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Development of smart irrigation systems based on real-time soil moisture data in a greenhouse: Proof of concept

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  • Liao, Renkuan
  • Zhang, Shirui
  • Zhang, Xin
  • Wang, Mingfei
  • Wu, Huarui
  • Zhangzhong, Lili

Abstract

A reasonable estimation of crop water uptake depth (WUD) provides vital prerequisites for determining scientific irrigation scheduling. However, real-time acquisition of crop WUD to guide irrigation has not been reported. In the current study, a smart irrigation system based on real-time soil moisture data was developed, in which the dynamic crop WUD was estimated using the spatiotemporal characteristics of soil moisture distributions. Subsequently, the data of crop WUD were acquired using a central irrigation controller to achieve a precise irrigation depth at each irrigation event. A drip irrigation experiment for tomato (Lycopersicum esculentum) planting was conducted in a greenhouse in northern China. Wireless soil moisture sensors were installed to collect real-time soil moisture data from a 0–100 cm soil profile. Soil moisture exhibited a ladder trend for 0–60 cm and a stable trend for 60–100 cm. A regression equation (WUDi = −0.0119d2 + 1.9387d - 6.5795, R2 = 0.89) quantifying the dynamic depth of crop water uptake was successfully obtained based on the characteristics of soil moisture distribution, and a water-saving scheme (i.e., irrigation to real-time crop WUD) was determined to guide every irrigation event via a remote automatic irrigation system. Tomato evapotranspiration (ET) calculated using soil moisture data was consistent with that calculated using indoor meteorological data, confirming the reliability of real-time soil moisture data for estimating the tomato WUD. The tomato irrigation water use efficiency (IWUE) of the established system reached 41.23 kg/m3, which was an evident improvement compared with that obtained using a traditional irrigation scheme (31.58 kg/m3). In addition, the IWUE of tomato in the established system was almost approached that of the previously published results. The findings of this study highlight the importance of reasonable water-saving irrigation scheduling and provide insights into the development of an efficient and automatic irrigation system.

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  • Liao, Renkuan & Zhang, Shirui & Zhang, Xin & Wang, Mingfei & Wu, Huarui & Zhangzhong, Lili, 2021. "Development of smart irrigation systems based on real-time soil moisture data in a greenhouse: Proof of concept," Agricultural Water Management, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:agiwat:v:245:y:2021:i:c:s037837742032179x
    DOI: 10.1016/j.agwat.2020.106632
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    6. Wang, Qunyan & Jia, Yifan & Pang, Zhongjun & Zhou, Jianbin & Scriber, Kevin Emmanuel & Liang, Bin & Chen, Zhujun, 2024. "Intelligent fertigation improves tomato yield and quality and water and nutrient use efficiency in solar greenhouse production," Agricultural Water Management, Elsevier, vol. 298(C).
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