A Novel Non-Invasive Method for Real-Time Monitoring of Plant Water Status Based on Xylem Electrical Conductivity

Non-invasive, real-time monitoring of plant water status is critical for precision agriculture and plant physiology. However, existing methods often lack continuous in situ measurement capability or are limited by temporal resolution. This paper proposes a novel non-invasive method based on xylem electrical conductivity, inspired by industrial non-contact fluid measurement. As a ground-based complement to remote sensing, this approach demonstrates the feasibility of online, in situ, and non-invasive monitoring of water stress in grapevine stems under controlled laboratory conditions. The industrial C4D sensing system is adaptively modified into a specialized Plant-C4D sensor with an array-based design for batch signal acquisition. To validate the electrical response to water loss, a gravimetric natural dehydration experiment was conducted, demonstrating a clear correlation between electrical signals and water content changes in detached stem samples. Full-day dynamic experiments are conducted under three conditions: normal water supply, varying water stress, and plant inactivation. Sensitive characteristic parameters are extracted through signal analysis, and a pattern recognition framework is established to eliminate environmental interference and suppress individual differences. Experimental results on 24 plant samples (Shine Muscat) show that the method accurately discriminates viable from inactivated plants with an accuracy of 91.67% (22/24 correct). Furthermore, the Fuzzy C-Means (FCM) clustering algorithm successfully quantifies the severity of water stress in viable plants, yielding results consistent with actual water supply conditions. While these findings demonstrate the capability of Plant-C4D sensor to capture stem water status-related information, the current results do not establish full physiological validation, warranting further exploration with in vivo experiments.

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Publication Details

Journal
Agronomy
Published
2026-07-27
DOI
https://doi.org/10.3390/agronomy16151427
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
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article

A Novel Non-Invasive Method for Real-Time Monitoring of Plant Water Status Based on Xylem Electrical Conductivity

Jiahui Huang, Xuzhuang Yao, Junchao Huang, Junjie Gu
Agronomy
Plant Water Relations and Carbon Dynamics
article

A Novel Non-Invasive Method for Real-Time Monitoring of Plant Water Status Based on Xylem Electrical Conductivity

Jiahui Huang, Xuzhuang Yao, Junchao Huang, Junjie Gu
article en

Abstract

Non-invasive, real-time monitoring of plant water status is critical for precision agriculture and plant physiology. However, existing methods often lack continuous in situ measurement capability or are limited by temporal resolution. This paper proposes a novel non-invasive method based on xylem electrical conductivity, inspired by industrial non-contact fluid measurement. As a ground-based complement to remote sensing, this approach demonstrates the feasibility of online, in situ, and non-invasive monitoring of water stress in grapevine stems under controlled laboratory conditions. The industrial C4D sensing system is adaptively modified into a specialized Plant-C4D sensor with an array-based design for batch signal acquisition. To validate the electrical response to water loss, a gravimetric natural dehydration experiment was conducted, demonstrating a clear correlation between electrical signals and water content changes in detached stem samples. Full-day dynamic experiments are conducted under three conditions: normal water supply, varying water stress, and plant inactivation. Sensitive characteristic parameters are extracted through signal analysis, and a pattern recognition framework is established to eliminate environmental interference and suppress individual differences. Experimental results on 24 plant samples (Shine Muscat) show that the method accurately discriminates viable from inactivated plants with an accuracy of 91.67% (22/24 correct). Furthermore, the Fuzzy C-Means (FCM) clustering algorithm successfully quantifies the severity of water stress in viable plants, yielding results consistent with actual water supply conditions. While these findings demonstrate the capability of Plant-C4D sensor to capture stem water status-related information, the current results do not establish full physiological validation, warranting further exploration with in vivo experiments.

AgronomyVol. 16(15)
Zhejiang A & F University (CN)
Clean water and sanitation
Openalex Percentile: Top 11%
Plant Water Relations and Carbon Dynamics
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A Novel Non-Invasive Method for Real-Time Monitoring of Plant Water Status Based on Xylem Electrical Conductivity — Jiahui Huang, Xuzhuang Yao, et al. · Agronomy (2026) | TGRS Research Map | TGRS