# Noninvasive Sensing of Foliar Moisture in Hydroponic Crops Using Leaf-Based Electric Field Energy Harvesters

## TL;DR

This paper introduces a self-powered sensor using electric fields to monitor leaf moisture in hydroponic crops without harming the plants.

## Contribution

A noninvasive electric field energy harvester is developed to estimate plant traits from electrical responses in hydroponic crops.

## Key findings

- EFEHs generate AC voltage based on leaf dielectric properties through electrostatic induction.
- Regression models achieved R2=0.697 and R2=0.794 for predicting foliar moisture in chard and lettuce.
- Plant functional traits strongly influence EFEH electrical output, enabling physiological monitoring.

## Abstract

Large-scale wireless sensor networks with electric field energy harvesters (EFEHs) offer self-powered, eco-friendly, and scalable crop monitoring in hydroponic greenhouses. However, their practical adoption is limited by the low power density of current EFEHs, which restricts the reliable operation of external sensors. To address this challenge, this work presents a noninvasive EFEH assembled with hydroponic leafy vegetables that harvests electric field energy and estimates plant functional traits directly from the electrical response. The device operates through electrostatic induction produced by an external alternating electric field, which induces surface charge redistribution on the leaf. These charges are conducted through an external load, generating an AC voltage whose amplitude depends on the dielectric properties of the leaf. A low-voltage prototype was designed, built, and evaluated under controlled electric field conditions. Two representative species, Beta vulgaris (chard) and Lactuca sativa (lettuce), were electrically characterized by measuring the open-circuit voltage (VOC) and short-circuit current (ISC) of EFEHs. Three regression models were developed to determine the relationship between foliar moisture content (FMC) and fresh mass with electrical parameters. Empirical results disclose that the plant functional traits are critical predictors of the electrical output of EFEHs, achieving coefficients of determination of R2=0.697 and R2=0.794 for each species, respectively. These findings demonstrate that EFEHs can serve as self-powered, noninvasive indicators of plant physiological state in living leafy vegetable crops.