Irrigatıon in Agriculture and Automation Based Irrigation Systems (Mini-Review)

Abstract

With the technological developments, modern agricultural applications and the effects of these applications in daily life are increasing day by day. Automation-based smart systems, which have replaced old-style fixed irrigation systems created for only a specific purpose, have brought along remote-controllable agricultural productions in line with agricultural product needs. Automation-based smart irrigation systems have brought significant gains to the agricultural sector. The most important of these gains are time, cost, and labor savings. This study tried to summarize the research on smart (automatic) irrigation systems in the last seven years and emphasize the necessity and advantages of automatic irrigation systems.

Keywords

• Irrıgatıon
• Agrıculture
• Smart system
• Automatıon
• Modern applications

Kaynakça

1. [1]. Aküzüm, T., Çakmak, B. ve Benli, B. 1999. Yirmibirinci Yüzyılda Dünyada Su Sorunu. 7.Kültürteknik Kongresi, s.8-16, Nevşehir.
2. [2]. Özgürel M., 2019. Adıyaman Bölgesi Modern Seracılık İşletmelerinin Isı Tüketimlerinin Hesaplanması Ve Isı Koruma Önlemlerinin Isı Tüketimine Etilerinin Araştırılması, Kahramanmaraş Sütçü İmam Üniversitesi, Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi.
3. [3]. De Pascale, S., Costa, L., Vallone, S., Barbieri, G. ve Maggio, A., 2011. Increasing water use efficiency in vegetable crop production: From plant to irrigation systems efficiency, Hortechnology, 21(3): 301-308.
4. [4]. Yavuz, D., Topak, R. ve Yavuz, N., 2014. Determining energy consumption of sprinkler irrigation for different crops in Konya Plain, Türk Tarım ve Doğa Bilimleri Dergisi 1(3): 312-321.
5. [5]. Cai, X. and Rosegrant, M. W. 2003. World Water Productivity: Current Situation and Future Options. Water productivity in agriculture: limits and opportunities for improvement, 1: 163
6. [6]. Kim, D. and Kaluarachchi, J. 2015. Validating FAO AquaCrop using Landsat images and regional crop information. Agricultural Water Management, 149: 143-155
7. [7]. Debaeke, P. and Aboudrare, A. 2004. Adaptation of crop management to water-limited environments. European Journal of Agronomy, 21(4): 433-446
8. [8]. Anonymous,2015. http://www.dsi.gov.tr/toprak-ve-su-kaynaklari

9. [9]. Sönmez, N., Benli, E. 1976. Lineer programming as a means in project Evalation and Aplplication to the Alpu irragation project. A.Ü. Ziraat Fakültesi yıllığı Cilt:25, Fasikül 4’ten ayrı basım. S. 942-950.
10. [10]. Smith, M. 2000. The application of climatic data for planning and management of sustainable rainfed and irrigated crop production. Agricultural and Forest Meteorology, 103(1-2): 99-108
11. [11]. Malik, A. Shakir, A. S. Ajmal, M. Khan, M .J. and Khan, T. A. 2017. Assessment of AquaCrop Model in Simulating Sugar Beet Canopy Cover, Biomass and Root Yield under Different Irrigation and Field Management Practices in Semi-Arid Regions of Pakistan Water Resources Management, 31(13): 4275-4292. doi:10.1007/s11269-017-1745-z
12. [12]. Emeksiz, F., Albayrak, M., Günes, E., Özçelik, A., Özer, O.O., Tasdan, K., 2005. Türkiye’de Tarımsal Üretimin Pazarlama Kanalları ve Araçlarının Degerlendirilmesi, Türkiye Ziraat Mühendisligi VI. Teknik Kongresi, 3-7 Ocak 2005, Ankara, 2.Cilt, s.1155-1171.
13. [13]. Kulkarni, S., 2011. Innovative technologies for water saving in irrigated agriculture, International Journal of Water Resources and Arid Environments, 1 (3): 226-231.
14. [14]. Kay, M., 1988. Sprinkler Irrigation Equipment and Practice.
15. [15]. Yavuz, D., 2006. Yağmurlama Sulamanın Enerji Gereksinimi. Master Tezi. Selçuk Üniversitesi, Fen Bilimleri Enstitüsü, Tarımsal Yapılar ve Sulama Anabilim Dalı, 49 s.
16. [16]. Arif I. ve Abbas, H. F., Design and Implementation a Smart Greenhouse, ISSN: 2320– 088X, https://ijcsmc.com/docs/papers/August2015/V4I8201560.pdf
17. [17]. Al-Ali, A.R., Qasaimeh, M., AI-Mardinia, M., Radder, S., Zualkernan, IA. 2015. ZigBee-Based Irrigation System for Home Gardens, Communications, Signal Processing, and their Applications (ICCSPA), 2015 International Conference on, American University of Sharjah, 1-5.
18. [18]. Ersin, C., Arduino mikrodenetleyici ve güneş enerjisiyle çalışan otomatik bitki sulama sistemi, http://tez.sdu.edu.tr/Tezler/TF02790.pdf
19. [19]. Kopdra, S. ve Martin, M., Implementation of Microcontroller Arduino in Irrigation System, DOI: http://dx.doi.org/10.1007/978-3-319-42291-6_13.
20. [20]. Mritunjay, O., Sheetal, M., Shraddha, K. ve Diksha, T., Microcontroller Based Automatic Plant Watering System, ISSN: 12278-9960. https://www.semanticscholar.org/paper/MICROCONTROLLER-BASED-AUTOMATIC-PLANT-WATERING-Ojha-Mohite/ac12bb74aad84864c31522be894d84a19e2e31f8
21. [21]. Kavianand G., Nivas V. M., Kiruthika R.,. Lalitha S. 2016.Smart drip irrigation system for sustainable agriculture. In 2016 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR), 19–22.
22. [22]. Patil A., Beldar M., Naik A., Deshpande S. 2016. Smart farming using arduino and data mining. In 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), 1913–1917
23. [23]. Karaca, C., Tekelioğlu, B., Büyüktaş, D., 2017. Sürdürülebilir Tarımsal Üretim için Toprak Nem Sensörlerinin Etkin Kullanımı, Acedemia Journal of Engineering and Applied Science, 2 (3), 33-41.
24. [24]. Suman, S., Kumar, S., Sarkar, R., Ghosh, G., 2017. Solar Powered Automatic Irrigation System on Sensing Moisture Content Using Arduino and GSM”, International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE), 6, 549-555.
25. [25]. Rehman, A.U., Asif, R. M., Tariq, R., Javed, A., 2017. Gsm Based Solar Automatıc Irrıgatıon System Usıng Moısture, Temperature And Humıdıty Sensors, International Conference on Engineering Technology and Technopreneurship (ICE2T), Pakistan, 1-4.
26. [26]. Kumar, B. D., Srivastava, P., Agrawal, R., Tiwari, V., 2017. Microcontroller based automatic plant irrigation system”, International Research Journal of Engineering and Technology (IRJET), 4 (5), 1436-1439.
27. [27]. Taneja, K., Bhatia, S., 2017. Automatic Irrigation System using Arduino UNO” International Conference on Intelligent Computing and Control Systems ICICCS 2017, Madurai-India.
28. [28]. Kızıl, Ü., Aksu, S., Çamoğlu, G., 2018. Kontrollü Ortamda Bitkisel Yetiştiricilik için Arduino Uyumlu Bir Toprak Nemi İzleme Sistemi Tasarımı, ÇOMÜ Zir. Fak. Derg., 6 (2), 131-139.
29. [29]. García, A. M., García, I. F., Poyato, E. C., Barrios, P. M., Díaz, J. A. R., 2018. Coupling irrigation scheduling with solar energy production in a smart irrigation management system, Cleaner Production, 175, 670-682.
30. [30]. Wazed, S. M., Hughes, B.R., O’Connor, D., Calautit, J.K., 2018. A review of sustainable solar irrigation systems for Sub-Saharan Africa”, Renewable and Sustainable Energy Reviews, 81, 1206-1225.
31. [31]. Yang, J., Liu, M., Lu, J., Miao, Y., Hossain, M. A., Alhamid, M. F., 2018. Botanical internet of things: toward smart indoor farming by connecting people, plant, data and clouds, Mobile Networks and Applications, 23(2), 188–202.
32. [32]. Aliev, K., Jawaid, M. M., Narejo, S., Pasero, E., Pulatov, A., 2018. Internet of plants application for smart agriculture. International Journal of Advanced Computer Science and Applications, 9(4), 421–429.
33. [33]. Subashini, M. M., Das, S., Heble, S., Raj, U., Karthik, R., 2018. Internet of things based wireless plant sensor for smart farming. Indonesian Journal of Electrical Engineering and Computer Science, 10(2), 456–468.
34. [34]. Goap, A., Sharma, D., Shukla, A. K., Rama Krishna, C., 2018. An IoT based smart irrigation management system using machine learning and open source technologies. Computers and Electronics in Agriculture, 155(October), 41–49.
35. [35]. Goap, A., Sharma, D., Shukla, A. K., Rama Krishna, C., 2018. Comparative study of regression models towards performance estimation in soil moisture prediction, 309-316, International Conference on Advances in Computing and Data Sciences, 20-21 April, Dehradun, India.
36. [36]. Sudharshan N., AVS Kasturi Karthik., JS Sandeep Kiran., S. Geetha., 2019. Renewable Energy Based Smart Irrigation System”, Procedia Computer Science, 165, 615–623.
37. [37]. Kang, S., van Iersel, M. W., Kim, J., 2019. Plant root growth affects FDR soil moisture sensor calibration”, Scientia Horticulturae, 252, 208-211.
38. [38]. Yılmaz, A., 2019. Fotovoltaik Sistem ve Damla Sulama Yöntemiyle Sulanan Fındıkta Sulama Uygulamalarının Verim ve Verim Bileşenlerine Etkisi”, Yüksek Lisans Tezi, Ordu Üniversitesi Fen Bilimleri Enstitüsü, Yenilenebilir Enerji Anabilim Dalı, Ordu.
39. [39]. Mekala, M. S., Viswanathan, P., 2019. CLAY-MIST: IoT-cloud enabled CMM index for smart agriculture monitoring system. Measurement: Journal of the International Measurement Confederation, 134, 236–244.
40. [40]. Keswani, B., Mohapatra, A. G., Mohanty, A., Khanna, A., Rodrigues, J. J. P. C., Gupta, D., de Albuquerque, V. H. C., 2019. Adapting weather conditions based on IoT enabled smart irrigation techniques in precision agriculture mechanisms. Neural Computing and Applications, 31, 277–292.
41. [41]. Domínguez-Niño, J. M., Oliver-Manera, J., Girona, J., Casadesús, J., 2020. Differential irrigation scheduling by an automated algorithm of water balance tuned by capacitance-type soil moisture sensors”, Agricultural Water Management, 228, 59-66.
42. [42]. H. Demirbaş, 2021. Güneş Enerjili Otomatik Bitki Sulama Sistemi, Yüksek Lisans Tezi, Pamukkale Üniversitesi Fen Bilimleri Enstitüsü Makina Mühendisligi˘ Anabilim Dalı, Mugla.