• Abstract

    In the era of advanced agriculture, implementing Internet of Things (IoT) technology has brought significant innovations to monitoring plant growth. This article discusses the development of an automation system to monitor soil moisture and temperature in lettuce farming based on smart agriculture. The system integrates soil moisture and temperature sensors connected in real-time through IoT, enabling accurate and continuous monitoring of the environmental conditions for lettuce cultivation. The soil moisture sensor used is YL-69 with the calibration equation y=-0.0612x+64.38 and an R-square value of 0.8953. The average standard deviation value is 0.36, and the average accuracy value is 98.71%. The temperature sensor used is DHT11 with the calibration equation y=0.9619x+2.8107 and an R-square value of 0.9928. The average standard deviation value is 0.023, and the average accuracy is 99.67%. The microcontroller used is ESP8266, known for its reliable connectivity. The IoT platform employed is the Blynk application. Monitoring results over five days yielded average soil moisture values ranging from 76% to 98%, and average temperature values ranged from 22°C to 27°C. Through continuous data collection, farmers can optimize irrigation, apply corrective measures for temperature fluctuations, and design more innovative farming strategies. The results of implementing this system demonstrate a significant improvement in resource efficiency, operational cost savings, and increased productivity in lettuce farming management.

  • References

    1. Al-Agele, H. A., Mahapatra, D. M., Nackley, L., & Higgins, C. (2022). Economic Viability of Ultrasonic Sensor Actuated Nozzle Height Control in Center Pivot Irrigation Systems. Agronomy, 12(5). https://doi.org/10.3390/agronomy12051077
    2. Alves, C. M. L., Chang, H. Y., Tong, C. B. S., Rohwer, C. L., Avalos, L., & Vickers, Z. M. (2022). Artificial Shading Can Adversely Affect Heat-tolerant Lettuce Growth and Taste, with Concomitant Changes in Gene Expression. Journal of the American Society for Horticultural Science, 147(1), 45–52. https://doi.org/10.21273/JASHS05124-21
    3. Ardiansah, I., Bafdal, N., Suryadi, E., & Bono, A. (2020). Greenhouse Monitoring and Automation Using Arduino: a Review on Precision Farming and Internet of Things (IoT). InternationalJournalon Advanced Science Engineering Information Technology, 10(2).
    4. Baz, H., Creech, M., Chen, J., Gong, H., Bradford, K., & Huo, H. (2020). Water-soluble carbon nanoparticles improve seed germination and post-germination growth of lettuce under salinity stress. Agronomy, 10(8). https://doi.org/10.3390/agronomy10081192
    5. Bekier, J., Jamroz, E., Sowiński, J., Adamczewska-Sowińska, K., & Kałuża-Haładyn, A. (2022). Effect of Differently Matured Composts from Willow on Growth and Development of Lettuce. Agronomy, 12(1). https://doi.org/10.3390/agronomy12010175
    6. Bella, E. La, Baglieri, A., Rovetto, E. I., Stevanato, P., & Puglisi, I. (2021). Foliar spray application of chlorella vulgaris extract: Effect on the growth of lettuce seedlings. Agronomy, 11(2). https://doi.org/10.3390/agronomy11020308
    7. Bodunde, O. P., Adie, U. C., Ikumapayi, O. M., Akinyoola, J. O., & Aderoba, A. A. (2019). Architectural design and performance evaluation of a ZigBee technology based adaptive sprinkler irrigation robot. Computers and Electronics in Agriculture, 160, 168–178. https://doi.org/10.1016/j.compag.2019.03.021
    8. Chaganti, R., Varadarajan, V., Gorantla, V. S., Gadekallu, T. R., & Ravi, V. (2022). Blockchain-Based Cloud-Enabled Security Monitoring Using Internet of Things in Smart Agriculture. Future Internet, 14(9). https://doi.org/10.3390/fi14090250
    9. Chen, C. J., Huang, Y. Y., Li, Y. S., Chang, C. Y., & Huang, Y. M. (2020). An AIoT Based Smart Agricultural System for Pests Detection. IEEE Access, 8, 180750–180761. https://doi.org/10.1109/ACCESS.2020.3024891
    10. Choi, K., Paek, K., & Lee, Y. (2000). Effect of air temperature on tipburn incidence of butterhead and leaf lettuce in a plant factory., 166-171. https://doi.org/10.1007/978-94-015-9371-7_27
    11. Di Mola, I., Cozzolino, E., Ottaiano, L., Nocerino, S., Rouphael, Y., Colla, G., El-Nakhel, C., & Mori, M. (2020). Nitrogen use and uptake efficiency and crop performance of baby spinach (Spinacia oleracea L.) and Lamb’s Lettuce (Valerianella locusta L.) grown under variable sub-optimal N regimes combined with plant-based biostimulant application. Agronomy, 10(2). https://doi.org/10.3390/agronomy10020278
    12. Feng, T., Xiao, Y., & Bo, L. (2020). CALIBRATION of CYCLIC FORCE with INERTIAL FORCE CORRECTION to A FATIGUE TESTING MACHINE. Acta IMEKO, 9(5), 124–128. https://doi.org/10.21014/ACTA_IMEKO.V9I5.953
    13. Felipe, A. and Bareng, J. (2022). Growth and yield assessment of lettuce (lactuca sativa l.): an economic feasibility and performance evaluation of capillary wick irrigation system. Plant Science Today, 9(1), 62-69. https://doi.org/10.14719/pst.1460
    14. Fernández-Ahumada, L. M., Ramírez-Faz, J., Torres-Romero, M., & López-Luque, R. (2019). Proposal for the design of monitoring and operating irrigation networks based on IoT, cloud computing and free hardware technologies. Sensors (Switzerland), 19(10). https://doi.org/10.3390/s19102318
    15. Ferrag, M. A., Shu, L., Djallel, H., & Choo, K. K. R. (2021). Deep learning-based intrusion detection for distributed denial of service attack in agriculture 4.0. Electronics (Switzerland), 10(11). https://doi.org/10.3390/electronics10111257
    16. Gaikwad, S. V., Vibhute, A. D., Kale, K. V., & Mehrotra, S. C. (2021). An innovative IoT based system for precision farming. Computers and Electronics in Agriculture, 187. https://doi.org/10.1016/j.compag.2021.106291
    17. Giménez, A., Fernández, J. A., Pascual, J. A., Ros, M., & Egea-Gilabert, C. (2020). Application of directly brewed compost extract improves yield and quality in baby leaf lettuce grown hydroponically. Agronomy, 10(3). https://doi.org/10.3390/agronomy10030370
    18. Hasan, M. K., Aziz, M. H., Zarif, M. I. I., Hasan, M., Hashem, M. M. A., Guha, S., Love, R. R., & Ahamed, S. (2021). Noninvasive hemoglobin level prediction in a mobile phone environment: State of the art review and recommendations. JMIR MHealth and UHealth, 9(4). https://doi.org/10.2196/16806
    19. Irawan, Y., Wahyuni, R., Muhardi, M., Fonda, H., Hamzah, M. L., & Muzawi, R. (2021). Real Time System Monitoring and Analysis-Based Internet of Things (IoT) Technology in Measuring Outdoor Air Quality. International Journal of Interactive Mobile Technologies, 15(10), 224–240. https://doi.org/10.3991/ijim.v15i10.20707
    20. Jeon, K. J., Kim, S.-J., Park, K. K., Kim, J.-W., & Yoon, G. (2002). Noninvasive total hemoglobin measurement. Journal of Biomedical Optics, 7(1), 45. https://doi.org/10.1117/1.1427047
    21. Karar, M. E., Alsunaydi, F., Albusaymi, S., & Alotaibi, S. (2021). A new mobile application of agricultural pests recognition using deep learning in cloud computing system. Alexandria Engineering Journal, 60(5), 4423–4432. https://doi.org/10.1016/j.aej.2021.03.009
    22. Katiyar, S., & Farhana, A. (2021). Smart Agriculture: The Future of Agriculture using AI and IoT. Journal of Computer Science, 17(10), 984–999. https://doi.org/10.3844/jcssp.2021.984.999
    23. Kumar, A., Kumar, A., De, A., Shekhar, S., & Singh, R. K. (2019). IoT based farming recommendation system using soil nutrient and environmental condition detection. International Journal of Innovative Technology and Exploring Engineering, 8(11), 3055–3060. https://doi.org/10.35940/ijitee.K2335.0981119
    24. Lakshmeesha, T. R., Murali, M., Ansari, M. A., Udayashankar, A. C., Alzohairy, M. A., Almatroudi, A., Alomary, M. N., Asiri, S. M. M., Ashwini, B. S., Kalagatur, N. K., Nayak, C. S., & Niranjana, S. R. (2020). Biofabrication of zinc oxide nanoparticles from Melia azedarach and its potential in controlling soybean seed-borne phytopathogenic fungi. Saudi Journal of Biological Sciences, 27(8), 1923–1930. https://doi.org/10.1016/j.sjbs.2020.06.013
    25. Lee, A., Liao, F., & Lo, H. (2015). Temperature, daylength, and cultivar interact to affect the growth and yield of lettuce grown in high tunnels in subtropical regions. Hortscience, 50(10), 1412-1418. https://doi.org/10.21273/hortsci.50.10.1412
    26. Le Page, M., Jarlan, L., El Hajj, M. M., Zribi, M., Baghdadi, N., & Boone, A. (2020). Potential for the detection of irrigation events on maize plots using Sentinel-1 soil moisture products. Remote Sensing, 12(10). https://doi.org/10.3390/rs12101621
    27. Liu, X., Wang, T., & Chen, J. (2022). Identifiability Analysis for Configuration Calibration in Distributed Sensor Networks. Remote Sensing, 14(16). https://doi.org/10.3390/rs14163920
    28. Malik, N. N., Alosaimi, W., Irfan Uddin, M., Alouffi, B., & Alyami, H. (2020). Wireless sensor network applications in healthcare and precision agriculture. Journal of Healthcare Engineering, 2020. https://doi.org/10.1155/2020/8836613
    29. Meng, Q., Boldt, J., & Runkle, E. S. (2020). Blue radiation interacts with green radiation to influence growth and predominantly controls quality attributes of lettuce. Journal of the American Society for Horticultural Science, 145(2), 75–87. https://doi.org/10.21273/JASHS04759-19
    30. Michelon, N., Pennisi, G., Myint, N. O., Dall’Olio, G., Batista, L. P., Salviano, A. A. C., Gruda, N. S., Orsini, F., & Gianquinto, G. (2020). Strategies for improved yield and water use efficiency of lettuce (Lactuca sativa L.) through simplified soilless cultivation under semi-arid climate. Agronomy, 10(9). https://doi.org/10.3390/agronomy10091379
    31. Montoya, A. P., Obando, F. A., Osorio, J. A., Morales, J. G., & Kacira, M. (2020). Design and implementation of a low-cost sensor network to monitor environmental and agronomic variables in a plant factory. Computers and Electronics in Agriculture, 178. https://doi.org/10.1016/j.compag.2020.105758
    32. Muthmainnah, Arabani, F. Z., Tazi, I., Chamidah, N., Sasmitaninghidayah, W., & Tirono, M. (2023). Development of Optical Sensor Technology for Non-Invasive Hemoglobin Measurement. Jurnal Penelitian Pendidikan IPA, 9(11), 10252–10258. https://doi.org/10.29303/jppipa.v9i11.5610
    33. Omar, N. B., Zen, H. Bin, Aldrin, N. N. A., Waluyo, & Hadiatna, F. (2020). Accuracy and Reliability of Data in IoT System for Smart Agriculture. International Journal of Integrated Engineering, 12(6), 105–116. https://doi.org/10.30880/IJIE.2020.12.06.013
    34. Perkasa, R., Wahyuni, R., Melyanti, R., Herianto, & Irawan, Y. (2021). Light control using human body temperature based on arduino uno and PIR (Passive Infrared Receiver) sensor. Journal of Robotics and Control (JRC), 2(4), 307–310. https://doi.org/10.18196/jrc.2497
    35. Pinto, M. A. B., Parfitt, J. M. B., Timm, L. C., Faria, L. C., Concenço, G., Stumpf, L., & Nörenberg, B. G. (2020). Sprinkler irrigation in lowland rice: Crop yield and its components as a function of water availability in different phenological phases. Field Crops Research, 248. https://doi.org/10.1016/j.fcr.2020.107714
    36. Priyanka, R., & Reji, M. (2019). IOT based health monitoring system using blynk app. International Journal of Engineering and Advanced Technology, 8(6), 78–81. https://doi.org/10.35940/ijeat.E7467.088619
    37. Qiu, M., & Ostfeld, A. (2021). A head formulation for the steady-state analysis of water distribution systems using an explicit and exact expression of the colebrook–white equation. Water (Switzerland), 13(9). https://doi.org/10.3390/w13091163
    38. Ramirez, J., Manuel, L., & Fernandez, E. (2020). Monitoring of Temperature in Retail Refrigerated and Software. Sensors, 20(864), 2–18.
    39. Ruslan, A. A., Salleh, S. M., Fatmadiana, S., Hatta, W. M., Abu, A., & Sajak, B. (n.d.). IoT Soil Monitoring based on LoRa Module for Oil Palm Plantation. In IJACSA) International Journal of Advanced Computer Science and Applications (Vol. 12, Issue 5). www.ijacsa.thesai.org
    40. Saad, A., Benyamina, A. E. H., & Gamatie, A. (2020). Water Management in Agriculture: A Survey on Current Challenges and Technological Solutions. IEEE Access, 8, 38082–38097. https://doi.org/10.1109/ACCESS.2020.2974977
    41. Saikat, M., Khan, I., Rahman, A., Islam, S., Kamal Nasir, M., Band, S. S., & Mosavi, A. (2021). IoT and Wireless Sensor Networking-based Effluent Treatment Plant Monitoring System. In Acta Polytechnica Hungarica, 18(10).
    42. Schröder, C., Häfner, F., Larsen, O. C., & Krause, A. (2021). Urban organic waste for urban farming: Growing lettuce using vermicompost and thermophilic compost. Agronomy, 11(6). https://doi.org/10.3390/agronomy11061175
    43. Serikul, P., Nakpong, N., & Nakjuatong, N. (2018). Smart Farm Monitoring via the Blynk IoT Platform. 2018 Sixteenth International Conference on ICT and Knowledge Engineering, 70–75.
    44. Shin, Y. K., Bhandari, S. R., Jo, J. S., Song, J. W., Cho, M. C., Yang, E. Y., & Lee, J. G. (2020). Response to salt stress in lettuce: Changes in chlorophyll fluorescence parameters, phytochemical contents, and antioxidant activities. Agronomy, 10(11). https://doi.org/10.3390/agronomy10111627
    45. Smoleń, S., Kowalska, I., Halka, M., Ledwozyw-Smoleń, I., Grzanka, M., Skoczylas, Ł., Czernicka, M., & Pitala, J. (2020). SelectedAspects of iodate and iodosalicylate metabolism in lettuce including the activity of vanadium dependent haloperoxidases as affected by exogenous vanadium. Agronomy, 10(1). https://doi.org/10.3390/agronomy10010001
    46. Thorp, K. R., Thompson, A. L., & Bronson, K. F. (2020). Irrigation rate and timing effects on Arizona cotton yield, water productivity, and fiber quality. Agricultural Water Management, 234. https://doi.org/10.1016/j.agwat.2020.106146
    47. Tomaz, A., Palma, P., Fialho, S., Lima, A., Alvarenga, P., Potes, M., & Salgado, R. (2020). Spatial and temporal dynamics of irrigation water quality under drought conditions in a large reservoir in Southern Portugal. Environmental Monitoring and Assessment, 192(2). https://doi.org/10.1007/s10661-019-8048-1
    48. Tsige, M., Synnevåg, G., & Aune, J. B. (2020). Gendered constraints for adopting climate-smart agriculture amongst smallholder Ethiopian women farmers. Scientific African, 7. https://doi.org/10.1016/j.sciaf.2019.e00250
    49. Wakchaure, G. C., Minhas, P. S., Meena, K. K., Kumar, S., & Rane, J. (2020). Effect of plant growth regulators and deficit irrigation on canopy traits, yield, water productivity and fruit quality of eggplant (Solanum melongena L.) grown in the water scarce environment. Journal of Environmental Management, 262. https://doi.org/10.1016/j.jenvman.2020.110320
    50. Wayangkau, I. H., Mekiuw, Y., Rachmat, R., Suwarjono, S., & Hariyanto, H. (2020). Utilization of IoT for soil moisture and temperature monitoring system for onion growth. Emerging Science Journal, 4(Special Issue), 102–115. https://doi.org/10.28991/ESJ-2021-SP1-07
    51. Yu, L., Zhao, X., Gao, X., & Siddique, K. H. M. (2020). Improving/maintaining water-use efficiency and yield of wheat by deficit irrigation: A global meta-analysis. Agricultural Water Management, 228. https://doi.org/10.1016/j.agwat.2019.105906

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Muthmainnah, M., Mulyadi, M. F., Tazi, I., Mulyono, A., Hananto, F. S., Chamidah, N., & Kusairi. (2024). Development of an automated monitoring system for soil moisture and temperature in smart agriculture to enhance lettuce farming productivity based on IoT. Multidisciplinary Science Journal, 6(11), 2024233. https://doi.org/10.31893/multiscience.2024233
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