CHAPTER V ELECTRICAL CONDUCTIVITY AS A SURROGATE FOR CHLORIDE DETERMINATION

Transcription

1 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. 119

2 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 AgNO 3 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 molm -3 would be approximately equal to 10 times the EC measured in dsm -1. 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 120

3 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 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 V DC 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 121

4 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 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) 122

5 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 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 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 123

6 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 Materials and Method 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 9 o 50 and 11 o 25 of the north latitude and 78 o 45 and 70 o 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 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) 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 36 o C in order to approximate air drying conditions. Samples are 124

7 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 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 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. 125

8 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 = x 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 The regression line equation arrived is y= x, and correlation coefficient R = 0.97 (n=30). 126

9 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) 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= 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 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 127

10 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 ( to ) 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. 128

11 Figure 5.1 Block diagram of Microcontroller ATmega32 based Electrical Conductivity instrument set up. 129

12 Figure 5.2 AC modified Wheatstone s bridge network with precision rectifier 130

13 Figure 5.3 Microcontroller ATmega32 and interfacing circuit 131

14 Figure 5.4 Temperature measurement circuit 132

15 Figure 5.5 Flowchart 133

16 Figure 5.6 Site map 134

17 Figure 5.7 Electrical Conductivity measured for known concentration of NaCl Solution using developed instrument. 135

18 Figure 5.8 Graph drawn between collected soil samples versus Electrical conductivity 136

19 Figure 5.9 Linear regression drawn between Electrical Conductivity versus Chloride concentration 137

20 Figure 5.10 Linear regression for Electrical Conductivity of the soil samples drawn between the developed instrument and standard instrument. 138

21 Figure 5.11 Graph drawn between collected soil samples versus Chloride concentration 139

22 References 1. Hajrasuliha S., Cassel D. K., Rezainejad Y., 49(1991), Maas E. V., Chloride and crop production. (Eds.: T.L. Jackson). Potash and Phosphate Institute. Atlanta, GA, (1986), Milne R.A, E.Rapp, Soil salinity and drainage problems, Canada Dept. of Agric, Ottawa, (1968), Braunstein J., Robbins G.D., Journal of Chemical Education, 48-1 (1981), Rajendran A., Neelamegam P., Measurement, 35(2004), Neelamegam P., Padmanabhan K., Selvasekarapandian S., Meas. Sci. Technol, 3(1992) Recommended Chemical Soil Test Procedures for the North Central Region, North Central Regional Publication No NDSU Bull. No. 499, (1988). 8. Jing A.S., Guo B.C., Zhang X.Y., Chin.J.Soil Sci, 33(6) (1992), Zhu Q.S., Yu B.S., Wubei Agric. Sci. 5(1991), (Chinese) 140