沙漠研究 24-1, 165-168 (2014)
Ἃ₍◊✲ 24-1, 165 - 168 (2014)
Journal of Arid Land Studies
Journal of Arid Land Studies－ DT11 Refereed Paper －㸫DT11 Refereed Paper㸫

Monitoring Salt Accumulation Status and Saline Stress of Iceplant Leaves
Using Hyperspectral Camera Imagery
Sawahiko SHIMADA*1), Tatsuya HIROKANE2), Makoto OOBA1), Hiromichi TOYODA1),
Fuminori ANDO3) and Yohei TAKARA3)
Abstract: Salinization in arid land regions is a major driver of desertification. One of the main causes of salinization is throughcapillary rise of saline groundwater often as a result of poor land management. According to the Soil Map of the World (FAO/
UNESCO, 1992), total area of ca. 323 Mha is believed to be salt-affected in the world. Halophytes in the iceplant family havepotential to reduce the use of fresh-water irrigation, and improve soil health and food security when grown on saline soils as abioremediation greening vegetable. In the following study, saline stress of the halophytic C3-CAM iceplant species,
Mesembryanthemum crystallinum, was monitored at various growth stages using a Hyperspectral Camera NH-7 to measure surface
reflectance of salt-accumulated leaves and calculate several narrow-band spectral indices. The iceplants received 12 treatments
which included three soil water conditions (144.1%, 83.3% and 65.6% on dry basis), each with four salt concentration irrigation
regimes (0%, 1%, 2% and 3%). Differences in hyperspectral reflectance imagery among treatments were not apparently obvious.
The Plant Senescence Reflectance Index (PSRI), which uses reflectance in 500, 680, 750 nm, to monitor saline stress, was the best
narrow-band spectral index for monitoring saline stress. It was also discovered that the relativeness in the reflectance between 680
and 500 nm shows some signal of saline stress index of the plant.
Key Words: Hyperspectral camera imagery, Iceplant, Mesembryanthemum crystallinum, Narrow-band spectral index, Saline stress1. Introduction
Soil salinization is a major driver of desertification, which
degrades land and limits agricultural production in arid regions.
One of the main causes of this salinization is capillary rise of
saline groundwater often as a result of poor land management(e.g. Banin and Fish, 1995). According to the Soil Map of theWorld (FAO/ UNESCO, 1992), global salt-affected land area iscalculated to be ca. 323 Mha. Intensified use of halophytes ispresumed to be necessary to deal with the limited fresh
irrigation water resources due to the increase of recent
world-wide desertification (Herppich et al., 2008).
Iceplant is a halophyte that is expected to be used forgreening vegetable for salt-affected lands. Moreover, it has
the potential for use in vegetative bioremediation to desalinize
saline soils. Numerous studies on morphological (e.g. Barkla
et al., 2012) or metabolic (e.g. Gabara et al., 2012) aspects ofthe saline effects on iceplant leaves have been done.
However, there is not a full understanding of the spectralreflectance characteristics of the iceplant leaf in association
with the status of salt uptake physiology. The techniques formonitoring salinity are important tools to address yield loss
* Corresponding Author: shima123@nodai.ac.jp

potential when deficit irrigating with poor water quality. In
this study, we attempted to monitor the saline stress of iceplantusing a Hyperspectral Camera to measure surface reflectanceof salt-accumulated leaves.

2. Materials and Methods
In the current study, the saline stress of halophytic
C3-CAM iceplant species, Mesembryanthemum crystallinum
was monitored. The iceplants were planted into 9 cm
diameter pots containing garden soil in September, 2012 andwere grown. The plants received one of 12 treatments which
included three soil water conditions, i.e., Good, Fair and Poor
(Soil water content on dry basis of 144.1%, 83.3% and 65.6%,
respectively), each with four salt concentration irrigation
regimes (0%, 1%, 2%, and 3% NaCl). The treatments werestarted after an iceplant grew six leaves on it. Salinizedirrigation treatments were applied approximately every six
days at treatment stages. The experiment had eight stages,
with stage one beginning 28 October, 2012 on 0%, 1% and 3%
salt concentration regimes for Fair and Poor irrigation soil
conditions, and 20 November, 2012 on all regimes for Good
irrigation condition and the 2% salt concentration regime for Fair
㸦Received, October 9th, 2013; Accepted, January 6th, 2014㸧

1-1-1 Sakuragaoka, Setagaya, Tokyo 156-8502, Japan
1) Faculty of Regional Environment Science, Tokyo University of Agriculture, Japan
2) Graduate School of Agriculture, Tokyo University of Agriculture, Japan3) Earth Blessing Agent Japan Co.,Ltd., Japan

166

Table 1. Treatment stages and schedule for salt concentration
irrigation applications at different soil water conditions (cf.
Hirokane et al., in press).
Soil Water Content dry(Irrigation Condition)

144%(good)

83.3%(fair)

65.6%(poor)

2012
2013
Salt
8-Dec 14-Dec 20-Dec 26-Dec 1-Jan
Concentration 28-Oct 1-Nov 7-Nov 13-Nov 20-Nov 27-Nov 2-Dec Image
taken
0%
1%
2%
3%
0%
1%
2%
3%
0%
1%
2%
3%

1
1

2
2

3
3

4
4

1
1
1

2
2
2

3
3
3

4
4
4

1

2

3

4

1
1
1
1
5
5
1
5
5
5
1
5

2
2
2
2
6
6
2
6
6
6
2
6

3
3
3
3
7
7
3
7
7
7
3
7

4
4
4
4
8
8
4
8
8
8
4
8

5
5
5
5

6
6
6
6

7
7
7
7

8
8
8
8

5

6

7

8

5

6

7

8

= 9cmFig. 1. Experimental setup of hyperspectral reflectance dataacquisition.

and Poor irrigation conditions. Irrigation with salinizedtreatment was performed at every stage, i.e., every 6 days after
the first stage.
The electric conductivity (EC) of the soil, and a young andmature leaf for each sample at every stage by EC meter,
DEC-2, Atago Co. Ltd. Soil EC and leaf EC were measured
after diluted with 5 times and 20 times of water, respectively.
Hyperspectral reflectance images were taken from iceplantleaf surfaces 2 days after the fourth stages on all salt
concentration regimes for Good irrigation soil water condition,and the 2% salt concentration regimes for Fair and Poor
irrigation conditions. Images were taken again 2 days after
the eighth stage on 0%, 1% and 3% salt concentration regimes
for Fair and Poor irrigation conditions (Table 1).
A Hyperspectral Camera NH-7 (1280 × 1024 pixel
resolution, 400 - 1000 nm range, 5 nm interval, Eba Japan Co.,
Ltd.) was used to predict the status of the halophytes bymonitoring the leaves. Hyperspectral reflectance imagery
measurements were collected on all iceplants used in the study.
The hyperspectral reflectance data were measured on theilluminated iceplant leaf samples using 3 halogen lamp lightsources (Caster, 250W CHP-250) (Fig. 1). Reflectancevalues were calculated using the white reference(ColorChecker White balance, X-Rite Inc.). The spectralreflectance data were normalized using the following equation
to remove wavelength-independent magnitude differences
between spectra and enhance wavelength-dependent effects (cf.
Zhang et al., 2005).

R(Ȝ) = Ro(Ȝ) / RT

(1)

Where, Ȝ is wavelength, R(Ȝ) is normalized reflectance in Ȝ,Ro(Ȝ) is original reflectance in Ȝ, RT is the total sum of Ro(Ȝ)
over the defined spectral region (i.e., 400 - 1000 nm). Since
each hyperspectral image consists of 121 bands, we calculated
the following narrow-band spectral indices: Normalized
Difference Vegetation Index (NDVI) (Rouse et al., 1973),
Photochemical Reflectance Index (PRI) (Gamon et al., 1997),
Normalized Difference Index between 490 - 620 nm (NDI(490,620)) (Shimada et al., 2012), RENDVI (Gitelson et al., 1996),
Plant Senescence Reflectance Index (PSRI) (Merzlyak et al.,1999), and Water Band Index (WBI) (Penuelas et al., 1997) toexamine the iceplant saline stress indicator.
Eachnarrow-band index can be expressed as follows:
NDVI = (R865 – R670) / (R865 + R670)
PRI = (R530 – R570) / (R530 + R570)
NDI(490, 620) = (R490 – R620) / (R490 + R620)
RENDVI = (R750 – R700) / (R750 + R700)
PSRI = (R680 – R500) / R750
WBI = R905 / R973

(2)
(3)
(4)
(5)
(6)
(7)

Where, Rn is the normalized reflectance in the wavelength of n
nm. In this paper, the reflectance data at the central part of theleaves were used for analysis. Regression analysis was
conducted between every narrow-band spectral index and thecorresponding soil and leaf EC.

3. Results and Discussion
Figures 2 and 3 show images (R:G:B = R845:R695:R595)
taken by the Hyperspectral Camera NH-7 on December 10 (cf.
Table 1). No obvious differences are visible in iceplant leaf
growth under different salinized irrigation regimes at Good
irrigation condition (i.e., pF 1.8) (Fig. 2). Good irrigation
condition at stage four, the soil EC measurements were 1.6,
11.6, 17.3 and 31.1 mS cm-1, mature leaf EC measurements
were 0.09, 0.14, 0.21 and 0.50 mS cm-1, and young leaf EC
measurements were 0.22, 0.44, 0.38, 0.29 mS cm-1 for 0%, 1%,
2% and 3% salt concentration irrigation regimes, respectively.
The prevention of the iceplant growth can be observed fromthe images by water stress (Fair and Poor irrigation) under the
2% salt concentration irrigated treatment (Fig. 3). The
measured soil, mature leaf, and young leaf EC values in the
Fair and Poor irrigation with 2% salt concentration conditions
were 12.0 - 13.1, 1.22 - 1.62, 0.93-1.37 mS cm-1, respectively.
Figure 4 shows the normalized reflectance curve for Good
irrigation condition samples. According to the result,

167

0%

9cm

1%

2%

3%

NDVI
0.9

0.5

0%

1%

2%

3%

Fig. 2. Images of the iceplants in different salt concentration
irrigated treatments (0%, 1%, 2%, 3%) under Good
irrigation conditions at stage 4. NH-7 used.
9cm

PRI
0.1

Ͳ0.3

NDI(490Ͳ620)
0.9

Ͳ0.7

Good

Fair

Poor

Fig. 3. Images of the iceplants in different soil water conditions(Good, Fair, Poor) under 2% salt concentration water
irrigated treatment at stage 4. NH-7 used.

RENDVI
0.9

0.2

PSRI

0.02

0.1

Ͳ0.1

0.015
WBI
1.5

0.01
1.0

0.005

Matureleaf
Youngleaf

0
450

550

650

750

850

Fig. 5. Images of narrow-band spectral indices (NDVI, PRI, NDI(490,690), RENDVI, PSRI, WBI) for each salt concentration (0%,1%, 2%, 3%) under Good irrigation condition at stage 4.

950

Wavelength(nm)Fig. 4. Normalized reflectance curves for stage four mature andyoung iceplant leaves grown in Good irrigation soil watercondition and four different salinized irrigation regimes.

differences in the normalized reflectance between near infrared(NIR: ca. 750 - 900 nm) and red (ca. 660 - 670 nm) regions
was greater on young leaf than mature leaf, while difference
between green (ca. 540 - 600 nm) and red regions was greateron mature leaf. This result indicates that, at this stage and soil
water condition, differences in reflectance are more obvious
between young and mature leaves than among different
iceplant saline stress statuses.
Figure 5 shows images of all the calculated narrow-band
spectral indices of iceplants under Good irrigation condition atstage four. The leaf veins had relatively lower values fromNDVI, PRI, NDI(490, 690) and RENDVI, while relatively higher
values were observed from PSRI and WBI.
Figure 6 shows the difference of narrow-band spectral
indices in relation to the difference in salt concentration. As
saline stress increases, NDVI, RENDVI and WBI tend to
decrease, while the opposite trend can be seen for PRI and
PSRI. Using the mature leaf reflectance and EC data, and thesoil EC data, the strongest correlation was found between PSRI
and soil EC, i.e., r = 0.88 (Fig. 7 (A)).
Other strong correlations (| r | > 0.6) were found between
PRI-NDI(490,620) (0.83), PSRI-leaf EC (0.70), RENVID-

Ͳ0.1

40

1%

2%

3%

0%

1%

2%

3%

0%

1%

2%

3%

Ͳ0.14

20

Ͳ0.16

10
0
0.50

0%

Ͳ0.12

30

Ͳ0.18

0%

1%

2%

3%

0.40

Ͳ0.2
0.54
0.52

0.30
0.5

0.20
0.10
0.00
0.76

0%

1%

2%

3%

0.75

0.48
Ͳ0.015

Ͳ0.02

0.74
0.73
Ͳ0.05

0%

1%

2%

3%

Ͳ0.0251.2
1.18

Ͳ0.055
1.16

Ͳ0.06
1.14

Ͳ0.065

Fig. 6. Difference of narrow band spectral indices (NDVI, PRI,
NDI(490, 620), RENVID, PSRI, WBI) with soil and leaf EC in
the degree of irrigated salt concentration 0%, 1%, 2% and3%.

NDI(490,620) (0.68), soil EC-leaf EC (0.66), RENDVI-WBI(0.66) and PRI-soil EC (0.61). These results suggest that
PSRI is the best narrow-band spectral index for monitoring soil
EC and the saline stress status of iceplant. These results also
indicate that spectral reflectance information from leaf surface
reflects more sensitively on soil salinity than on leaf salinity.
Since PSRI uses the reflectance values 500, 680, and 750
nm (eq (6)), we checked each part (R500, R680, R750, R680 - R500,
R680/R750 and R500/R750) of the index that contributes the most

168

40
35

7

(A)

30

6

y=3201.3x+79.0
R²=0.78

25

5

y=408.9x+9.6
R²=0.49

420

References

(B)

3

15

2

10

1

5
0

0

Ͳ5
Ͳ0.03

Ͳ1
Ͳ0.03

Ͳ0.025

Ͳ0.02

Ͳ0.015

Ͳ0.01

Ͳ0.025

PSRI

Ͳ0.02

Ͳ0.015

Ͳ0.01

PSRI

Fig. 7. Correlation of (A) PSRI–soil EC1:5 and (B) PSRI-leaf EC1:20.
0.0005(A)

0.0004

0%
1%
2%
3%

0.00030.00020.0001450
0.0005

460

470

480

490

500

510

520

530

460

470

480

490

500

510

520

530

460

470

480

490

500

510

520

530

(B)

0.00040.00030.00020.0001450
0.00050.0004(C)

0.00030.00020.00010450

Wavelength(nm)Fig. 8. Difference values of normalized reflectance for iceplant
between the wavelengths of 680 nm and around 500 nm
under different irrigation conditions, (A) Good, (B) Fair and(C) Poor, with various salt concentration patterns.

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PSRI and the difference value between normalized reflectancein 680 nm and 500 nm are good indicators for monitoringsaline stress.

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