Ref: C0521
Application of impedance spectroscopy sensing for leaf
water status
Diyana Jamaludin, Samsuzana Abd Aziz and Desa Ahmad, Department of Biological and
Agricultural Engineering, Faculty of Engineering, Universiti Putra Malaysia, 43400 Serdang,
Selangor Malaysia
Hawa ZE Jaafar, Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor Malaysia.
Abstract
Water stress is one of the most important environmental stresses that can depress growth
and alter the biochemical properties of plants. Conversely, studies show that non-severe
water stress has sometimes proven beneficial for the production of phytochemical content.
This indicated that manipulation of plant water stress may be an effective method to increase
expression of secondary metabolites compounds plus as an advantage to manage irrigation
efficiently. Plant chosen for this study is Labisia pumila or locally known as Kacip Fatimah
which is one of the main herbs in Malaysia. An impedance spectroscopy technique was
used in this research to measure water content of Labisia pumila leaf for plant water status
monitoring. An impedance analyzer connected to a PC was used to monitor real-time
changes in the electrical properties of tested leaf over a frequency range from 100Hz to 100
kHz. A randomized complete block design experiment was designed to characterize the
relationship between impedance, leaf water potential (LWP) , relative water content (RWC)
and soil moisture content under four levels of evapotranspiration replacement (ER) (100%;
well watered), (75%, moderate water stress), (50%, high water stress) and (25%, severe
water stress). Statistical analysis shows that impedance value change with different water
treatment and it was observed that severe water stress (25% ER) shows the highest
impedance value. Correlation between impedance with treatment, LWP, RWC and soil
moisture content showed that impedance measurement technique could be used to monitor
leaf water status. The use of partial least square (PLS) and principle component analysis
(PCA) for variable selection methods was found to enhance the classification performance of
the models. These results demonstrated that impedance spectroscopy is capable of
identifying leaf water status.
Keywords: Impedance spectroscopy, leaf water status, water stress, evapotranspiration
1
Introduction
Plant water status had been studied frequently as one of the great interest in plant growth
and production. Early farmers used visual indicators such as wilting and leaf rolling as water
stress indicators which remain useful today. However, only the expert and experienced
grower can detect subtle changes due to water stress. Methods of measuring water status
have ranged from factors based on the plant itself to factors associated with various
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properties of the plant environment. Factors based on the environment are often difficult to
interpret because of the dynamic nature of the soil plant-atmosphere system .It is influenced
by range of factors including soil water potential, the interface between the soil and plant
roots, hydraulic conductivity, within the plant and the evaporative demand to which the plant
is expose (Kramer & Boyer, 1995).
Plant water measurement can be classified into direct and indirect methods. The direct
method usually utilizes a sensor which directly measure plant water potential or turgor
pressure of the leaf. Alternatively, many indirect methods are available to monitor plant water
status. Most of the indirect methods are based on estimating soil water content, or dielectric
parameter of soil. Direct methods on plant itself are preferable as they give the real condition
of plant water status. However, most of the direct methods are destructive where plants need
to be harvested to get the measurement such as using pressure chamber to measure leaf
water potential or using oven dry method to measure relative water content.
Electrical properties of plant materials can
provide information about cell structure, as
biological tissue can be represented by a simplified electrical model consisting of parallel
circuit of capacitor and a resistor (Kuson & Terdwongworakul, 2013). Impedance
spectroscopy allows for the analysis of properties of materials and systems through
application of alternate electric signals of different frequencies (voltage or current) and
measuring the corresponding electric output signals (current or voltage)(Macdonald &
Johnson, 2005).The ratio of the signal voltage to the signal current is called impedance and it
is frequency dependent (Fuentes et al., 2013). At high frequencies, current flows through
capacitive component thus decrease the overall impedance (Repo, 1988). Impedance
spectrsocopy technique had been used in some research related to agricultural materials to
determine the physical and physiological aspects in the plant. For example, moisture content
of tea leaves at frequency range of 10Hz to 1.0MHz was investigated and it shows that
impedance and capacitance have effect on moisure content at a frequency of 3.0kHz
(Mizukami, Sawai, & Yamaguchi, 2006). The ripening stages of fruits also show relationship
with impedance parameters such as in banana (Jamaludin, Aziz, & Ibrahim, 2014),
nectarines (Roger, Harker, Maindonald, & John, 1994) and kiwifruit (Bauchot, Harkera, &
W.Michael, 2000). In this paper, impedance technique was studied to determine water status
of Labisia pumila var. pumila which is one of the main herbs use in Malaysia for general
well-being and vitality of women, maintaining the figure and appearance, aiding in reducing
symptoms related to hormonal imbalance, and increasing libido in women (Hussain & Kadir,
2013). The potential of impedance measurement to determine physiological aspects of plant
water stress such as leaf water potential, relative water content and soil moisture content is
explored.
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2
Materials and methods
2.1
Design of experiment
The experiment was conducted in a natural ventilation greenhouse at Universiti Putra Malaysia (3°0’ 30” N latitude; 101° 42’ 18” E, 68 m above sea level). Total of 192 Labisia pumila
var. pumila were grown under soilless media consisting of mixture of coco-peat, burnt paddy
husk and chicken dung in a ratio of 5:5:1 v/v. Water stress treatment was performed with 4
levels of water treatment based on Evapotranspiration Replacement (ER) method which are
100% ER (well-watered), 75% ER (moderate water stress), 50% ER (high water stress) and
25% ER (severe water stress). In this method, amount of water applied to the plant was
based on amount of water needed to be replaced after loss via evapotranspiration process.
Treatment was applied for 20 weeks.
2.2
Electrical impedance measurement
An impedance analyzer board AD5933 with a pair of electrocardiogram (ECG) probe was
used to measure impedance value of Labisia pumila at four levels of evapotranspiration rate
(Figure 1). This sensing system offers a non-destructive method, in situ measurement and
easy to use instrument. A fully expanded leaf was selected from each plant as a sample.
Leaf surface was cleaned and dried before a pair of ECG probe attached on top-bottom parallel position. Frequency sweeps from 100Hz to 100 kHz was selected in this experiment.
Impedance data were downloaded to the PC in Microsoft Excel format for further analysis.
Figure 1: Impedance sensing system with a pair of ECG probe attached on the leaf
2.3
Leaf water potential measurement
Leaf water potential (LWP) indicates the demand for water within a plant, the resistance to
water movement within the plant, and the demands for transpiration imposed by the
environment. A pressure chamber (PMS Instrument Co, Model 600, USA) was used to
measure the LWP expressed in bar unit. The water column in a plant is always under tension. The same leaf used for impedance measurement was cut and placed in a chamber with
the cut surface protruding through the chamber. The pressure control valve was open slowly
to release pressure while the cut surface was observed. The chamber pressure was record-
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ed when water first appeared at the cut surface. The pressure measured is equal to the tension of the water column at the time the sample was cut.
2.4
Relative water content measurement
Samples of leaf disc were taken and fresh weight was determined. Samples then were floated in distilled water for 24 hours and turgid weight was recorded. Samples were subsequently oven-fried to a constant weight at 60°C for 48 hours and dry weight of sample was recorded. Relative water content (RWC) was calculated based on equation below:
-
⁄
-
(Equation 1)
where FW= fresh weight, DW= dry weight and TW=turgid weight.
2.5
Soil moisture content measurement
Soil moisture meter (IMKO, Trime FM3, German) was used to measure the volumetric soil
moisture content (SMC). The Trime FM3 system consists of a read-out unit and three-pin
probes. The probes have a measuring range of 0 - 95 volume percentage moisture. Two
points of measurement were taken for each polybag to get the average value of the soil
moisture content.
2.6
Data analysis
Data were analyzed statisticaly using SAS 9.1.3 Portable for Pearson Correlation
Coeffiecient and further classification of treatment by Principle Component Analysis were
analyzed using MATLAB Version 7.7.
3
Results
3.1
Changes in impedance with respect to frequency
Relationship between impedance and frequency was determined by plotting scatter plot of
impedance versus frequency from 100Hz to 100 kHz at different water treatment. Frequencies from 70 kHz to 100 kHz were chosen for further analysis as this region shows better
results in differentiating effect of water treatment and had lesser noise compared to the lower
frequencies. Figure 2 shows relationship between impedance and frequency at different water treatment at 5, 10 and 20 weeks of experiment. These graphs have same pattern where it
shows that impedance decreases as frequency increases. A similar decline of impedance
value was also reported in durian (Kuson & Terdwongworakul, 2013) and kiwifruit (Juansah,
Budiastra, & Dahlan, 2012). It is apparent that 25% ER which is severe water stress had the
highest impedance value followed by 50%ER, 75% ER and 100% ER. This result confirms
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that leaf with less water content has the highest impedance value as it conducts electricity
poorly thus result to higher impedance value. However, at 20 weeks of experiment, the 100%
ER shows higher impedance compared to 50% and 75% ER. This could be due to seasonal
changes in vocalization and wall thickness in the cells that result in amount of water content
of the tissue.
Figure 2: Relationship between impedance and frequency at four level of Evapotranspiration Replacement (ER) treatment at 5 weeks to 20 weeks.
3.2
Electrical impedance with Labisia pumila water stress parameters at selected frequencies
In order to quantify the degree of which frequencies are related to the Labisia pumila water
stress parameter, statistical analysis of Pearson Correlation Coeffiecients method was
performed. Frequency of 70 kHz, 80 kHz, 90 kHz and 100 kHz were selected from previous
analysis. Table 1 shows that all parameters have significant result with frequencies selected
at each week of experiment. LWP had most of the highest correlation coeffiecient (r)
compared to RWC and SMC.
Positive values indicate a relationship between x and y
variables such that as values for x increase, values for y also increase. Negative value
indicates a relationship between x and y such that as values for x increase, values for y
decrease. In week 5, the highest correlation for each parameters are 80kHz for LWP, 90kHz
for RWC and 90 kHz for SMC. The result is different for each week of experiment but it
shows that these selected frequency have strong correlation with impedance except for
SMC at week 5. This could be due to indirect measurement of SMC to determine leaf water
status.
Table 1: Correlation coefficient (r) of impedance with leaf water potential (LWP), relative water content
(RWC) and soil moisture content (SMC) at selected frequencies with different harvest time using
Pearson Correlation Coefficients method.
Week 5
Week 10
Week 20
LWP
RWC
SMC
LWP
RWC
SMC
LWP
RWC
SMC
70
0.9247 ⃰
-0.5839 ⃰
-0.4507 ⃰
0.8108 ⃰
-0.7390 ⃰
-0.7598 ⃰
0.7430 ⃰
-0.7606 ⃰
-0.818 ⃰
Frequency (kHz)
80
90
0.9381⃰
0.9370⃰
-0.5879 ⃰
-0.6034 ⃰
-0.4646 ⃰
-0.4732 ⃰
0.8214 ⃰
0.8178 ⃰
-0.6977 ⃰
-0.6572 ⃰
-0.7573 ⃰
-0.7269 ⃰
0.7632 ⃰
0.7561 ⃰
-0.7674 ⃰
-0.7855 ⃰
-0.8244 ⃰
-0.8140 ⃰
100
0.9377⃰
-0.5972 ⃰
-0.4654 ⃰
0.8030 ⃰
-0.6484 ⃰
-0.7091 ⃰
0.7694 ⃰
-0.7691 ⃰
-0.8193 ⃰
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⃰ significant at P≤0.05
Relationship between impedance and plant water stress parameters were further explored to
find the regression coefficient (R2) for each parameter with impedance. The frequency
selected on each harvest week to produce scatter plot of impedance verses plant water
stress parameters was based on the highest correlation coeffient (r) in Pearson analysis .
Figure 3 shows relationship between LWP and impedance value. Polynomial curve with R2
ranging from 0.69 to 0.78 were obtained. RWC also shows good regression coefficient with
impedance with R2 ranged from 0.73 to 0.77 (Figure 4). SMC shows acceptable range of
regression coefficients (R2) from 0.59 to 0.69.
Figure 3: Scatter plot illustrating relationship between leaf water potential and impedance at different
harvest time.
Figure 4: Scatter plot illustrating relationship between relative water content and impedance at different harvest time.
Figure 5: Scatter plot illustrating relationship between soil moisture content and impedance at different
harvest time.
3.3
Principle component analysis (PCA) on water stress component
Since the impedance spectroscopy measurement gave huge amount of data, Principle Component Analysis (PCA) was applied to compress information in a manner that retains essential information which captures big variability and ignores small variability. Figures 6 to 8 present the score plots of PCA First PC versus Second PC. LWP shows clustering pattern of
different % ER at week 5 of harvest. In weeks 10 and 20, clearly shows that 100% ER differ
from the scores of 75% ER, 50%ER and 25% ER. Score plots of RWC and SMC however,
shows no clear classification between water treatment (Figures 7 and 8).
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6
1
PCA LWP Week5 for Water Treatment
x 10
6
2
100%
75%
50%
25%
0.5
6
PCA LWP Week 10 for Water Treatment
x 10
1
100%
75%
50%
25%
1.5
PCA LWP Week 20 for Water Treatment
x 10
100%
75%
50%
25%
0.5
0
1
-0.5
Second PC
Second PC
Second PC
0
0.5
0
-0.5
-1
-1
-1.5
-0.5
-1.5
-2
-6
-5
-4
-3
-2
First PC
-1
0
1
2
-1
-2
-1.5
-4
-2.5
-3
-2
0
2
4
6
8
10
First PC
6
x 10
-2
-1
0
6
x 10
1
First PC
2
3
4
5
6
x 10
Figure 6: Score plot of First PC vs Second PC on different percentage of Evapotranspiration Replacement for leaf water potential.
6
2
6
PCA RWC Week5 for Water Treatment
x 10
3
100%
75%
50%
25%
1.5
1
PCA RWC Week 10 for Water Treatment
x 10
6
2
100%
75%
50%
25%
2.5
2
PCA RWC Week 10 for Water Treatment
x 10
100%
75%
50%
25%
1.5
1
1.5
0
Second PC
Second PC
Second PC
0.5
1
0.5
0.5
0
-0.5
0
-0.5
-1
-0.5
-1.5
-1
-1
-2
-2
-1
0
1
2
3
4
-1.5
-5
5
First PC
0
5
-1.5
-3
10
First PC
6
x 10
-2
-1
0
6
x 10
1
First PC
2
3
4
5
6
x 10
Figure 7: Score plot of First PC vs Second PC on different percentage of Evapotranspiration Replacement for relative water content.
6
2
6
PCA Soil Moisture Week 5 for Water Treatment
x 10
3.5
x 10
1.5
100%
75%
50%
25%
3
1
6
PCA Soil Moisture Week10 for Water Treatment
2.5
0
PCA Soil Moisture Week 20 for Water Treatment
x 10
100%
75%
50%
25%
1
0.5
2
-2
100%
75%
50%
25%
-3
-4
0
1.5
Second PC
Second PC
Second PC
-1
1
0.5
-0.5
-1
0
-1.5
-0.5
-5
-6
-2
-2
-1
-1
0
1
2
First PC
3
4
5
6
x 10
-1.5
-5
0
5
First PC
10
6
x 10
-2.5
-5
-4
-3
-2
-1
First PC
0
1
2
3
6
x 10
Figure 8: Score plot of First PC vs Second PC on different percentage of Evapotranspiration Replacement for soil moisture content.
4
Discussion
The relationship between impedance and frequency at different ER shows that electrical impedance of biological tissue decreases with an increase in frequency due to capacitive characteristics of cell membrane. The leaf with severe water stress treatment (25% ER) shows
the highest value of impedance because the loss of moisture content contributes to electrolyte concentration. As a result, the equivalent electrical conductivity decreases and the impedance increase. Pearson correlation coefficient (r) of impedance with LWP, RWC and
SMC indicates that there were significant correlations at frequency 70 kHz to 100 kHz. This
was confirmed by regression coefficients of the polynomial curves produced. It shows that
LWP and RWC have high correlation with impedance compared to SMC. This can be explained by the measurement of LWP and RWC directly on the leaf compared to SMC that
was measured indirectly on the soil surface. Measurement techniques for LWP and RWC for
leaf water status were destructive and time consuming; however impedance spectroscopy
technique offers non-destructive method, easy to use and in-situ measurement. The use of
PCA was to analyze data on two-dimensional planes and identify trend among ER water
treatments. It can be suggested that impedance closely related with plant water metabolism
supported by correlation of impedance with LWP.
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5
Conclusions
ER method for water stress study substantially affected the LWP and RWC. These changes
can be detected using real-time impedance spectroscopy at frequencies between 70 kHz to
100 kHz. Although the regression coefficient of impedance and SMC was not substantial,
when considering the result acquired from indirect measurement, the performance seems
appropriate. The impedance technique provides an important tool for evaluation of the leaf
water status non-destructively.
6
Acknowledgements
The authors gratefully acknowledge the financial support from Ministry of Education Malaysia
and Universiti Putra Malaysia with grant under Fundamental Research Grant Scheme (Project No: 03-02-13-1276FR).
7
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