a 0.24 a 50.52 a 1.65 a 15.43 a 289.05 a 139.33 a 13.00 a 26.9 cz
NFW(2) 1.86 b 0.15 c 33.53 b 1.06 b 14.42 a 203.91 b 88.83 c 5.50 ab 16.3 d
NSW 2.83 a 0.20 b 49.74 a 1.49 a 15.58 a 278.31 a 116.50 b 10.33 ab 53.9 b
EBB 2.59 a 0.21 b 49.41 a 1.56 a 14.40 a 287.57 a 130.50 ab 4.00 b 60.6 a
Significancey *** *** *** *** NS *** *** NS ***
Z
Mean separation within columns by Duncan’s multiple range test at P=0.001.
Non significant or significant at P=0.01 and 0.001, respectively.
yNS,**,***
By Myung-min Oh (2003)
Experiment 3
20. Experiments
1. Classification of model-based system
· Soil water content, soil electrical conductivity, leaf-air temperature
differential, solar radiation
2. Influence of model-based systems
· Plant growth, fluctuation pattern
Experiment 3
21. Expected results
Table 1. Influence of various systems on kalanchoe growth at
10 weeks after short-day treatment
Fig 1. Change in fluctuation at various irrigation systems
Fig 2. Effect of irrigation system on soil water content
Experiment 3
22. Possible Publications
Scientia Horticulturae
HortTechnology
Agricultural Water Management
Computers and Electronics in Agriculture·
