All Issue

2025 Vol.7, Issue 4 Preview Page

Review Article

Moisture sensing technologies for grain storage: From single sensors to intelligent multisensory system
Amiruddin Aziz12
,
Gilbert Mugwaneza13
,
Jean Claude Nshimiyimana14
,
Alisabela Dhiya Rachmah15
,
Tusan Park678*
1Department of Food Security and Agricultural Development, Kyungpook National University, Daegu 41566, Korea
2Research Center for Process and Manufacturing Industry Technology, National Research and Innovation Agency (BRIN), Republic of Indonesia
3Department of Irrigation Innovation and Technology Transfer, Rwanda Agriculture and Animal Resources Development Board (RAB), 5016, Rwanda
4Department of Research and Technology Transfer, Agricultural extension, Training and farmer development unit, Rwanda Agriculture and Animal Resources Development Board (RAB), 5016, Rwanda
5Directorate General of Horticulture, Ministry of Agriculture, 12520, Republic of Indonesia
6Department of Smart Bio-Industrial Mechanical Engineering, Kyungpook National University, Daegu 41566, Korea
7Smart Agriculture Innovation Center, Kyungpook National University, Daegu 41566, Korea
8Department of Applied Biosciences, Kyungpook National University, Daegu 41566, Korea
*Corresponding Author
31 December 2025. pp. 421-435
PDF XML Citation
Abstract

Moisture content is a critical parameter influencing grain quality during storage, as it directly affects microbial activity, respiration, and post-harvest deterioration. Accurate and timely monitoring of grain moisture is therefore essential to minimize storage losses and preserve quality, particularly under long-term storage conditions. This study presents a systematic review and bibliometric analysis of moisture content sensing technologies applied to grain storage, covering research published between 2015 and 2024. A two-step methodological approach was adopted. First, a bibliometric analysis of 97 publications retrieved from the Scopus database was conducted to identify publication trends, research focus areas, and technological development patterns. Second, a systematic review following PRISMA guidelines was performed, resulting in the selection of 29 studies that specifically addressed sensor-based moisture measurement in grain storage. The selected studies were analyzed with respect to grain type, sensing principles, sensor configurations, and data processing approaches. The results reveal a clear transition from conventional single-parameter moisture sensing toward integrated monitoring systems that combine indirect sensing techniques, wireless communication, and data-driven models. Capacitive and equilibrium relative humidity (ERH) sensors remain the most commonly used approaches due to their simplicity and low cost; however, their sensitivity to environmental variability and calibration drift limits their reliability when used alone. Recent studies increasingly employ multisensor frameworks that integrate temperature, relative humidity, and carbon dioxide measurements, with CO2 emerging as a robust indicator of grain respiration and early quality deterioration. Machine learning models, particularly artificial neural networks and random forest algorithms, demonstrate strong performance in predicting moisture content and overall grain quality from multisensor data. Despite these advances, challenges related to sensor accuracy, long-term stability, calibration, and cost continue to hinder large-scale adoption, especially in developing regions. This review highlights the need for intelligent, low-cost multisensor systems to enable reliable, real-time grain storage monitoring and improved post-harvest management.

Keywords
Grain Storage
Indirect Sensors
Intelligent multisensor
Moisture Sensor
Real-time monitoring
References
1

Albuquerque, J.R.P., Makara, C.N., Ferreira, V.G., Brazaca, L.C., Carrilho, E. 2024. Low-cost precision agriculture for sustainable farming using paper-based analytical devices. RSC Advances 14(32): 23392-23403. https://doi.org/10.1039/D4RA02310B

10.1039/D4RA02310B
2

Alencar, E.R., Faroni, L.R.D. 2011. Storage of soybeans and its effects on quality of soybean sub-products. In: Recent Trends for Enhancing the Diversity and Quality of Soybean Products edited by Krezhova D. pp. 47-66. InTech. https://doi.org/10.5772/18022

10.5772/18022
3

Al-Rawi, M.A.M. 2024. Low-cost soil moisture sensors’ assessment for their accuracy after calibration through the gravimetric method. SABRAO Journal of Breeding and Genetics 56(1): 353-369. https://doi.org/10.54910/sabrao2024.56.1.32

10.54910/sabrao2024.56.1.32
4

Aswani, G., Islam, T. 2023. Capacitive fringing sensor based on PCB for the detection of moisture content in grain. 2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) pp. 1-5. https://doi.org/10.1109/PIECON56912.2023.10085773

10.1109/PIECON56912.2023.10085773
5

Aswani, G., Maurya, O. P., Mahboob, R., Khan, A. U., Islam, T. 2024. Design and fabrication of nondestructive capacitive sensors for the moisture measurement in chickpeas and mustard seeds. Sustainability 16(5): 1847. https://doi.org/10.3390/su16051847

10.3390/su16051847
6

Azmi, N., Kamarudin, L.M., Zakaria, A., Ndzi, D.L., Rahiman, M.H.F., Zakaria, S.M.M.S., Mohamed, L. 2021. RF-based moisture content determination in rice using machine learning techniques. Sensors 21(5): 1875. https://doi.org/10.3390/s21051875

10.3390/s2105187533800174PMC7962462
7

Batey, I. 2017. The diversity of uses for cereal grains. In: Cereal Grains (2nd), edited by Wrigley, C., Batey, I., Miskelly, D., pp. 41-53. Woodhead Publishing. https://doi.org/10.1016/B978-0-08-100719-8.00003-6

10.1016/B978-0-08-100719-8.00003-6
8

Berbert, P.A., Jesus Soares, K., Moura, E.E., Berbert-Molina, M.A., Oliveira, M.T.R., Martinazzo, A.P. 2019. Predicting sorghum moisture content with radiofrequency dielectric functions,” Engineering in Agriculture, Environment and Food 12(2): 222-231. https://doi.org/10.1016/j.eaef.2019.01.003

10.1016/j.eaef.2019.01.003
9

Bilhalva, N.S., Coradi, P.C., Biduski, B., Mallmann, C.A., Anschau, K.F., Müller, E.I. 2023. Early detection of quality alterations in corn grains stored in vertical prototype silos using real-time monitoring of carbon dioxide and equilibrium moisture content. Food and Bioproducts Processing 140: 242-258. https://doi.org/10.1016/j.fbp.2023.06.008

10.1016/j.fbp.2023.06.008
10

Chen, Z., Wu, W., Dou, J., Liu, Z., Chen, K., Xu, Y. 2021. Design and analysis of a radio-frequency moisture sensor for grain based on the difference method. Micromachines 12(6): 708. https://doi.org/10.3390/mi12060708

10.3390/mi1206070834208717PMC8234241
11

Coradi, P.C., Lutz, É., Bilhalva, N.S., Jaques, L.B.A., Leal, M.M., Teodoro, L.P.R. 2022. Prototype wireless sensor network and Internet of Things platform for real-time monitoring of intergranular equilibrium moisture content and predict the quality corn stored in silos bags. Expert Systems with Applications 208: 118242. https://doi.org/10.1016/j.eswa.2022.118242

10.1016/j.eswa.2022.118242
12

David, J., Mohamed, A., Goru, D., Liet, Z. 2024. Utilizing modern technology and sustainable methods for storing rice. In: E3S Web of Conferences, 447: 00061. EDP Sciences. https://doi.org/10.1051/e3sconf/202447700061

10.1051/e3sconf/202447700061
13

Dean, R.N., Craven, J.D., Guertal, E.A., Varnavas, K.A. 2019. A PCB sensor for status monitoring of stored food stocks. IEEE Sensors Letters 3(4): 6000604. https://doi.org/10.1109/LSENS.2019.2902837

10.1109/LSENS.2019.2902837
14

Ferreira Junior, W.N., Resende, O., Sousa, K.A., Costa, L.M., Quirino, J.R. 2024. Equilibrium moisture content: Use of intergranular relative air humidity sensors in silos. Revista Brasileira de Engenharia Agricola e Ambiental, 28(8): e280005. https://doi.org/10.1590/1807-1929/agriambi.v28n8e280005

10.1590/1807-1929/agriambi.v28n8e280005
15

Flor, O., Palacios, H., Suárez, F., Salazar, K., Reyes, L., González, M., Jiménez, K. 2022. New sensing technologies for grain moisture. Agriculture 12(3): 386. https://doi.org/10.3390/agriculture12030386

10.3390/agriculture12030386
16

Jimoh, K.A., Hashim, N., Shamsudin, R., Man, H.C., Jahari, M., Onwude, D.I. 2023. Recent advances in the drying process of grains. Food Engineering Reviews 15: 548-576. https://doi.org/10.1007/s12393-023-09333-7

10.1007/s12393-023-09333-7
17

Kaushik, R., Singhai, J. 2019. An approach for the development of a sensing System to monitor contamination in stored grain. 2019 6th International Conference on Signal Processing and Integrated Networks (SPIN). pp. 880-884. https://doi.org/10.1109/SPIN.2019.8711604

10.1109/SPIN.2019.8711604
18

Kibar, H. 2015. Influence of storage conditions on the quality properties of wheat varieties. Journal of Stored Product Research 62: 8-15. https://doi.org/10.1016/j.jspr.2015.03.001

10.1016/j.jspr.2015.03.001
19

Lima, R.E., Coradi, P.C., Rodrigues, D.M., Teodoro, P.E., Teodoro, L.P.R., Oliveira, D.P. 2024. Monitoring and predicting the quality of soybeans for different drying and storage technologies on a real scale using sensors and machine learning models. Journal of Stored Products Research 108: 102386. https://doi.org/10.1016/j.jspr.2024.102386

10.1016/j.jspr.2024.102386
20

Lin, L., He, Y. Xiao, Z., Zhao, K., Dong, T., Nie, P. 2019. Rapid-detection sensor for rice grain moisture based on NIR spectroscopy. Applied Sciences 9(8): 1654. https://doi.org/10.3390/app9081654

10.3390/app9081654
21

Liu, J., Qiu, S., Wei, Z. 2022. Real-time measurement of moisture content of paddy rice based on microstrip microwave sensor assisted by machine learning strategies. Chemosensors 10(10): 376. https://doi.org/10.3390/chemosensors10100376

10.3390/chemosensors10100376
22

Liu, L., Song, C., Zhu, K., Liu, P. 2024. A design method for an SVM-based humidity sensor for grain storage. Sensors 24(9): 2854. https://doi.org/10.3390/s24092854

10.3390/s2409285438732960PMC11086073
23

Lutz, É., Coradi, P.C. 2022. Applications of new technologies for monitoring and predicting grains quality stored: Sensors, internet of things, and artificial intelligence. Measurement 188: 110609. https://doi.org/10.1016/j.measurement.2021.110609

10.1016/j.measurement.2021.110609
24

Lutz, É., Coradi, P.C. 2023. Equilibrium moisture content and dioxide carbon monitoring in real-time to predict the quality of corn grain stored in silo bags using artificial neural networks. Food Anal Methods 16(6): 1079-1098. https://doi.org/10.1007/s12161-023-02497-2

10.1007/s12161-023-02497-2
25

Lutz, É., Coradi, P.C., Jaques, L.B.A., Oliveria Carneiro, L., Teodoro, L.P.R., Teodoro, P.E., Meneghetti, V.L., Souza, G.A.C. 2022. Real-time equilibrium moisture content monitoring to predict grain quality of corn stored in silo and raffia bags. Journal of Food Process Engineering 45(9): e14076. https://doi.org/10.1111/jfpe.14076

10.1111/jfpe.14076
26

Mabasso, B.A., Resende, O., Souza, D.G., Santos Rosa, E. Almeida, A.B., Bessa, J.F.V., Célia, J.A., Leite, J.M., Leite, L.F. 2024. Physical properties and quality of corn grains stored at different initial moisture contents under hermetic and non-hermetic conditions. Journal of Stored Products Research 109: 102463. https://doi.org/10.1016/j.jspr.2024.102463

10.1016/j.jspr.2024.102463
27

Maramba, R.G., Caya, M.V.C., Hernandez, A.J.G., Ombay, G.P., Ching, M.J.T. 2019. Paddy rice moisture tester with Bluetooth data transfer. 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) pp.1-6. https://doi.org/10.1109/HNICEM48295.2019.9072784

10.1109/HNICEM48295.2019.9072784
28

Mun, H.K., You, K.Y., Dimon, M.N. 2015. Rice grain moisture determination using microstrip wide-ring and microstrip coupled-line sensors. American Journal of Applied Sciences 12(2): 112-120. https://doi.org/10.3844/ajassp.2015.112.120

10.3844/ajassp.2015.112.120
29

Ramli, N.A.M., Rahiman, M.H.F., Rahim, R.A., Kamarudin, L.M., Mohamed, L., Zakaria, A., Abdullah, M.S.M. 2024. Measurement of rice moisture content based on quantitative analysis from radio tomography images, Journal Teknologi 86(3): 63-78. https://doi.org/10.11113/jurnalteknologi.v86.21081

10.11113/jurnalteknologi.v86.21081
30

Reddy, N.G.K.K., Anand, K., Priyadharshini, R., Rajeshwari, K. 2016. Estimation of durability of rice grains using sensors and mobile technology. 2016 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR). pp. 33-35. https://doi.org/10.1109/TIAR.2016.7801209

10.1109/TIAR.2016.7801209
31

Rodrigues, D.M., Coradi, P.C., Teodoro, L.P.R., Teodoro, P.E., Moraes, R.S., Leal, M.M. 2024. Monitoring and predicting corn grain quality on the transport and post-harvest operations in storage units using sensors and machine learning models. Scientific Reports 14: 6232. https://doi.org/10.1038/s41598-024-56879-5

10.1038/s41598-024-56879-538486079PMC10940695
32

Serna Saldivar, S.O. 2016. Cereals: Types and composition. In: Encyclopedia of Food and Health, edited by Caballero, B., Finglas, P.M., Toldrá, F. pp. 718-723. Elsevier Ltd. https://doi.org/10.1016/B978-0-12-384947-2.00128-8

10.1016/B978-0-12-384947-2.00128-8
33

Shao, A., Chu, J. 2021. Design and research of an ultrasonic grain moisture content detection device. In: 2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) pp. 692-696. https://doi.org/10.1109/IMCEC51613.2021.9482332

10.1109/IMCEC51613.2021.9482332
34

Shen, E., Yang, W., Wang, X., Mao, S., Bin, W. 2022. TagSense: Robust wheat moisture and temperature sensing using a passive RFID tag. ICC 2022 - IEEE International Conference on Communications, pp. 1617-1622. https://doi.org/10.1109/ICC45855.2022.9838925

10.1109/ICC45855.2022.9838925
35

Singh, C.B., Fielke, J.M. 2017. Recent developments in stored grain sensors, monitoring and management technology. IEEE Instrumentation & Measurement Magazine 20(3): 32-55. https://doi.org/10.1109/MIM.2017.7951690

10.1109/MIM.2017.7951690
36

Souza, D.G., Resende, O., Zuchi, J., Mabasso, G.A. 2024. CO2 levels, technical breakage and quality of maize grains stored under different conditions. Revista Brasileira de Engenharia Agrícola e Ambiental 28(8): e279894. https://doi.org/10.1590/1807-1929/agriambi.v28n8e279894

10.1590/1807-1929/agriambi.v28n8e279894
37

Wang, R., Liu, L., Guo, Y., He, X., Lu, Q. 2020. Effects of deterioration and mildewing on the quality of wheat seeds with different moisture contents during storage. RSC Advances 10(25): 14581-14594. https://doi.org/10.1039/D0RA00542H

10.1039/D0RA00542H
38

Wang, X., Chen, Y., Jiang, J., Zheng, G., Zhang, R., Li, S., Lv, W., Song, Y., Wang, L., Li, W. 2024. Design and simulation of capacitive sensor for grain moisture detection. Journal of Physics: Conference Series 2740: 012018. https://doi.org/10.1088/1742-6596/2740/1/012018

10.1088/1742-6596/2740/1/012018
39

Wrigley, C.W. Taylor, J.R.N. 2023. Origin, evolution, production, and utilization of cereals. In: ICC Handbook of 21st Centry Cereal Science and Technology, edited by Shewry, P.R., Koksel, H., Taylor J.R.N. pp. 1-15. Academic Press. https://doi.org/10.1016/B978-0-323-95295-8.00016-2

10.1016/B978-0-323-95295-8.00016-2
40

Yadav, S.V., Chittora, A. 2023. Design and implementation of a surface wave transmission line microwave sensor for measuring grain moisture content. 2023 IEEE Wireless Antenna and Microwave Symposium (WAMS) pp. 1-4. https://doi.org/10.1109/WAMS57261.2023.10242983

10.1109/WAMS57261.2023.10242983
41

Yigit, E., Sabanci, K., Toktas, A., Ustun, D., Duysak, H. 2018. Grain moisture detection by using A-scan radar measurement. In: 2018 XXIIIrd International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED) pp. 222-224. Tbilisi, Georgia. https://doi.org/10.1109/DIPED.2018.8543311

10.1109/DIPED.2018.8543311
42

Yu, L., Zhang, M., Yang, D., Loescher, L., Soleimani, M. 2024. Grain moisture sensing using electrical capacitance tomography. IEEE Sensors Journal 24(2): 2038-2048. https://doi.org/10.1109/JSEN.2023.3335366

10.1109/JSEN.2023.3335366
43

Zhao, L., Wang, J., Li, Z., Hou, M., Dong, G., Liu, T. 2020. Quasi-distributed fiber optic temperature and humidity sensor system for monitoring of grain storage in granaries. IEEE Sensors Journal 20(16): 9226-9233. https://doi.org/10.1109/JSEN.2020.2989163

10.1109/JSEN.2020.2989163
Information
  • Publisher :Korean Society of Precision Agriculture
  • Publisher(Ko) :한국정밀농업학회
  • Journal Title :Precision Agriculture Science and Technology
  • Journal Title(Ko) :정밀농업과학기술
  • Volume : 7
  • No :4
  • Pages :421-435
  • Received Date : 2025-12-18
  • Revised Date : 2025-12-26
  • Accepted Date : 2025-12-29
  • DOI :https://doi.org/10.22765/pastj.20250028
Journal Informaiton Precision Agriculture Science and Technology Precision Agriculture Science and Technology
Online Submission & Review System
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close