NON-DESTRUCTIVE GROWTH MEASUREMENT
OF SELECTED VEGETABLE SEEDLINGS USING
MACHINE VISION
Ta-Te Lin, Sheng-Fu Cheng, Tzu-Hsiu Lin, Meng-Ru Tsai
Department of Agricultural Machinery Engineering,
National Taiwan University,
Taipei, Taiwan, ROC
INTRODUCTION
Plant growth measurement and
modeling
 Machine vision technique
 Seedling characteristics
 Applications in production management

OBJECTIVES
Image processing algorithm
development
 Growth measurements of selected
vegetable seedlings
 Model parameter determination and
simulations

SYSTEM IMPLEMENTATION
Back-lighting apparatus
`
Desktop computer
CCD camera
Seedling
Rotary stage
Stepping motor
Tripod
Tripod
Stepping motor
driver
SEEDLING CHARACTERISTICS
Stem length
 Height
 Span
 Total leaf area
 Top fresh weight
 Top dry weight
 Number of leaves

IMAGE PROCESSING ALGORITHM
Start
Read image
Start Tracing
Threshold
Find root node, set it as
the father node, and
mark it.
Skeletonize
1. Find the child nodes
which have not been
marked as the father
node.
2. Set the pointer to the
father node.
3. Set it as marked.
Is the child node a
branch node?
No
Set the type of the child
node as termninal node.
1. Set the type of the
child node as branch
node.
2. Set itself as the
father node.
Yes
RESULT OF NODE TRACING
RESULT OF NODE TRACING
Calibration of cabbage top fresh weight from seedling projection
area.
2.50
Top Fresh Weight (g)
2.25
Y = -2x10-8X2 +1x10 -3X + 0.023
R2 = 0.950
2.00
1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
0
250
500
750
1000 1250 1500 1750 2000 2250
2
Projection Area (mm )
Calibration of cabbage top dry weight from seedling projection
area.
Top Dry Weight (g)
0.25
Y = 7x10-9 X2 + 7x10-5 X + 2x10-5
R2 = 0.917
0.20
0.15
0.10
0.05
0.00
0
250
500
750
1000
1250
1500
2
Projection Area (mm )
1750
2000
2250
Calibration of cabbage total leaf area from seedling projection
area.
8000
2
Total Leaf Area (mm ）
7000
Y = 3x10-4 X2 + 2.633 X - 82.28
R2 = 0.955
6000
5000
4000
3000
2000
1000
0
0
250
500
750
1000
1250
1500
2
Projection Area （mm ）
1750
2000
2250
Calibration of amaranth top fresh weight from seedling projection
area.
5.50
Top Fresh Weight (g)
5.00
Y = 1x10-8 X2 + 8x10-4 X + 3x10-6
R2 = 0.9683
4.50
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
0
500 1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500
2
Projection Area (mm )
Calibration of amaranth top dry weight from seedling projection
area.
0.60
0.55
Y = 3x10-9 X2 + 7x10-5 X - 0.0113
R2 = 0.9316
Top Dry Weight (g)
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
0
500
1000 1500 2000 2500 3000 3500 4000 4500 5000 5500 6000 6500
2
Projection Area (mm )
Calibration of amaranth total leaf area from seedling projection
area.
16000
Y = 6x10-5 X2 + 2.7589 X - 214.46
R2 = 0.9799
2
Total Leaf Area (mm )
14000
12000
10000
8000
6000
4000
2000
0
0
500
1000
1500
2000
2500
3000
3500
2
Projection Area (mm )
4000
4500
5000
Calibration of kale top fresh weight from seedling projection area.
5.50
Top Fresh Weight (g)
5.00
4.50
Y = 8x10-8 X2 + 7x10-4 X - 0.024
R2 = 0.905
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
0
500
1000
1500
2000
2500
3000
2
Projection Area (mm )
3500
4000
4500
Calibration of kale top dry weight from seedling projection area.
0.65
0.60
Top Dry Weight (g)
0.55
Y = 2x10-8 X2 + 5x10-5 X + 0.0075
R2 = 0.846
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
0
500
1000
1500
2000
2500
3000
2
Projection Area (mm )
3500
4000
4500
Calibration of kale total leaf area from seedling projection area.
9000
8000
2
Total Leaf Area (mm )
Y = 0.0001 X 2 + 1.7988 X - 59.28
R2 = 0.954
7000
6000
5000
4000
3000
2000
1000
0
0
500
1000
1500
2000
2500
3000
2
Projection Area (mm )
3500
4000
Comparison between manually measured top fresh weight and
that determined by the automatic measurement system.
Top Fresh Weight from the System (g)
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2
Manually Measured Top Fresh Weight (g)
Comparison between manually measured total leaf area and that
determined by the automatic measurement system.
Total Leaf Area from the System (mm2)
6000
5000
4000
3000
2000
1000
0
0
1000
2000
3000
4000
5000
6000
2
Manually Measured Total Leaf Area (mm )
Top Dry Weight from the System (g)
Comparison between manually measured top fresh weight and
that determined by the automatic measurement system.
0.18
0.16
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18
Manually Measured Top Dry Weight (g)
Serial images of kale seedlings at various growth stages.
(images are not of the same scale)
Kale seedlings images from different angles
Top fresh weight of kale seedlings growing under 25/20C. Each
curve indicates individual seedling.
1.2
Top Fresh Weight (g)
1.0
0.8
0.6
0.4
0.2
0.0
6
7
8
9
10
11
12
13
14
15
16
17
18
Time (day)
19
20
21
22
23
24
25
26
27
28
Average plant height of kale seedlings grown under five different
day/night temperatures.
9
15 ℃
20 ℃
25 ℃
30 ℃
35 ℃
Average Plant Height (cm)
8
7
6
5
4
3
2
1
0
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Time (day)
Average plant top fresh weight of kale seedlings grown under
five different day/night temperatures.
1.2
Average Top Fresh Weight (g)
1.1
15 ℃
20 ℃
25 ℃
30 ℃
35 ℃
1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Time (day)
Average top dry weight of kale seedlings grown under five
different day/night temperatures.
0.10
15 ℃
20 ℃
25 ℃
30 ℃
35 ℃
Average Top Dry Weight (g)
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Time (day)
Average total leaf area of kale seedlings growing under five
different day/night temperatures.
1200
15 ℃
20 ℃
25 ℃
30 ℃
35 ℃
Total Leaf Area (mm 2)
1000
800
600
400
200
0
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Time (day)
PLANT GROWTH MODELS

LOGISTIC MODEL
Y = Y0 / [ Y0 + ( 1 -  Y0 ) e- t]
t : Time
Y : Plant characteristics
 : Growth constant
 : Reciprocal of Y when t = 
Y0 : Y at time = 0
PLANT GROWTH MODELS

RICHARDS MODEL
dY  Y [1  ( Y ) ]

dt

Y = Y0 / { ( Y0) + [ 1 - ( Y0 ) ] e- t }1/
t : Time
Y : Plant characteristics
 : Growth constant
 : Reciprocal of Y when t = 
Y0 : Y at time = 0
 : For logistic model,  =1
Comparison of regression curves to the experimental data. Top
fresh weight of cabbage seedlings growing under various
day/night temperatures was used as an example.
2
.
5
Top Fresh Weight (g)
2
.
0
o
1
.
5
1
5
/
1
2
C
o
2
0
/
1
5
C
o
2
5
/
2
0
C
1
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0
o
3
0
/
2
5
C
o
3
5
/
3
0
C
0
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5
0
.
0
9
1
0
1
1
1
2
1
3
1
4
1
5
1
6
1
7
1
8
1
9
2
0
2
1
2
2
2
3
2
4
2
5
2
6
2
7
2
8
2
9
T
i
m
e
(
d
a
y
)
GROWTH MODEL PARAMETERS
Temperature
(day/night)
Top fresh weight of cabbage seedlings
Y0


-1
(g x10-2)
(g )
RMSE
(g x10-2)
15/12ºC
0.159± 0.020
0.601± 0.206
2.80± 0.53
4.30± 1.41
20/15ºC
0.204± 0.064
0.604± 0.335
2.71± 1.57
7.75± 3.34
25/20ºC
0.161± 0.029
0.378± 0.137
4.40± 1.06
9.26± 1.74
30/25ºC
0.172± 0.024
0.551± 0.242
3.61± 1.39
5.25± 2.39
35/30ºC
0.143± 0.026
0.595± 0.386
3.58± 1.08
3.94± 1.32
GROWTH MODEL PARAMETERS
Temperature
(day/night)
Top fresh weight of cabbage seedlings
Y0


(g x10-2)
(g-1)
RMSE
(g x10-2)
15/12ºC
0.159± 0.020
0.601± 0.206
2.80± 0.53
4.30± 1.41
20/15ºC
0.204± 0.064
0.604± 0.335
2.71± 1.57
7.75± 3.34
25/20ºC
0.161± 0.029
0.378± 0.137
4.40± 1.06
9.26± 1.74
30/25ºC
0.172± 0.024
0.551± 0.242
3.61± 1.39
5.25± 2.39
35/30ºC
0.143± 0.026
0.595± 0.386
3.58± 1.08
3.94± 1.32
Temperature
(day/night)
Top fresh weight of kale seedlings
Y0


(g x10-2)
(g-1)
RMSE
(g x10-2)
15/12ºC
0.162± 0.008
0.912± 0.171
1.45± 0.17
2.34± 0.75
20/15ºC
0.246± 0.053
0.591± 0.318
0.81± 0.45
1.96± 1.24
25/20ºC
0.268± 0.041
0.991± 0.279
0.64± 0.18
2.16± 0.79
30/25ºC
0.217± 0.001
0.853± 0.257
1.15± 0.14
3.57± 0.17
35/30ºC
0.152± 0.004
0.563± 0.082
1.88± 0.44
2.45± 1.54
Temperature
(day/night)
Top fresh weight of amaranth seedlings
Y0


(g x10-2)
(g-1)
RMSE
(g x10-2)
20/15ºC
0.182± 0.012
4.686± 2.076
0.29± 0.07
0.34± 0.25
25/20ºC
0.281± 0.116
1.379± 0.948
0.67± 0.49
4.28± 1.82
30/25ºC
0.374± 0.079
1.280± 0.510
0.29± 0.51
4.61± 3.32
35/30ºC
0.436± 0.050
0.809± 0.108
0.13± 0.06
4.16± 1.35
RELATIVE GROWTH RATE, RGR

LOGISTIC MODEL
1 dY
  (1  Y )
Y dt

RICHARDS MODEL
1 dY  [1  ( Y ) ]

Y dt

Predicted relative growth rate of cabbage seedling growing under
5 different day/night temperatures using the logistic model.
0
.
3
0
o
1
5
/
1
2
C
o
Relative Growth Rate (1/day)
0
.
2
5
2
0
/
1
5
C
o
2
5
/
2
0
C
o
3
0
/
2
5
C
0
.
2
0
o
3
5
/
3
0
C
0
.
1
5
0
.
1
0
0
.
0
5
0
.
0
0
0 2 4 6 81
01
21
41
61
82
02
22
42
62
83
0
T
i
m
e
(
d
a
y
)
Comparison of calculated top fresh weight of cabbage, amaranth
and kale seedlings growing at 25/200C.
2.0
Cabbage
Top Fresh Weight (g)
1.8
Amaranth
1.6
Kale
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0
5
10
15
Time (day)
20
25
30
Comparison of calculated relative growth rate (RGR) of cabbage,
amaranth and kale seedlings growing at 25/200C.
Relative Growth Rate, RGR
0.30
Cabbage
Amaranth
Kale
0.25
0.20
0.15
0.10
0.05
0.00
0
5
10
15
Time (day)
20
25
30
SEEDLING 3-D RECONSTRUCTION

ARTIFICIAL WIRE MODEL
A
B
C
D
E
F
G
H
SEEDLING 3-D RECONSTRUCTION

CABBAGE SEEDLING
A
B
C
D
E
F
G
H
CONCLUSIONS




A non-destructive machine vision system was
successfully developed for the measurement of
vegetable seedling characteristics. A new algorithm
for the determination of seedling nodes was
implemented.
3-dimension reconstruction of seedling architecture
can be achieved with the nodal coordinates
determined with the machine vision system.
Growth responses of cabbage, kale and amaranth
seedlings under various temperature conditions
were measured and compared.
The dynamic growth responses of selected
vegetable seedlings were analyzed with logistic and
Richards growth model and the relative growth
rates of the seedlings under various conditions
were calculated.
FUTURE DEVELOPMENT
Measurement under natural lighting
 Leaf area index (LAI) determination
 Extraction of information from serial
images
 Modification of the current growth
model
 Application of geometrical modeling in
seedling 3D reconstruction

THANK YOU
謝 謝