Laboratory performance evaluation of a low-cost capacitive soil moisture sensor for fine- and medium-textured soils

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Natthapol Laowatthanarassamee
Pongsakorn Heepkaew
Watcharachai Jainam
Napassakorn Chulee
Chuphan Chompuchan

Abstract

          IoT soil moisture sensors, especially capacitive types, play a vital role in precision irrigation due to offering cost-effective and rapid soil moisture monitoring. However, low-cost capacitive sensors often require accurate calibration specific to agricultural soil textures. This study focuses on calibrating Soil Stick sensors, commercially available in Thailand, using fine and medium-textured soils from agricultural areas in Phetchaburi Province. The calibration process establishes an equation relating the sensor's output voltage, connected to the NodeMCU ESP32 microcontroller board, to volumetric water content. The calibration results revealed a third-degree polynomial equation with an RMSE value of 0.07 cm3.cm-3. The performance evaluation was conducted using the calibrated Soil Stick sensor compared to the SM100 sensor, a factory-calibrated for various soil types. The Soil Stick sensor exhibited a lower RMSE value of 0.07 cm3.cm-3, whereas the SM100 sensor had an RMSE value of 0.08 cm3 cm-3. Furthermore, the confidence index of measurement (CI) demonstrated that the Soil Stick sensor achieved a value of 0.78, indicating a very good measurement performance, while the SM100 sensor yielded a CI of 0.66, denoting good measurement performance. The sensor's accuracy in soil moisture measurement was enhanced through calibration, enabling efficient control in irrigation applications.

Article Details

How to Cite
Laowatthanarassamee, N., Heepkaew, P., Jainam, W., Chulee, N., & Chompuchan, C. (2023). Laboratory performance evaluation of a low-cost capacitive soil moisture sensor for fine- and medium-textured soils. RMUTSB ACADEMIC JOURNAL, 11(2), 254–264. Retrieved from https://li01.tci-thaijo.org/index.php/rmutsb-sci/article/view/258687
Section
Research Article

References

Bitella, G., Rossi, R., Bochicchio, R., Perniola, M., & Amato, M. (2014). A novel low-cost open-hardware platform for monitoring soil water content and multiple soil-air-vegetation parameters. Sensors, 14(10), 19639-19659.

Burt, R. (2011). Soil survey laboratory information manual: Soil survey investigations report No. 45, Version 2.0. Lincoln: United States Department of Agriculture, Natural Resources Conservation Service.

Chen, D., Chen, N., Zhang, X., Ma, H., & Chen, Z. (2021). Next-generation soil moisture sensor web: High-density in situ observation over NB-IoT. IEEE Internet of Things Journal, 8(17), 13367-13383.

Dong, Y., Miller, S., & Kelley, L. (2020). Performance evaluation of soil moisture sensors in coarse- and fine-textured Michigan agricultural soils. Agriculture, 10(12), 598.

FAO. (2023). Standard operating procedure for soil moisture content by gravimetric method. Rome: Food and Agriculture Organization of the United Nations.

González-Teruel, J. D., Torres-Sánchez, R., Blaya-Ros, P. J., Toledo-Moreo, A. B., Jiménez-Buendía, M., & Soto-Valles, F. (2019). Design and calibration of a low-cost SDI-12 soil moisture sensor. Sensors, 19(3), 491.

Jiménez, A. Á. C., Almeida, C. D. G. C. de, Santos Júnior, J. A., Morais, J. E. F. de, Almeida, B. G. de, & Andrade, F. H. N. de. (2019). Accuracy of capacitive sensors for estimating soil moisture in northeastern Brazil. Soil and Tillage Research, 195, 104413.

Kulmány, I. M., Bede-Fazekas, Á., Beslin, A., Giczi, Z., Milics, G., Kovács, B., Kovács, M., Ambrus, B., Bede, L., & Vona, V. (2022). Calibration of an Arduino-based low-cost capacitive soil moisture sensor for smart agriculture. Journal of Hydrology and Hydromechanics, 70(3), 330-340.

Liang, Z., Liu, X., Xiong, J., & Xiao, J. (2020). Water allocation and integrative management of precision irrigation: A systematic review. Water, 12(11), 3135.

Pahuja, R. (2022). Development of semi-automatic recalibration system and curve-fit models for smart soil moisture sensor. Measurement, 203, 111907.

Pramanik, M., Khanna, M., Singh, M., Singh, D. K., Sudhishri, S., Bhatia, A., & Ranjan, R. (2022). Automation of soil moisture sensor-based basin irrigation system. Smart Agricultural Technology, 2, 100032.

Saxton, K. E., Rawls, W. J., Romberger, J. S., & Papendick, R. I. (1986). Estimating generalized soil-water characteristics from texture. Soil Science Society of America Journal, 50(4), 1031-1036.

Shah, N. G., & Das, I. (2012). Precision irrigation: Sensor network based irrigation. In M. Kumar (Ed.), Problems, Perspectives and Challenges of Agricultural Water Management (pp. 217-232). Rijeka: IntechOpen.

Songara, J. C., & Patel, J. N. (2022). Calibration and comparison of various sensors for soil moisture measurement. Measurement, 197, 111301.

Schwartz, M., Li, Z., Sakaki, T., Moradi, A., & Smits, K. (2019). Accounting for temperature effects on the performance of soil moisture sensors in sandy soils. Soil Science Society of America Journal, 83(5), 1319-1323.

Togneri, R., Kamienski, C., Dantas, R., Prati, R., Toscano, A., Soininen, J. P., & Cinotti, T. S. (2019). Advancing IoT-based smart irrigation. IEEE Internet of Things Magazine, 2(4), 20-25.

Yu, L., Gao, W., Shamshiri, R. R., Tao, S., Ren, Y., Zhang, Y., & Su, G. (2021). Review of research progress on soil moisture sensor technology. International Journal of Agricultural and Biological Engineering, 14(4), 32-42.