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Interfaced circuit using a non- destructive method for moisture measurement
Microprocessors and Microsystems 73 (2020) 102951
Contents lists available at ScienceDirect
Microprocessors and Microsystems journal homepage: www.elsevier.com/locate/micpro
Interfaced circuit using a non- destructive method for moisture measurement Divya Nath K a,∗, Prabhu Ramanathan b a b
SCMS School of Engineering & Technology, Karukutty, Ernakulam, Kerala 683582, India Universitetslektor, Department of Engineering Science, University West, Nohabgatan 18A, Building 73, Trollhättan, Sweden
a r t i c l e
i n f o
Article history: Received 28 September 2019 Revised 4 December 2019 Accepted 7 December 2019 Available online 9 December 2019 Keywords: Error correction Moisture content measurement Non-destructive method and relative permitivity
a b s t r a c t Analysing the moisture in stored products like harvested cereal grains and their products, peas, beans, oil-seeds, copra, cocoa beans, spices etc. is very much important to avoid the fungi growth. Moisture can be present in grain in more than one state, i.e. as bound, adsorbed or absorbed water. A designed, integrated circuit was interfaced with personal computer to measure the capacitance which in turn help to calculate the moisture content of rice. The interfaced circuit was tested by measuring the capacitance of different ceramic capacitor. This technique is fast, reliable, accurate and gives hundred set of readings in few seconds. Moisture contents are measured in percentage. The error correction was done with the help of mat - lab programming. © 2019 Elsevier B.V. All rights reserved.
1. Introduction Agriculture is a main source of income in a developing country like India. The moisture content of grains depends upon the humidity and the temperature of the atmosphere. As the humidity and temperature of the atmosphere varies, it is very much necessary to measure the moisture content of grains frequently. Moisture content is a factor critical to the shelf life. The moisture content in food grains like paddy, rice, etc. should be known by the farmers for its trading, processing and storage else fungi affect the grains and become useless [1,2]. At the time of harvesting, 20% - 40% will be the approximate amount of water content in food items and that has to be reduced to 10% −13% for trading, processing, and storing [3]. The direct or indirect method can be used to measure the moisture content. In direct technique moisture content is calculated using the standard equation (1) or (2).
Dry basis % MC (Wet weight of sample − Dry weight of Sample) = Dry weight of sample Wet basis % MC (Wet weight of sample − Dry weight of Sample) =, Wet weight of sample ∗
Corresponding author. E-mail address: [email protected] (D.N. K).
https://doi.org/10.1016/j.micpro.2019.102951 0141-9331/© 2019 Elsevier B.V. All rights reserved.
(1)
(2)
The difference in the two weights (loss on drying) is then compared with either the original weight (wet-base test) or final weight (dry-base test) and the moisture content are calculated. The direct method does not require calibration, help to measure high levels of moisture and are cheaper than more sophisticated instruments. The disadvantage is that all volatiles are evaporated causing improper moisture content calculations. In this the operator error contributes inaccurate readings. Since in this method heating of grains are done, to conduct this method significant amount of space are required. In the indirect technique moisture content is calculated by measuring any of the physical property having relation with moisture. For example consider the resistance of the food grains as a physical property which has the relation with moisture, ie resistance will be more when moisture content in grains is less. Using this relation moisture content in food items are indirectly calculated. Moisture content can also be measured either by destructive method or non-destructive method. In non - destructive method, samples are directly used where as in destructive method the food items are cleaned and shells are removed. The time and labour cost are less for non – destructive method of moisture measurement. The capacitive type moisture meters were used to measure moisture content of food items in the early 20th century. The electrical grain moisture meters were developed considering the dielectric property of the grains. Barley and rice were used as samples [4–6,]. When current is passed through the samples like soil and wheat whose MC have to be measured, samples got cracked and were wasted in electric resistance method. This technique is
2
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951 Table 1 The comparison of different techniques. Author Jishun, Briggs and Nelson Nelson Tripathi, shukla and Gupta Ki Kim Kandala Mizukami Kiwa & Tsukada Casada & Mcintosh Kandala Davis Klomklao Yigit Yang
Frequency
200 Hz to KHz 10.5 GHz 1 MHz to 5 MHz 10 Hz to 1MHz
1 MHz to 5 MHz
1 GHz to 6 GHz 5 GHz
Year
Technique
Samples
advantages
1908 1977 1996 2002 2004 2006 2007 2008 2016 2017 2017 2018 2018
Grain moisture meter Electrical Resistance moisture meter Doule capacitor cell Differential frequency Complex RF impedance Electrical spectroscopy Magnetic strength transducer Fringing Field Capacitance sensor Chari impedance meter 3 different techniques 5555 timer A - scan radar Wi Fi LSTM deep approach
Rice and barley Soil and wheat Twelve grains are used Brown rice Pecans Tea leaf peanuts
Non Low Non Non Non Non Non Non Non Non Non Non Non
30 peanuts Low carbon 5 grams of paddy wheat Wheat
Destructive cost Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive
Fig. 1. Block diagram to measure the capacitance. Fig. 2. The circuit diagram to measure the capacitance.
cost effective [7–11]. At low frequency variation in calibration is not accountable and at high frequency calibration variation happens due to ionic conduction. So microwave signals with moisture density and attenuation at 10.5 GHz was used to measure the MC [9]. The dielectric constant of twelve food items like soybean, rice, linseed, mustard, wheat, paddy were measured in the frequency range of 200 Hz to 2 KHz using double capacitor cell with immersion method as the principle [12]. The impedance and capacitance were measured to calculate MC of tea leaves at different stages using electrical spectroscopy in the frequency range of 10 Hz to 1 MHz [13]. The magnetic strength produced by the samples was measured to calculate the moisture content. [14]. It is clear that at any designed frequency the moisture content can be obtained accurately. The main disadvantage was that only few quantities of samples were used at a time to measure moisture content. For different types of wheat, nuts, grains, inshell peanut, wood chips, dry cherries moisture content were measured by Chari V Kandala. Initially he used RF impedance method to measure the moisture content [3, 15]. He later developed (Chari Impedance) CI meter and observed the values em1 , er1 , and ep1 where er1 is the actual input voltage, em1 is the output voltage after passing through samples, ep1 is the output voltage of phase detector. The impedance and phase angle were calculated using the observed values and substituted in empirical formula developed to find the moisture content in grains [1–3, 16–19]. With a modified empirical formula, using same experiment the oil content in peanut kernels was also measured for different frequencies and compared with Soxhlet result. By using magnetic or electrical properties of food grains many indirect and non-destructive techniques for analyzing moisture content have been developed over last few decades. Most of the techniques developed to calculate the content of moisture were complex, time consuming and are using only few grams as samples.
In this paper a novel technique is been used to measure the moisture content. The technique was developed, by designing with AD 5933, an integrated circuit and it is interfaced with PC. The capacitance of paddy was measured using the circuit which helped to calculate dielectric constant and moisture content of the grains. Larger the value of dielectric constant, the moisture content is more but the increase is not uniform for all the food commodities [20]. Since this method is a non - destructive technique, no labour is required to clean and crush. The method developed is very simple to measure the moisture content, requires less time and it is very economic. Large quantity of samples can be used to measure moisture content at a time. The comparative study of all the above method is analysed [21–23]. The comparison of different techniques are tabulated in Table 1.
2. Technique 2.1. Design and testing The designed circuit is an impedance converter in which frequency sweep can be done efficiently from 30 KHz. A set of hundred readings are obtained when frequency sweep is done. The block diagram of the circuit used to measure the capacitance is shown in Fig. 1. The design of calculated resistor, Rcal and feedback resistor Rfb of non-inverting amplifier are critical. These two resistors will decide the range of impedance that can be measured using the circuit. The circuit diagram to measure the capacitance is shown in Fig. 2. The feedback resistor is calculated using the Eq. (3) which depends on the minimum impedance required to measure using the
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951
3
Table 2 The readings obtained for ceramic capacitor values 27 pF, 22 pF and 4.7 pF. Frequency (Hz)
Actual Ceramic Capacitor of 27 pF
Actual Ceramic Capacitor of 2.2 pF
Actual Ceramic Capacitor of 4.7 pF
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
30000 30002 30004 30006 30008 30010 30012 30014 30016 30018 30020 30022 30024 30026 30028 30030
195706.6676 196052.2382 195635.756 196490.0164 195295.919 195386.5463 196604.5848 195501.5615 196375.0483 195730.4209 195295.919 195501.5615 195501.5615 196698.8554 195706.6676 194749.233
27.121 27.079 27.127 27.008 27.012 27.156 26.989 27.137 27.0148 27.102 27.16 27.165 27.182 26.897 27.0975 27.224
2406208.6343 2406048.2311 2405887.8492 2405727.4888 2405567.1497 2404316.8837 2403067.7716 2405086.2607 2404926.0071 2404765.7748 2404605.5639 2404445.3743 2404285.2061 2404125.0592 2403964.9337 2404131.7887
2.2059 2.2059 2.2059 2.2059 2.2059 2.2069 2.2079 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2056
113658.5787 113894.8883 113400.5984 113393.0399 113143.7223 113136.1819 113128.6425 113121.1041 113113.5667 113106.0303 113098.495 113090.9606 113083.4272 113560.1599 113796.2714 113302.4161
4.67 4.66 4.68 4.68 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.67 4.66 4.68
Table 3 The readings obtained for the ceramic capacitor values 22 pF and 47 pF. Frequency (Hz)
Actual Ceramic Capacitor of 22 pF
Actual Ceramic Capacitor of 47 pF
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
30000 30002 30004 30006 30008 30010 30012 30014 30016 30018 30020 30022 30024 30026 30028 30030
235537.6155 234986.1998 236487.0313 233849.0899 234986.1998 234592.3209 232641.6452 234242.1066 233502.1887 234592.3209 235692.0058 234789.7366 235181.7015 235181.7015 233502.1887 234083.3707
22.5351 22.5864 22.441 22.692 22.5819 22.618 22.806 22.649 22.719 22.612 22.505 22.5903 22.551 22.549 22.271 22.652
111970.6275 112159.5442 111943.8926 112113.7928 111355.8554 112658.1654 112051.1358 112114.7013 112019.6435 111905.8461 111931.4485 111820.1685 111371.3012 111807.6292 112005.6236 111482.4883
47.404 47.321 47.409 47.334 47.653 47.099 47.351 47.321 47.358 47.403 47.389 47.433 47.621 47.432 47.345 47.564
VDD is the biasing voltage and VPK is the peak voltage. The value of VDD = 3.5 V which is supplied with the help of battery. The range of VDD required for the proper functioning of AD 5933 evaluation board is (3 - 5) V. The VPK = Vp−p = 1V and gain = 1. These setting are done on the display screen of user interface. The minimum range of impedance, Zmin or minimum reactance is calculated for capacitor value of 80 pF. R f b = 89793.34 ≈ 10K The maximum reactance or impedance, Zmax is calculated for the capacitor value of 2 pF. The value of calculated resistor, Rcal is found using the Eq. (4).
Rcal =
Zmax + Zmin 3
Rcal = 912398.9667 ≈ 1M
Fig. 3. The graph between frequency and ceramic capacitor values.
circuit, gain, biasing voltage, peak voltage and DC offset voltage.
VDD Rfb =
2
Vpk +
− 0.2 Zmin
VDD 2
− VDC o f f set
×
1 gain
(3)
(4)
(5)
The capacitance of the grains is varying from 15 to 60 pF. The voltage divider resistors, R = 50 K, R1 = 20 K and capacitor, C = 47 nF. The operational amplifier used is CMOS. The circuit was tested using the ceramic capacitor of different values. The ceramic capacitors used are 2.2 pF, 10 pF, 22 pF, 27 pF and 47 pF. Using the arrangement shown in Fig. 5 the ceramic capacitors are tested. The set of readings obtained are tabulated in Tables 2 and 3. The graph between frequency and capacitor values were plotted using the Tables 2 and 3. The Fig. 3 is the graph that shows the capacitor values remains almost constant.
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D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951 Table 4. Readings obtained for the rice heated at different temperature at the frequency of 30 KHz. Temp ( °C)
Weight (grams)
Impedance ()
Capacitor value (pF)
Predicted% MC
Wet Basis% MC
Dielectric Constant
25 30 35 40 45 50 55 60
592.3 585.5 585.03 539.81 516.3 500.75 489.95 469.3
198291.0799 201657.8193 208507.7083 220021.125 229449.5148 235195.9706 241670.4135 251268.9534
26.768 26.3211 25.4564 24.1243 23.133 22.5678 21.9632 21.1242
23.99506874 22.70459821 20.0790371 15.66594678 12.05204686 9.849431491 7.36777883 3.688660399
23.4340706 22.5448335 22.4826077 15.9889591 12.1634709 9.43584623 7.43953465 3.36671639
8.857710126 8.709827929 8.423692919 7.982892124 7.654864328 7.46783587 7.267769689 6.990138981
Fig. 4. Sample holder.
3. Sample holder After testing the circuit, the ceramic capacitor is replaced by samples placed in sample holder. To measure the moisture content of rice, sample holder / parallel plate capacitor is required to place the samples. The sample holder is shown in Fig. 4. A rectangular glass box made of thickness 5 cm is used as holder for the sample. The rectangular face of glass box is of the size 10.8 cm × 15.8 cm. The base of the rectangular glass box is of the size 5 cm × 15.8 cm. The two rectangular electrodes of the size 10.8 cm × 15.8 cm wide are placed internally on the faces of the rectangular box and it forms the two sides of parallel plate sensor. The distance between two parallel plate electrodes is 5 cm. The capacitance of parallel plate sensor was calculated using the formula (6).
C1 =
ε0 εr1 A d
=
8.854 × 10−12 × 1 × 0.108 × 0.158 =3.022pF 0.05
(6)
Fig. 6. Variation of dielectric constant with temperature.
4. Sample preparation Rice being the staple food in Kerala, India, the samples used is rice collected from the Ernakulum district, Kerala. There are different types of rice. Sample used is ponni named rice, which is used to make idly in Kerala. The rice heated at different temperature was considered as samples. The rice was heated at different temperatures (25 °C, 30 °C, 35 °C, 40 °C, 45 °C, 50 °C, 55 °C, and 60 °C) for 10 min using conventional microwave oven. The arrangement to measure the impedance consists of a PC for interfacing, bread board, evaluation board and the parallel plate sensor to place the rice. The arrangement is shown in Fig. 5. The rice after heating at a particular temperature was placed in sample holder to measure its
Fig. 5. The arrangement to measure the moisture content of grains. 1. PC, 2. Bread board, 3. Evaluation board, 4 Weighing machine, 5. Conventional microwave oven, 6. Sample holder.
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951
5
5. Result A set of hundred readings are obtained. The readings obtained at 30 0 0 0 Hz are noted in Table 3. The rice was heated for the temperature 60 °C for the 30 min for dry basis. The capacitance and weight of rice of dry basis is 20.345 pF and 453.5 grams respectively. The predicted% MC was calculated using the Eq. (8). Predicted % MC (Wet Capacitive value of sample − Dry Capacitive value of Sample) = Wet Capacitive value of sample
(8)
Wet basis% MC was calculated using the Eq. (2). The dielectric constant of rice at different temperature are obtained are calculated and tabulated in Table 3. The dielectric constant and capacitance of parallel plate sensor without samples is,
εr1 = 1andC1 = 3.022 pF
Fig. 7. Predicted% MC versus wet basis% MC.
(9)
Let C2 be the capacitance of rice heated at a particular temperature then ε r2 can be obtained by dividing Eq. (10) by (9) impedance. From the impedance capacitance are calculated using the Eq. (7) and tabulated in Table 3.
C=
1 2 ∗ 3.14 ∗ f ∗ XC
(7)
C2 = C2 = C1
ε0 εr2 A d
εr2 εr1
Fig. 8. (a) The graph between frequency versus impedance. (b) The graph between frequency versus impedance.
(10)
(11)
6
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951
Fig. 9. (a) The graph between frequency versus corrected capacitance. (b) The graph between frequency versus corrected capacitance.
Similarly the dielectric constant of rice heated at different temperature is calculated. As the temperature increases the dielectric constant decreases as shown in Fig. 6. The predicted% MC and wet basis% MC have a linear relation which is shown in Fig. 7. 6. Error correction A set of hundred readings are obtained using the circuit shown in Fig. 5. The graph of 10 pF, 22 pF, 27 pF and 47 pF were plotted and error correction were done using matlab programming. The capacitance value obtained was calculated from set of hun-
dred readings of impedance. The graph of impedance using mat lab and shown typical graphs as shown in Fig. 8 a and b. The capacitance value obtained by calculation were plotted using mat lab and shown typical graphs as shown in and Fig. 9 a and b. Bubbles shows the raw data of capacitance and straight line indicate the corrected data of capacitance (Fig. 10). The weight and hundred set of impedance readings obtained for rice heated at 25 °C and dry basis rice sample were given as input to the mat lab program as shown in Fig. 11. The result obtained after uploading the data for matlab programming is shown in Fig. 11.
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951
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Fig. 10. Screen to upload the data to calculate the capacitance, oven and predicted% MC.
Fig. 11. Result screen after running the Mat Lab program.
7. Conclusion Though the climatic conditions are varying due to global warming, the moisture content of grains has to be measured frequently to avoid its wastage. Humidity effect the moisture content of grains. As humidity is varying moisture content of food items also varies. The method developed to measure the moisture content of grains, help to measure it quickly and accurately. A set of hundred readings are obtained in fraction of seconds. The amount of grains used to measure the content of moisture is large. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. Declaration of Competing Interest This paper has not communicated anywhere till this moment, now only it is communicated to your esteemed journal for the publication with the knowledge of all co-authors. References [1] C.K. Kandala, S.O. Nelson, Rf impedance method for estimating moisture content in small samples of in-shell peanuts, IEEE Trans. Instrument. Measure. 56 (no.3) (June 2007). [2] C.K. Kandala, C.L. Butts, S.O. Nelson, Capacitance sensor for non-destructive measurement of moisture content in nuts and grain, IEEE Trans. Instrument. Measure. 56 (5) (October. 2007) 1809–1813. [3] C.V. Kandala, J. Sundaram, Nondestructive measurement of moisture content using a parallel plate capacitance sensor for nuts and grain„ IEEE Sens. J. 10 (7) (July 2010) 1282–1287.
[4] O. Nelson S, Dielectric properties of agriculture products -measurements and applications, IEEE Trans. Electr. Insul. 26 (no.5) (1991) pp.845–869. [5] S.O. Nelson, Use of electrical properties for grain moisture measurement, J. Microw. Power vol.12 (no.1) (1977) 67–72. [6] O. Nelson S, A. Kraszewski, S. Trabelsi, C. Lawrence K, Using cereal grain permittivity for sensing moisture content, IEEE Trans. Instrument. Measure. 49 (3) (20 0 0) 470–475. [7] G. Briggs, An electrical resistance method for the rapid determination of the moisture content of grain, Am. Assoc. Advance. Sci. vol.28 (no.727) (December 1908) pp.810–813. [8] J. Jiang, H. Ji, Modeling of moisture test for grain based on neural network and dielectric loss factor, IEEE Comp. Soc. Second Int. Sympos. Comp. Intell. Des. (November 10 2009). [9] K.-B. Kim, J. –Heon Kim, S.S. Lee, S.H. Noh, Measurement of grain moisture content using microwave attenuation at 10.5ghz and moisture density, IEEE Trans. Instrument. Measure. vol.51 (no.1) (February 2002). [10] O. Nelson S, G. Bartley, Measuring frequency and temperature dependent permittivity of food materials, IEEE Trans. Instrument. Measure. vol.51 (no.4) (August 2002) 589–592. [11] O. Nelson S, Agriculture application of dielectric measurements, IEEE Trans. Instrument. Measure. vol.51 (no.4) (May 2005) 688–702. [12] R.K. T.ripathi, M. Gupta, J.P. S.hukla, Capacitance technique for measuring moisture content using dielectric data- an immersion method, in: ICDL International conference on conduction ad breakdown in dielectric liquids, Roma, Italy, July 15-19, 1996, pp. 440–442. [13] Y. Mizukami, Y. Sawai, Y. Yamaguchi, Moisture content of tea leaves by electrical impedance and capacitance, Biosyst. Eng. vol.93 (No.3) (2006) 293–299 www.sciencedirect.com. [14] K. Tsukada, T. Kiwa, Magnetic measurement of moisture content of grain, IEEE Trans. Magnet. vol.43 (No.6) (June 2007). [15] V.K. Kandala, Moisture determination in single peanut pods by complex RF impedance measurement, IEEE Trans. Instrument. Measure. 53 (6) (2004) 1493–1496. [16] C.V. Kandala, N. Puppala., Capacitance sensors for nondestructive moisture determination in grain, nuts and bio-fuel materials, ICST (2012). [17] C.V. Kandala, N. Puppala., Parallel plate capacitance sensors for nondestructive moisture content of different types of wheat, Sens. Appl. Sympos. IEEE Bresua (February 2012) 1–5. [18] C.V. Kandala, R. Avula, V. Settaluri, R.S. Reddy, N. Puppala, Sensing the moisture content of dry cherries-A rapid and non-destructive method, Sci. Res. Food Nutr. Sci. 4 (2013) 38–42. [19] “Moisture Measurement-Peanuts,”, American Society of Agricultural Engineers, St. Joseph, ASAE Standard (20 0 0). [20] C.V. Kandala, R.C.N. Rachaputi, D.O. Connor, International conference on educational and information technology (ICEIT 2010) scientific research, J. Sens. Technol. 3 (September 2013) pp.42–46. [21] Divya.Nath K., Sudha Ramasamy, Y.M. Saranya Das, Prabhu Ramanathan, A review on non-destructive methods for the measurement of moisture contents in food items” presented in circuit, power and computing technologies (ICCPCT), 2015 International Conference, IEEE Digital library, 2015 Publisher, doi:10.1109/ICCPCT7159367.
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[22] S. Das, Y. M, D.N. K, S. Ramaswamy, P. Ramanathan, A review on sensor based methods for moisture content determination of agricultural commodities, Int. J. Appl. Eng. Res., ISSN 10 (No.2) (2015) 1697–1703 0973-4562pp.. [23] D.N. K., R. P, Non-destructive methods for the measurement of moisture contents – a review, Sens. Rev. Vol.37 (no.1) (2017) pp.71–77. Divya Nath K. completed her Ph.D. in Electrical Engineering from VIT University, Vellore, Tamil Nadu, India. In 2007 she joined SCMS School of Engineering as lecturer in Department of Electrical Engineering She became Assistant Professor in 2011. She has published nearly 7 papers as author / co-author, in peer reviewed journals.
Prabhu K. Ramanathan received his Ph.D. in Electrical Engineering from VIT University, Vellore, India (2013). In 2019, he joined University West, Trollhättan, Sweden as a Lecturer in Department of Engineering Science. He has served as a Head of the Control and Automation Department in VIT University. He has experience in semiconductor industries (TSMC, UMC, Chartered) as an Application Engineer in KLA-Tencor. He is the author/co-author of over 30 publications in peer-reviewed journals. His research interests include Sensors, Signal Conditioning, Collaborative Robot, Automation, Bio-Medical Instrumentation and Data Acquisition Systems.
Contents lists available at ScienceDirect
Microprocessors and Microsystems journal homepage: www.elsevier.com/locate/micpro
Interfaced circuit using a non- destructive method for moisture measurement Divya Nath K a,∗, Prabhu Ramanathan b a b
SCMS School of Engineering & Technology, Karukutty, Ernakulam, Kerala 683582, India Universitetslektor, Department of Engineering Science, University West, Nohabgatan 18A, Building 73, Trollhättan, Sweden
a r t i c l e
i n f o
Article history: Received 28 September 2019 Revised 4 December 2019 Accepted 7 December 2019 Available online 9 December 2019 Keywords: Error correction Moisture content measurement Non-destructive method and relative permitivity
a b s t r a c t Analysing the moisture in stored products like harvested cereal grains and their products, peas, beans, oil-seeds, copra, cocoa beans, spices etc. is very much important to avoid the fungi growth. Moisture can be present in grain in more than one state, i.e. as bound, adsorbed or absorbed water. A designed, integrated circuit was interfaced with personal computer to measure the capacitance which in turn help to calculate the moisture content of rice. The interfaced circuit was tested by measuring the capacitance of different ceramic capacitor. This technique is fast, reliable, accurate and gives hundred set of readings in few seconds. Moisture contents are measured in percentage. The error correction was done with the help of mat - lab programming. © 2019 Elsevier B.V. All rights reserved.
1. Introduction Agriculture is a main source of income in a developing country like India. The moisture content of grains depends upon the humidity and the temperature of the atmosphere. As the humidity and temperature of the atmosphere varies, it is very much necessary to measure the moisture content of grains frequently. Moisture content is a factor critical to the shelf life. The moisture content in food grains like paddy, rice, etc. should be known by the farmers for its trading, processing and storage else fungi affect the grains and become useless [1,2]. At the time of harvesting, 20% - 40% will be the approximate amount of water content in food items and that has to be reduced to 10% −13% for trading, processing, and storing [3]. The direct or indirect method can be used to measure the moisture content. In direct technique moisture content is calculated using the standard equation (1) or (2).
Dry basis % MC (Wet weight of sample − Dry weight of Sample) = Dry weight of sample Wet basis % MC (Wet weight of sample − Dry weight of Sample) =, Wet weight of sample ∗
Corresponding author. E-mail address: [email protected] (D.N. K).
https://doi.org/10.1016/j.micpro.2019.102951 0141-9331/© 2019 Elsevier B.V. All rights reserved.
(1)
(2)
The difference in the two weights (loss on drying) is then compared with either the original weight (wet-base test) or final weight (dry-base test) and the moisture content are calculated. The direct method does not require calibration, help to measure high levels of moisture and are cheaper than more sophisticated instruments. The disadvantage is that all volatiles are evaporated causing improper moisture content calculations. In this the operator error contributes inaccurate readings. Since in this method heating of grains are done, to conduct this method significant amount of space are required. In the indirect technique moisture content is calculated by measuring any of the physical property having relation with moisture. For example consider the resistance of the food grains as a physical property which has the relation with moisture, ie resistance will be more when moisture content in grains is less. Using this relation moisture content in food items are indirectly calculated. Moisture content can also be measured either by destructive method or non-destructive method. In non - destructive method, samples are directly used where as in destructive method the food items are cleaned and shells are removed. The time and labour cost are less for non – destructive method of moisture measurement. The capacitive type moisture meters were used to measure moisture content of food items in the early 20th century. The electrical grain moisture meters were developed considering the dielectric property of the grains. Barley and rice were used as samples [4–6,]. When current is passed through the samples like soil and wheat whose MC have to be measured, samples got cracked and were wasted in electric resistance method. This technique is
2
D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951 Table 1 The comparison of different techniques. Author Jishun, Briggs and Nelson Nelson Tripathi, shukla and Gupta Ki Kim Kandala Mizukami Kiwa & Tsukada Casada & Mcintosh Kandala Davis Klomklao Yigit Yang
Frequency
200 Hz to KHz 10.5 GHz 1 MHz to 5 MHz 10 Hz to 1MHz
1 MHz to 5 MHz
1 GHz to 6 GHz 5 GHz
Year
Technique
Samples
advantages
1908 1977 1996 2002 2004 2006 2007 2008 2016 2017 2017 2018 2018
Grain moisture meter Electrical Resistance moisture meter Doule capacitor cell Differential frequency Complex RF impedance Electrical spectroscopy Magnetic strength transducer Fringing Field Capacitance sensor Chari impedance meter 3 different techniques 5555 timer A - scan radar Wi Fi LSTM deep approach
Rice and barley Soil and wheat Twelve grains are used Brown rice Pecans Tea leaf peanuts
Non Low Non Non Non Non Non Non Non Non Non Non Non
30 peanuts Low carbon 5 grams of paddy wheat Wheat
Destructive cost Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive Destructive
Fig. 1. Block diagram to measure the capacitance. Fig. 2. The circuit diagram to measure the capacitance.
cost effective [7–11]. At low frequency variation in calibration is not accountable and at high frequency calibration variation happens due to ionic conduction. So microwave signals with moisture density and attenuation at 10.5 GHz was used to measure the MC [9]. The dielectric constant of twelve food items like soybean, rice, linseed, mustard, wheat, paddy were measured in the frequency range of 200 Hz to 2 KHz using double capacitor cell with immersion method as the principle [12]. The impedance and capacitance were measured to calculate MC of tea leaves at different stages using electrical spectroscopy in the frequency range of 10 Hz to 1 MHz [13]. The magnetic strength produced by the samples was measured to calculate the moisture content. [14]. It is clear that at any designed frequency the moisture content can be obtained accurately. The main disadvantage was that only few quantities of samples were used at a time to measure moisture content. For different types of wheat, nuts, grains, inshell peanut, wood chips, dry cherries moisture content were measured by Chari V Kandala. Initially he used RF impedance method to measure the moisture content [3, 15]. He later developed (Chari Impedance) CI meter and observed the values em1 , er1 , and ep1 where er1 is the actual input voltage, em1 is the output voltage after passing through samples, ep1 is the output voltage of phase detector. The impedance and phase angle were calculated using the observed values and substituted in empirical formula developed to find the moisture content in grains [1–3, 16–19]. With a modified empirical formula, using same experiment the oil content in peanut kernels was also measured for different frequencies and compared with Soxhlet result. By using magnetic or electrical properties of food grains many indirect and non-destructive techniques for analyzing moisture content have been developed over last few decades. Most of the techniques developed to calculate the content of moisture were complex, time consuming and are using only few grams as samples.
In this paper a novel technique is been used to measure the moisture content. The technique was developed, by designing with AD 5933, an integrated circuit and it is interfaced with PC. The capacitance of paddy was measured using the circuit which helped to calculate dielectric constant and moisture content of the grains. Larger the value of dielectric constant, the moisture content is more but the increase is not uniform for all the food commodities [20]. Since this method is a non - destructive technique, no labour is required to clean and crush. The method developed is very simple to measure the moisture content, requires less time and it is very economic. Large quantity of samples can be used to measure moisture content at a time. The comparative study of all the above method is analysed [21–23]. The comparison of different techniques are tabulated in Table 1.
2. Technique 2.1. Design and testing The designed circuit is an impedance converter in which frequency sweep can be done efficiently from 30 KHz. A set of hundred readings are obtained when frequency sweep is done. The block diagram of the circuit used to measure the capacitance is shown in Fig. 1. The design of calculated resistor, Rcal and feedback resistor Rfb of non-inverting amplifier are critical. These two resistors will decide the range of impedance that can be measured using the circuit. The circuit diagram to measure the capacitance is shown in Fig. 2. The feedback resistor is calculated using the Eq. (3) which depends on the minimum impedance required to measure using the
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Table 2 The readings obtained for ceramic capacitor values 27 pF, 22 pF and 4.7 pF. Frequency (Hz)
Actual Ceramic Capacitor of 27 pF
Actual Ceramic Capacitor of 2.2 pF
Actual Ceramic Capacitor of 4.7 pF
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
30000 30002 30004 30006 30008 30010 30012 30014 30016 30018 30020 30022 30024 30026 30028 30030
195706.6676 196052.2382 195635.756 196490.0164 195295.919 195386.5463 196604.5848 195501.5615 196375.0483 195730.4209 195295.919 195501.5615 195501.5615 196698.8554 195706.6676 194749.233
27.121 27.079 27.127 27.008 27.012 27.156 26.989 27.137 27.0148 27.102 27.16 27.165 27.182 26.897 27.0975 27.224
2406208.6343 2406048.2311 2405887.8492 2405727.4888 2405567.1497 2404316.8837 2403067.7716 2405086.2607 2404926.0071 2404765.7748 2404605.5639 2404445.3743 2404285.2061 2404125.0592 2403964.9337 2404131.7887
2.2059 2.2059 2.2059 2.2059 2.2059 2.2069 2.2079 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2059 2.2056
113658.5787 113894.8883 113400.5984 113393.0399 113143.7223 113136.1819 113128.6425 113121.1041 113113.5667 113106.0303 113098.495 113090.9606 113083.4272 113560.1599 113796.2714 113302.4161
4.67 4.66 4.68 4.68 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.69 4.67 4.66 4.68
Table 3 The readings obtained for the ceramic capacitor values 22 pF and 47 pF. Frequency (Hz)
Actual Ceramic Capacitor of 22 pF
Actual Ceramic Capacitor of 47 pF
Impedance (Ω)
Obtained Capacitor Value (pF)
Impedance (Ω)
Obtained Capacitor Value (pF)
30000 30002 30004 30006 30008 30010 30012 30014 30016 30018 30020 30022 30024 30026 30028 30030
235537.6155 234986.1998 236487.0313 233849.0899 234986.1998 234592.3209 232641.6452 234242.1066 233502.1887 234592.3209 235692.0058 234789.7366 235181.7015 235181.7015 233502.1887 234083.3707
22.5351 22.5864 22.441 22.692 22.5819 22.618 22.806 22.649 22.719 22.612 22.505 22.5903 22.551 22.549 22.271 22.652
111970.6275 112159.5442 111943.8926 112113.7928 111355.8554 112658.1654 112051.1358 112114.7013 112019.6435 111905.8461 111931.4485 111820.1685 111371.3012 111807.6292 112005.6236 111482.4883
47.404 47.321 47.409 47.334 47.653 47.099 47.351 47.321 47.358 47.403 47.389 47.433 47.621 47.432 47.345 47.564
VDD is the biasing voltage and VPK is the peak voltage. The value of VDD = 3.5 V which is supplied with the help of battery. The range of VDD required for the proper functioning of AD 5933 evaluation board is (3 - 5) V. The VPK = Vp−p = 1V and gain = 1. These setting are done on the display screen of user interface. The minimum range of impedance, Zmin or minimum reactance is calculated for capacitor value of 80 pF. R f b = 89793.34 ≈ 10K The maximum reactance or impedance, Zmax is calculated for the capacitor value of 2 pF. The value of calculated resistor, Rcal is found using the Eq. (4).
Rcal =
Zmax + Zmin 3
Rcal = 912398.9667 ≈ 1M
Fig. 3. The graph between frequency and ceramic capacitor values.
circuit, gain, biasing voltage, peak voltage and DC offset voltage.
VDD Rfb =
2
Vpk +
− 0.2 Zmin
VDD 2
− VDC o f f set
×
1 gain
(3)
(4)
(5)
The capacitance of the grains is varying from 15 to 60 pF. The voltage divider resistors, R = 50 K, R1 = 20 K and capacitor, C = 47 nF. The operational amplifier used is CMOS. The circuit was tested using the ceramic capacitor of different values. The ceramic capacitors used are 2.2 pF, 10 pF, 22 pF, 27 pF and 47 pF. Using the arrangement shown in Fig. 5 the ceramic capacitors are tested. The set of readings obtained are tabulated in Tables 2 and 3. The graph between frequency and capacitor values were plotted using the Tables 2 and 3. The Fig. 3 is the graph that shows the capacitor values remains almost constant.
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D.N. K and P. Ramanathan / Microprocessors and Microsystems 73 (2020) 102951 Table 4. Readings obtained for the rice heated at different temperature at the frequency of 30 KHz. Temp ( °C)
Weight (grams)
Impedance ()
Capacitor value (pF)
Predicted% MC
Wet Basis% MC
Dielectric Constant
25 30 35 40 45 50 55 60
592.3 585.5 585.03 539.81 516.3 500.75 489.95 469.3
198291.0799 201657.8193 208507.7083 220021.125 229449.5148 235195.9706 241670.4135 251268.9534
26.768 26.3211 25.4564 24.1243 23.133 22.5678 21.9632 21.1242
23.99506874 22.70459821 20.0790371 15.66594678 12.05204686 9.849431491 7.36777883 3.688660399
23.4340706 22.5448335 22.4826077 15.9889591 12.1634709 9.43584623 7.43953465 3.36671639
8.857710126 8.709827929 8.423692919 7.982892124 7.654864328 7.46783587 7.267769689 6.990138981
Fig. 4. Sample holder.
3. Sample holder After testing the circuit, the ceramic capacitor is replaced by samples placed in sample holder. To measure the moisture content of rice, sample holder / parallel plate capacitor is required to place the samples. The sample holder is shown in Fig. 4. A rectangular glass box made of thickness 5 cm is used as holder for the sample. The rectangular face of glass box is of the size 10.8 cm × 15.8 cm. The base of the rectangular glass box is of the size 5 cm × 15.8 cm. The two rectangular electrodes of the size 10.8 cm × 15.8 cm wide are placed internally on the faces of the rectangular box and it forms the two sides of parallel plate sensor. The distance between two parallel plate electrodes is 5 cm. The capacitance of parallel plate sensor was calculated using the formula (6).
C1 =
ε0 εr1 A d
=
8.854 × 10−12 × 1 × 0.108 × 0.158 =3.022pF 0.05
(6)
Fig. 6. Variation of dielectric constant with temperature.
4. Sample preparation Rice being the staple food in Kerala, India, the samples used is rice collected from the Ernakulum district, Kerala. There are different types of rice. Sample used is ponni named rice, which is used to make idly in Kerala. The rice heated at different temperature was considered as samples. The rice was heated at different temperatures (25 °C, 30 °C, 35 °C, 40 °C, 45 °C, 50 °C, 55 °C, and 60 °C) for 10 min using conventional microwave oven. The arrangement to measure the impedance consists of a PC for interfacing, bread board, evaluation board and the parallel plate sensor to place the rice. The arrangement is shown in Fig. 5. The rice after heating at a particular temperature was placed in sample holder to measure its
Fig. 5. The arrangement to measure the moisture content of grains. 1. PC, 2. Bread board, 3. Evaluation board, 4 Weighing machine, 5. Conventional microwave oven, 6. Sample holder.
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5. Result A set of hundred readings are obtained. The readings obtained at 30 0 0 0 Hz are noted in Table 3. The rice was heated for the temperature 60 °C for the 30 min for dry basis. The capacitance and weight of rice of dry basis is 20.345 pF and 453.5 grams respectively. The predicted% MC was calculated using the Eq. (8). Predicted % MC (Wet Capacitive value of sample − Dry Capacitive value of Sample) = Wet Capacitive value of sample
(8)
Wet basis% MC was calculated using the Eq. (2). The dielectric constant of rice at different temperature are obtained are calculated and tabulated in Table 3. The dielectric constant and capacitance of parallel plate sensor without samples is,
εr1 = 1andC1 = 3.022 pF
Fig. 7. Predicted% MC versus wet basis% MC.
(9)
Let C2 be the capacitance of rice heated at a particular temperature then ε r2 can be obtained by dividing Eq. (10) by (9) impedance. From the impedance capacitance are calculated using the Eq. (7) and tabulated in Table 3.
C=
1 2 ∗ 3.14 ∗ f ∗ XC
(7)
C2 = C2 = C1
ε0 εr2 A d
εr2 εr1
Fig. 8. (a) The graph between frequency versus impedance. (b) The graph between frequency versus impedance.
(10)
(11)
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Fig. 9. (a) The graph between frequency versus corrected capacitance. (b) The graph between frequency versus corrected capacitance.
Similarly the dielectric constant of rice heated at different temperature is calculated. As the temperature increases the dielectric constant decreases as shown in Fig. 6. The predicted% MC and wet basis% MC have a linear relation which is shown in Fig. 7. 6. Error correction A set of hundred readings are obtained using the circuit shown in Fig. 5. The graph of 10 pF, 22 pF, 27 pF and 47 pF were plotted and error correction were done using matlab programming. The capacitance value obtained was calculated from set of hun-
dred readings of impedance. The graph of impedance using mat lab and shown typical graphs as shown in Fig. 8 a and b. The capacitance value obtained by calculation were plotted using mat lab and shown typical graphs as shown in and Fig. 9 a and b. Bubbles shows the raw data of capacitance and straight line indicate the corrected data of capacitance (Fig. 10). The weight and hundred set of impedance readings obtained for rice heated at 25 °C and dry basis rice sample were given as input to the mat lab program as shown in Fig. 11. The result obtained after uploading the data for matlab programming is shown in Fig. 11.
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Fig. 10. Screen to upload the data to calculate the capacitance, oven and predicted% MC.
Fig. 11. Result screen after running the Mat Lab program.
7. Conclusion Though the climatic conditions are varying due to global warming, the moisture content of grains has to be measured frequently to avoid its wastage. Humidity effect the moisture content of grains. As humidity is varying moisture content of food items also varies. The method developed to measure the moisture content of grains, help to measure it quickly and accurately. A set of hundred readings are obtained in fraction of seconds. The amount of grains used to measure the content of moisture is large. Ethical approval This article does not contain any studies with human participants or animals performed by any of the authors. Declaration of Competing Interest This paper has not communicated anywhere till this moment, now only it is communicated to your esteemed journal for the publication with the knowledge of all co-authors. References [1] C.K. Kandala, S.O. Nelson, Rf impedance method for estimating moisture content in small samples of in-shell peanuts, IEEE Trans. Instrument. Measure. 56 (no.3) (June 2007). [2] C.K. Kandala, C.L. Butts, S.O. Nelson, Capacitance sensor for non-destructive measurement of moisture content in nuts and grain, IEEE Trans. Instrument. Measure. 56 (5) (October. 2007) 1809–1813. [3] C.V. Kandala, J. Sundaram, Nondestructive measurement of moisture content using a parallel plate capacitance sensor for nuts and grain„ IEEE Sens. J. 10 (7) (July 2010) 1282–1287.
[4] O. Nelson S, Dielectric properties of agriculture products -measurements and applications, IEEE Trans. Electr. Insul. 26 (no.5) (1991) pp.845–869. [5] S.O. Nelson, Use of electrical properties for grain moisture measurement, J. Microw. Power vol.12 (no.1) (1977) 67–72. [6] O. Nelson S, A. Kraszewski, S. Trabelsi, C. Lawrence K, Using cereal grain permittivity for sensing moisture content, IEEE Trans. Instrument. Measure. 49 (3) (20 0 0) 470–475. [7] G. Briggs, An electrical resistance method for the rapid determination of the moisture content of grain, Am. Assoc. Advance. Sci. vol.28 (no.727) (December 1908) pp.810–813. [8] J. Jiang, H. Ji, Modeling of moisture test for grain based on neural network and dielectric loss factor, IEEE Comp. Soc. Second Int. Sympos. Comp. Intell. Des. (November 10 2009). [9] K.-B. Kim, J. –Heon Kim, S.S. Lee, S.H. Noh, Measurement of grain moisture content using microwave attenuation at 10.5ghz and moisture density, IEEE Trans. Instrument. Measure. vol.51 (no.1) (February 2002). [10] O. Nelson S, G. Bartley, Measuring frequency and temperature dependent permittivity of food materials, IEEE Trans. Instrument. Measure. vol.51 (no.4) (August 2002) 589–592. [11] O. Nelson S, Agriculture application of dielectric measurements, IEEE Trans. Instrument. Measure. vol.51 (no.4) (May 2005) 688–702. [12] R.K. T.ripathi, M. Gupta, J.P. S.hukla, Capacitance technique for measuring moisture content using dielectric data- an immersion method, in: ICDL International conference on conduction ad breakdown in dielectric liquids, Roma, Italy, July 15-19, 1996, pp. 440–442. [13] Y. Mizukami, Y. Sawai, Y. Yamaguchi, Moisture content of tea leaves by electrical impedance and capacitance, Biosyst. Eng. vol.93 (No.3) (2006) 293–299 www.sciencedirect.com. [14] K. Tsukada, T. Kiwa, Magnetic measurement of moisture content of grain, IEEE Trans. Magnet. vol.43 (No.6) (June 2007). [15] V.K. Kandala, Moisture determination in single peanut pods by complex RF impedance measurement, IEEE Trans. Instrument. Measure. 53 (6) (2004) 1493–1496. [16] C.V. Kandala, N. Puppala., Capacitance sensors for nondestructive moisture determination in grain, nuts and bio-fuel materials, ICST (2012). [17] C.V. Kandala, N. Puppala., Parallel plate capacitance sensors for nondestructive moisture content of different types of wheat, Sens. Appl. Sympos. IEEE Bresua (February 2012) 1–5. [18] C.V. Kandala, R. Avula, V. Settaluri, R.S. Reddy, N. Puppala, Sensing the moisture content of dry cherries-A rapid and non-destructive method, Sci. Res. Food Nutr. Sci. 4 (2013) 38–42. [19] “Moisture Measurement-Peanuts,”, American Society of Agricultural Engineers, St. Joseph, ASAE Standard (20 0 0). [20] C.V. Kandala, R.C.N. Rachaputi, D.O. Connor, International conference on educational and information technology (ICEIT 2010) scientific research, J. Sens. Technol. 3 (September 2013) pp.42–46. [21] Divya.Nath K., Sudha Ramasamy, Y.M. Saranya Das, Prabhu Ramanathan, A review on non-destructive methods for the measurement of moisture contents in food items” presented in circuit, power and computing technologies (ICCPCT), 2015 International Conference, IEEE Digital library, 2015 Publisher, doi:10.1109/ICCPCT7159367.
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[22] S. Das, Y. M, D.N. K, S. Ramaswamy, P. Ramanathan, A review on sensor based methods for moisture content determination of agricultural commodities, Int. J. Appl. Eng. Res., ISSN 10 (No.2) (2015) 1697–1703 0973-4562pp.. [23] D.N. K., R. P, Non-destructive methods for the measurement of moisture contents – a review, Sens. Rev. Vol.37 (no.1) (2017) pp.71–77. Divya Nath K. completed her Ph.D. in Electrical Engineering from VIT University, Vellore, Tamil Nadu, India. In 2007 she joined SCMS School of Engineering as lecturer in Department of Electrical Engineering She became Assistant Professor in 2011. She has published nearly 7 papers as author / co-author, in peer reviewed journals.
Prabhu K. Ramanathan received his Ph.D. in Electrical Engineering from VIT University, Vellore, India (2013). In 2019, he joined University West, Trollhättan, Sweden as a Lecturer in Department of Engineering Science. He has served as a Head of the Control and Automation Department in VIT University. He has experience in semiconductor industries (TSMC, UMC, Chartered) as an Application Engineer in KLA-Tencor. He is the author/co-author of over 30 publications in peer-reviewed journals. His research interests include Sensors, Signal Conditioning, Collaborative Robot, Automation, Bio-Medical Instrumentation and Data Acquisition Systems.