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Field evaluation and performance of capacitance probes for automated drip irrigation of watermelons

Author

Listed:
  • Miller, G.A.
  • Farahani, H.J.
  • Hassell, R.L.
  • Khalilian, A.
  • Adelberg, J.W.
  • Wells, C.E.

Abstract

Continuous, real-time monitoring of soil-moisture is essential to effective and efficient water management in an automated drip irrigation system. The primary objectives of this 3-year (2008–2010) field study were to demonstrate the utility of multi-sensor capacitance probes (MCP) to automate high frequency drip irrigation in watermelons [Citrullus lanatus (Thumb.) Matsum. & Nak.] production and to determine irrigation set points as percent soil water content depletion. Irrigation water treatments of 15% available water depletion (AWD), 50% AWD and No water application (fertigation only) were tested in sandy Coastal Plain soils in South Carolina. Multi-sensor capacitance probes (MCPs) monitored soil water status in the top 50cm profile and automatically triggered short (30–60min) duration irrigation water cycles whenever the average 0–30cm profile soil water content reached the irrigation set points. During peak crop water use and on hot days, four to seven irrigation events per day were necessary to meet crop water needs and minimize leaching in the sandy fields. The tactical irrigation scheduling capability offered via MCPs in an automated mode was highly advantageous. The short but frequent irrigation water cycles reduced water movement below the root zone (0–30cm). The 15% AWD irrigation water treatment showed a significant yield increase of 44% and 18.4% during 2008 and 45% and 40% during 2010 compared to No Water Application and 50% AWD irrigation water treatments respectively. The MCP factory calibration was as good as on-site calibration and was sufficiently accurate for irrigation scheduling.

Suggested Citation

  • Miller, G.A. & Farahani, H.J. & Hassell, R.L. & Khalilian, A. & Adelberg, J.W. & Wells, C.E., 2014. "Field evaluation and performance of capacitance probes for automated drip irrigation of watermelons," Agricultural Water Management, Elsevier, vol. 131(C), pages 124-134.
    • Handle: RePEc:eee:agiwat:v:131:y:2014:i:c:p:124-134
    DOI: 10.1016/j.agwat.2013.09.012
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    Citations

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    Cited by:

    1. Xiaoping Chen & Shaoyuan Feng & Zhiming Qi & Matthew W. Sima & Fanjiang Zeng & Lanhai Li & Haomiao Cheng & Hao Wu, 2022. "Optimizing Irrigation Strategies to Improve Water Use Efficiency of Cotton in Northwest China Using RZWQM2," Agriculture, MDPI, vol. 12(3), pages 1-15, March.
    2. Soulis, Konstantinos X. & Elmaloglou, Stamatios & Dercas, Nicholas, 2015. "Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems," Agricultural Water Management, Elsevier, vol. 148(C), pages 258-268.
    3. Zhang, Zhe & Liu, Shengyao & Jia, Songnan & Du, Fenghuan & Qi, Hao & Li, Jiaxi & Song, Xinyue & Zhao, Nan & Nie, Lanchun & Fan, Fengcui, 2021. "Precise soil water control using a negative pressure irrigation system to improve the water productivity of greenhouse watermelon," Agricultural Water Management, Elsevier, vol. 258(C).
    4. Bao, Lei & Zhang, Saifeng & Liang, Xinyu & Wang, Peizhou & Guo, Yawen & Sun, Qinghao & Zhou, Jianbin & Chen, Zhujun, 2023. "Intelligent drip fertigation increases water and nutrient use efficiency of watermelon in greenhouse without compromising the yield," Agricultural Water Management, Elsevier, vol. 282(C).
    5. Kargas, George & Soulis, Konstantinos X., 2019. "Performance evaluation of a recently developed soil water content, dielectric permittivity, and bulk electrical conductivity electromagnetic sensor," Agricultural Water Management, Elsevier, vol. 213(C), pages 568-579.

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