Preprint Article Version 1 This version is not peer-reviewed

Characterization and Water Content Estimation Method of Living Plant Leaves Using Terahertz Waves

Version 1 : Received: 4 July 2019 / Approved: 9 July 2019 / Online: 9 July 2019 (03:25:11 CEST)

How to cite: Zahid, A.; Abbas, H.T.; Imran, M.A.; Qaraqe, K.A.; Alomainy, A.; Cumming, D.R.S..; Abbasi, Q.H. Characterization and Water Content Estimation Method of Living Plant Leaves Using Terahertz Waves. Preprints 2019, 2019070125 (doi: 10.20944/preprints201907.0125.v1). Zahid, A.; Abbas, H.T.; Imran, M.A.; Qaraqe, K.A.; Alomainy, A.; Cumming, D.R.S..; Abbasi, Q.H. Characterization and Water Content Estimation Method of Living Plant Leaves Using Terahertz Waves. Preprints 2019, 2019070125 (doi: 10.20944/preprints201907.0125.v1).

Abstract

An increasing global aridification due to climate change has made the health monitoring of vegetation indispensable to maintaining the food supply chain. Cost-effective and smart irrigation systems are required not only to ensure the efficient distribution of water, but also to track the moisture of plant leaves, which is an important marker of the overall health of the plant. This paper presents a novel electromagnetic method to monitor the water content (WC) and characterization in plant leaves utilizing the absorption spectra of water molecules in the terahertz (THz) frequency for four consecutive days. We extracted the material properties of leaves of eight types of pot herbs from the scattering parameters, measured using a material characterization kit in the frequency range of 0.75 to 1.1 THz. From the computed permittivity, it is deduced that the leaf specimens increasingly become transparent to the THz waves as they dry out with the passage of days. Moreover, the loss in weight and thickness of leaves were observed due to the natural evaporation of leaf moisture cells and change occurred in the morphology of fresh and water-stressed leaves. It is also illustrated that loss observed in WC on day 1 was in the range of 5\% to 22\%, and increased from 83.12\% to 99.33\% on day 4. Furthermore, we observed an exponential decaying trend in the peaks of the real part of the permittivity from day 1 to 4, which was reminiscent of the trend observed in the weight of all leaves. Thus, results in paper demonstrated that timely detection of water stress in leaves can help to take proactive action in relation to plants health monitoring, and for precision agriculture applications, which is of high importance to improve the overall productivity.

Subject Areas

vegetation health monitoring; leaf water content; terahertz; sensing; plants health

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