CHAPTER V
ELECTRICAL CONDUCTIVITY AS A SURROGATE FOR CHLORIDE
DETERMINATION
This chapter presents the design and development of Microcontroller
ATmega32 based Instrument set up to determine the Electrical Conductivity in soil
samples. The Electrical Conductivity of the soil samples measured by the implemented
embedded based Electrical Conductivity instrument is comparable with that of the
commercial instrument (ELICO CM 180). Since, Electrical Conductivity can be used as
a surrogate for Chloride concentration measurement, a linear regression model is
developed between Electrical Conductivity and Chloride concentration of soil samples.
The Chloride concentration of the soil samples collected at various samples and their
plant cultivation is also discussed.
5.1 Introduction
Electrical conductivity is an inherent property of most materials, and ranges from
extremely conductive materials like metals to very non-conductive materials like plastics
or glass. In metals, the electrical current is carried by electrons, while in water it is
carried by charged ions. In both cases, the conductivity is determined by the number of
charge carriers, how fast they move and how much charge each one carries. Conductivity
(G), the inverse of resistivity (R) is determined from the voltage and current values
according to Ohm's law. Using Ohm’s Law, V= iR and knowing conductivity G=
(1/R)*k, where k=cell constant =length (d, spacing between two electrodes)/area of
electrodes then G can be determined as G= (1/R)*k = (i/V)*k. When resistance is
measured in ohms, conductance is measured in siemens (formerly known as a mho).
Since 1 siemens is a very large unit, aqueous samples are commonly measured in micro
siemens μS. Metals are extremely conductive because electrons move almost with the
speed of light, while in water ions move much slower and the conductivity is much
lower. Raising the temperature makes water less viscous and the ions can move faster.
Because the ions are of different sizes and carry different amounts of water with them as
they move, the temperature effect is different for each ion.
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5.1.1
Electrical Conductivity as a surrogate for Chloride concentration
Electrical Conductivity (EC) is usually a representation of salinity and it can
be measured with a simple device. Chloride ion is an important element among dissolved
solids which can limit plant growth, decrease yields and reduce quality of drinking water.
Chloride is highly soluble and remains in the soil solution, while other ions such as
sulphate and bicarbonate combine with calcium and magnesium, are present, to form
calcium sulphate and calcium carbonate, which are sparingly soluble compounds.
Chloride concentration typically is measured by titration of aqueous samples using
standard AgNO3 solution. Chloride analysis thus is time consuming and expensive,
compared to EC measurement which is fast and inexpensive (Hajrasuliha, S et al) [1].
Since Chloride is a major constitute of saline waters and soils and it directly affects EC, a
close correlation between EC and Chloride can be obtained. Maas et al., [2] suggested
that if Chloride is the predominant anion in a soil solution, the Chloride concentration in
-3
molm
-1
would be approximately equal to 10 times the EC measured in dSm .
Observations of Chloride concentration and Electrical Conductivity delivered the
possibility of a generelised empirical relationship between these two factors. Therefore it
is conceivable that the Chloride concentration can simply be estimated from Electrical
Conductivity measurement. The concept of computation of Chloride concentration is, to
correlate Electrical Conductivity with the Chloride Concentration of the soil samples
using regression model, which validates Electrical Conductivity as a surrogate for
Chloride estimation.
5.2 Agricultural soil
All soils contain some water soluble salts which include essential nutrients for
plant growth. When the level of water soluble salts exceeds a certain level, harmful
effects on plant growth occur. A soil with excess total soluble salts is referred to as a
saline soil. The influence that a certain level of soluble salt will have on crop growth
depends upon several factors such as climatic condition, soil texture, distribution of salt
in the profile, salt composition and plant species ( Milne, R.A et al) [3]. The areal extent
and depth of a salt problem is usually irregular. Soil sampling on a grid system may be
necessary to map the extent of the problem. Soluble salts are most commonly detected by
measuring the soil solution’s ability to conduct an electric current, referred to as
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Electrical Conductivity. The common unit of measurement for EC has been mmhos/cm.
The official international unit of measurement is siemen/ m (S/m). One mmhos/cm is
equal to 0.1S/m or 1.0 ds/m.
5.3 Design and development of Electrical Conductivity measurement set up using
Microcontroller Atmega32
Soil Chloride analysis has been conducted primarily for the purpose of salinity
and irrigation management. Presently, it has become highly advantageous to carry out
information processing and control using microcontroller. It is also a well known fact that
the microcontroller system can offer high accuracy and high speed response. Hence, these
reasons infuse a strong motivation for the design and implementation of the automatic
measurement system based on microcontroller. An embedded systems controlled by
microcontrollers consist of not only a digital part, used for control and data processing,
but also an analog part mostly used for adjustment of input signals e.g. from sensors. In
this experimental study, to decrease the test cost, it is proposed to use ATmega32
microcontroller mounted in the system and the developed system is used for in-situ
measurement of the conductivity.
5.3.1 Design of the measurement system
The block diagram of microcontroller based Electrical Conductivity measurement
set up is shown in figure 5.1. The conductivity cell made up of platinum which is used to
measure the conductivity of the samples is kept in Block 1. The cell constant (K) is
related to the physical characteristics of the measuring cell. K is defined for two flat,
parallel measuring electrodes as the electrode separation distance (d) divided by the
electrode area (A). Thus, for a 1 cm cube of liquid, K = d/A = 1 cm–1. Its determination is
much more convenient by calibration with pattern solutions (Braunstein et al.,) [4].
Polarizing the conductance cell by an external DC potential VDC produces some
undesirable effects (double-layer capacitance, electrolysis, ohmic resistance and
electrolytic saturation). On the other hand, it is proved that the electrolytic saturation is
reduced considerably if the AC polarization frequency is high enough. Hence, a fixed
sinusoidal excitation voltage of 1V is applied to the bridge. The Conductivity cell is
connected to one arm of a modified Wheatstone’s bridge network. The Block 2 consists
of precision rectifier to rectify the output of Bridge network. Block 3 represents the
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temperature sensor Chromel alumel thermocouple to measure the temperature of the
sample. The effect of temperature is important when an electric conductivity of a liquid
or solution must be done. A solution at a higher temperature will present higher quantity
of ions dissociated, therefore the concentration of electric charges will raise and as a
consequence, conductivity will be higher. On the contrary, the same solution at low
temperature will have a low conductivity due to the low quantity of ions present, which
results in lower electric conductivity. From an application point of view, conductivity is
given at a certain temperature, which has been stated as a reference to better compare the
measurements at different times and locations. This temperature is usually 25°C. Block 4
indicates keypad to give input data to the Microcontroller for processing. Block 5 consists
of ATmega32 microcontroller from Atmel company, is a low power, high performance 8
bit AVR microcontroller. Block 6 is a four rows twenty characters LCD (Liquid Crystal
Display) from Hitachi, to display the experimental results. Block 7 consists of MAX232
(dual RS232 transmitter/receiver interface), which is used to communicate with PC kept
in Block 8.
5.3.2 AC modified Wheatstone bridge network
A modified AC Wheatstone bridge network is shown in figure 5.2. The most
accurate methods of measurement of unknown impedance are the bridge methods, whose
accuracy is basically limited only by the accuracy of the known values of the various
elements constituting the bridge. A modified approach of the balancing techniques of AC
Wheatstone’s bridge network has been reported to achieve high accuracy in
measurement. In the developed Instrument, two high gain operational amplifiers
(CA3041) IC1 and IC2 are connected with the bridge network with the non-inverting
terminal connected to the ground circuit. The bridge output nodal points B and D almost
at the same potentials with respect to the ground and hence the effect of stray capacitance
that will exist between them and also between them and ground is assumed to be
minimized. Since, B and D are at virtual ground, the sinusoidal supply voltage,
V= V sin ωt, the current through the bridge impedances are Z1, Z2, Z3 and Z4
respectively. The output voltage of the circuit is [5]
Vo= Rf [Z2Z3 – Z1 Z2] V
(1)
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At balance condition of the bridge, Vo=0 which is identical with the conventional bridge
network. The conductivity cell is connected instead of Z3. The conductivity of a sample
is determined by,
Vo= Bridge output Voltage, Vi= input excitation voltage, Z1, Z2, Z4=known resistances,
Rf =Feed back resistance and Gc = Conductivity of a sample.
The output of the Amplifier IC2 is given to input of the precision rectifier constructed
with operational amplifiers IC3 and IC4 as shown in Figure 5.2.
5.3.3 Microcontroller and interfacing circuit
The circuit diagram of the Microcontroller based instrumentation set up to
measure the Electrical Conductivity of the sample is shown in figure 5.3. In the designed
circuit, the output from the modified Wheatstone’s bridge network (figure 5.2) is given to
pin 38 (ADC 2) of microcontroller. The Thermocouple which is used to measure the
temperature of the sample is connected to pin 39 (ADC 1) of Port A. The signal
generated by the junction of the thermocouple due to thermal changes is fed to an
amplifier circuit specially designed for very low signal amplification as shown in figure
5.4 (Temperature measurement). The output signal is amplified to a suitable level by
using an instrumentation amplifier read by the microcontroller through A/D converter. A
semiconductor temperature sensor AD590 is used to simulate a reference junction
(Neelamegam et al., 1992) [6]. A crystal oscillator of 8MHz is connected between pin 12
and 13 of microcontroller as shown in figure 5.3. Three keys are connected to PC0, PC1,
and PC2 Port C. A four rows twenty characters LCD is connected with Port D, to display
the measured data and the computed results. MAX232 (dual RS232 transmitter/receiver
interface) is connected with pin 14 and 15 of Port D to transmit/ receive data from PC.
5.3.4 Software
Software is developed in C and assembly language to initialize LCD, to start
ADC, to check End of Conversion, to read 10bits of data from ADC, to measure the
temperature, to compute Conductivity, to compute Chloride concentration using
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regression model, to display the results in LCD and to send data to PC for further
processing. The flowchart for performing the above tasks is shown in figure 5.5.
5.4 Materials and Method
5.4.1
Sampling Field
Soil samples are collected from thirty paddy field sites originated from
Thanjavur- Nagapattinam Delta districts, TN, South India, where rice is the main crop of
several agricultural products (Figure 5.6). The field chosen is located on the eastern coast
of TN, between 9o 50’ and 11o 25’ of the north latitude and 78o 45’ and 70o 25’ of the
East. The samples are collected at every 3 kms from Thanjavur to Nagapattinam over
90kms, during the major cropping season of spring-summer (March- June), which
produces about 56% of the Nations total production.
5.4.2 Sample Collection
Sampling areas of paddy fields are selected by avoiding tracks, drainage lines,
sheep camp, or influences other than effluent irrigation. During collection, the size of the
sample (Volume or weight), identification of sample (unique labeling), special packaging
and storage are noted. After collection of the samples, they are air-dried to remove
moisture. Samples are commonly collected from the soil surface or from boreholes
drilled with a hollow stem auger equipped with a split-spoon or core barrel sampler. The
sample is placed in a mixing bowl and organic matter such as roots discarded. Rock and
gravel larger than small pebbles are commonly removed. Homogenize the sample by
thoroughly mixing it prior to weighing or placement in a sample jar (if laboratory
analysis is to be performed). To the extent possible the material placed in a sample jar for
laboratory analysis should be as much like the sample selected for field determination. In
addition coordinate with the analytical laboratory to ascertain if they have a standard
protocol for selection of small volume samples (e.g. a maximum size of pebbles in the
sample).
5.4.3 Sampling procedure
The collected soil samples are assigned a number, transferred to a paper bag,
and then placed in a metal tray. These samples are dried overnight in a cabinet equipped
with a heating element and an exhaust fan to remove moisture. The temperature in the
cabinet does not exceed 36oC in order to approximate air drying conditions. Samples are
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crushed with a mechanical grinder equipped with porcelain mortar and stainless steel 10
mm mesh sieve to remove larger clods and unwanted debris. Since the material from the
particle sizing 2mm and smaller are most important in making an inventory of the
mineral constituents of the soil and in evaluating EC, the sample is crushed again and the
particles sizing 2mm and less than 2mm are sieved using 2mm mesh. The sample is
prepared as given below to measure the conductivity. Three 10 gram scoops of soil and
30 ml of deionized water are taken in a large test tube and shaken well for 30 min to get
1:1 suspension of soil sample. After initial shaking, the suspension is allowed to stand,
with intermittent shaking for 30 minutes [7]. The supernatant solution is then filtered and
it is used for the measurement of Electrical Conductivity.
5.4.4 Measurement
To measure the Electrical conductivity of the sample, the conductivity cell is
connected at one arm of the modified AC Wheatstone bridge and selecting the resistance
value Z1 (100 Ω or 1 kΩ), Z2 (1 kΩ), and Z4 (1 kΩ). A fixed sinusoidal excitation
voltage of 1V with frequency 1 KHz is applied to the bridge. For the calibration of the
instrument, the known concentrations of NaCl are prepared and the Conductivity is
measured before using the Soil samples. The solution is maintained at 25° C. Initially, the
Conductivity cell is kept in the solution of NaCl having concentration of 0.1N, and the
Electrical Conductivity is measured using the developed Instrument. Then the probe is
washed with deionised water and the Electrical Conductivity for various concentrations
of NaCl (0.2N, 0.3N, 0.4N and 0.5N) is measured using the microcontroller based
instrument. The calibration curve is drawn between NaCl concentrations versus
Conductivity (figure 5.7). Then, the conductivity cell is immersed in the prepared soil
sample and the measurements are made for Electrical Conductivity. A graph is drawn
between soil samples and their corresponding Electrical Conductivity as shown in Figure
5.8. At the same time, Chloride concentration of the prepared soil samples is determined
using the titration method for the development of regression model.
5.4.5
Development of regression Model
Regression analysis is the statistical technique that identifies the relationship
between two or more variables. The technique is used to find the equation to evaluate the
relation between the two and to predict the unknown value from the developed equation.
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A simple regression analysis can show that the relations between an independent variable
X and a dependent variable Y is linear, using the simple linear regression equation.
Y= a + mX (where a is an intercept and m is a slope).
The Chloride concentration of the sample is strongly related to the Electrical
Conductivity of the sample, a relation between them is evaluated using linear regression
model (using software ULTIMACALC). It can be seen that from the figure 5.9, as the
Chloride concentration increases the Electrical Conductivity of the soil sample also
increases. The regression line equation is arrived by using the following statistical
equation,
y - y = b xy ( x- x )
where b xy = r (  x /  y ).
The regression line equation y = -517.80+14.02x is obtained for that line, using the above
relation. The concentration of Chloride for the soil sample can be determined if the
conductivity of the soil sample is known.
The correlation coefficient between the
Electrical Conductivity and the Chloride concentration is R= 0.96 (n=30) which enables
the value of Electrical Conductivity can be used as a surrogate for Chloride estimation.
A regression line also drawn between the Electrical Conductivity measured using
the developed instrument and the commercially available ELICO CM 180 instrument to
check the correlations between the two, which is shown in figure 5.10. The regression
line equation arrived is y= 5.85 + 0.94x, and correlation coefficient R = 0.97 (n=30).
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5.5 Results and Discussion
The developed microcontroller based instrument is used to measure the
Conductivity of the soil samples. The empirical relationship between the Electrical
Conductivity and the Chloride concentration has been developed using linear regression
model to determine the Chloride concentration of the sample. The performance of the
designed instrument is investigated by comparing the results with the standard instrument
(ELICO CM 180).
5.5.1 Analytical performance of the system
The calibration curve is obtained by plotting the concentration of Chloride against
the Electrical Conductivity of prepared NaCl Solutions at various concentrations as
shown in figure 5.7. The reproducibility of the instrument is tested by taking five
replicate readings for soil sample and it is found to agree well within the limits. The
statistical analysis is made for the results obtained using the developed instrument and the
standard instrument to compare the relative accuracies in average Electrical Conductivity
for soil samples. The values (n=30) of Mean=72.06, Median value=62, Standard
Deviation= 20.45, Coefficient of Variation =28.38 and Standard Error of Coefficient of
variation= 3.66 for the Conductivity measured using the designed instrument and for the
standard one, the values of mean=73.83, Median value=64, S.D=19.69, Coeff of
Variation= 26.68 and Std Err of Coeff of variation= 3.44 which shows that there is no
significant difference between the two methods. The accuracy of the developed
instrument is confirmed by the absence of large exceptional errors which allows the
suitability of microcontroller based instrument for Electrical Conductivity measurement.
5.5.1 Analysis of Chloride concentration at various locations and plants
In this study, it is observed (Figure 5.8) that the range of Electrical Conductivity
of soil samples varies from 45mS/cm to 109mS/cm and the Chloride concentration
(Figure 5.11) is maximum at Ramarmadam (1010 ppm) and minimum at Kattuthottam
(140ppm). It is also to be noted that all the collected paddy field soil samples are having
the Chloride concentration within the maximum tolerable limit (1050 ppm).
The concentration of Chloride varies from 140ppm to 210ppm for the particular
places like Kattuthottam (140ppm), Pulavarnatham (210ppm), Athanur (210ppm),
Needamangalam (210ppm), and Kilerium (175ppm). It is observed from the literature
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survey (Jing et al., 1992) [8], that the places having Chloride concentration from
100ppm-200ppm are suitable for the cultivation of white potato, peanut, tomato and
sugarcane. Hence, the research report suggests that the above places are suitable for the
cultivation of the above plants with other necessary minerals.
The Chloride concentrations are ranged from 820ppm to 1010ppm for the places
like Aandipalayam (985ppm), Kurukkathi (930ppm), Koothanur (820ppm), Kilvelur
(860ppm), Aazhiyur (980ppm), Ramarmadam (1010ppm), Sikkal (965ppm) and
Nagapattinam (985ppm). These places are suitable for paddy field which is confirmed by
the literature survey (Zhu, Q.S., and Yu,B.S,1991)[9]. It is also observed that the above
places are already cultivating rice only. Hence, it is concluded that the Chloride
concentration is also very important for the paddy growth in addition to other necessary
minerals (rice).
Tomatoes are sensitive to salinity. The test has been conducted to know the effect
of Chloride on tomato plant which is planted at Thanjavur (Tamil Nadu, South India)
having deep, loamy, well-drained soil. The value of soil pH is about 6.2 to 6.8 and the
direct sun light on plant is around 6 hours. The test is performed on the plant during the
ripening stage of tomato fruit. It is observed that irrigating tomato plant with 1N of NaCl
once in a day for the period of 1 month (1.09.2010 to 30.09.2010) increases the total
soluble solids rather than the normal irrigation.
Chloride plays a vital role in stomatal movement in the palm. It is observed that
healthy coconut palms along seashores (Nagapattinam, Tamil Nadu, South India)
Chloride at a concentration of 7-10mg/g DM in their foliage. The optimal Chloride
concentration is usually in the range of 3.8 to 6.4 mg/g.
An embedded based Electrical Conductivity measurement set up has been
designed and developed and a regression model is developed between Conductivity and
Chloride concentration of soil samples. The Chloride concentration of soil samples at
various locations is measured and their plant cultivation is also discussed.
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Figure 5.1 Block diagram of Microcontroller ATmega32 based Electrical
Conductivity instrument set up.
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Figure 5.2 AC modified Wheatstone’s bridge network with precision rectifier
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Figure 5.3 Microcontroller ATmega32 and interfacing circuit
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Figure 5.4 Temperature measurement circuit
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Figure 5.5 Flowchart
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Figure 5.6 Site map
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Figure 5.7 Electrical Conductivity measured for known concentration of NaCl
Solution using developed instrument.
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Figure 5.8 Graph drawn between collected soil samples versus Electrical
conductivity
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Figure 5.9 Linear regression drawn between Electrical Conductivity versus
Chloride concentration
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Figure 5.10 Linear regression for Electrical Conductivity of the soil samples drawn
between the developed instrument and standard instrument.
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Figure 5.11 Graph drawn between collected soil samples versus Chloride
concentration
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References
1. Hajrasuliha S., Cassel D. K., Rezainejad Y., 49(1991), 117-127.
2. Maas E. V., Chloride and crop production. (Eds.: T.L. Jackson). Potash and
Phosphate Institute. Atlanta, GA, (1986), 4-20.
3. Milne R.A, E.Rapp, Soil salinity and drainage problems, Canada
Dept. of Agric, Ottawa, (1968), 1314
4. Braunstein J., Robbins G.D., Journal of Chemical Education, 48 -1 (1981), 52–59.
5. Rajendran A., Neelamegam P., Measurement, 35(2004), 59–63.
6. Neelamegam P., Padmanabhan K., Selvasekarapandian S., Meas. Sci. Technol,
3(1992) 581.
7. Recommended Chemical Soil Test Procedures for the North Central Region,
North Central Regional Publication No. 221. NDSU Bull. No. 499, (1988).
8. Jing A.S., Guo B.C., Zhang X.Y., Chin.J.Soil Sci, 33(6) (1992), 257-259.
9. Zhu Q.S., Yu B.S., Wubei Agric. Sci. 5(1991), 22-26. (Chinese)
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