Nano-sensors for monitoring plant growth： working principles and examples of system integration in applications

YE Ting; LUO Zhen; XU Wenying; LI Jiaqi; ZHANG Youchang; WANG Xiaogang; SONG Zhiyong

doi:10.13300/j.cnki.hnlkxb.2026.03.002

您当前的位置：

首页 >

文章列表页 >

Nano-sensors for monitoring plant growth： working principles and examples of system integration in applications

Agricultural artificial intelligence | 更新时间：2026-11-05

- Nano-sensors for monitoring plant growth： working principles and examples of system integration in applications
- Journal of Huazhong Agricultural University Vol. 45, Issue 3, Pages: 18-33(2026)
- 作者机构：
  
  1.武汉船舶职业技术学院计算机信息技术学院，武汉 430050
  2.华中农业大学作物纳米生物学与技术中心，武汉 430070
  3.湖北省农业科学院经济作物研究所，武汉 430064
  4.华中农业大学化学学院，武汉430070
- 作者简介：
- 基金信息：
- DOI：10.13300/j.cnki.hnlkxb.2026.03.002
  CLC： S24;TP212
- Received：03 September 2025，
  
  Published：25 May 2026
- 稿件说明：
移动端阅览
叶婷，罗真，徐雯颍，等.面向植物生长监测的纳米传感器：工作机制与系统集成应用示例［J］.华中农业大学学报，2026，45（3）：18‐33.

YE Ting,LUO Zhen,XU Wenying,et al.Nano-sensors for monitoring plant growth： working principles and examples of system integration in applications[J].Journal of Huazhong Agricultural University,2026,45(03):18-33.
叶婷，罗真，徐雯颍，等.面向植物生长监测的纳米传感器：工作机制与系统集成应用示例［J］.华中农业大学学报，2026，45（3）：18‐33. DOI： 10.13300/j.cnki.hnlkxb.2026.03.002.

YE Ting,LUO Zhen,XU Wenying,et al.Nano-sensors for monitoring plant growth： working principles and examples of system integration in applications[J].Journal of Huazhong Agricultural University,2026,45(03):18-33. DOI： 10.13300/j.cnki.hnlkxb.2026.03.002.

摘要

智慧农业的发展亟须超越传统环境监测，实现对植物内在生理状态的精准、实时感知。纳米传感器凭借其纳米尺度效应所带来的超高灵敏度、卓越特异性及与生物体系的良好相容性，为原位、无损、动态解析植物生理过程提供了前所未有的技术工具。本文系统综述了面向植物生长监测的纳米传感器的设计原理、材料体系与应用前沿，重点剖析了纳米传感器在植物体内关键生理信号分子（如H

、Ca

、植物激素等）动态检测中的机制与效能。探讨了纳米传感数据（如近红外荧光影像、高频电化学信号）的特有属性对农业物联网、数据挖掘与智能建模提出的新挑战与新兴解决方案；通过结合一个集成多源纳米传感数据的“智慧种植分析系统”实例，详细阐述了从数据采集、智能处理到决策支持的全链条集成路径。从材料创新、智能抗干扰、系统集成与风险评估4个维度，对纳米传感器在迈向规模化田间应用中所面临的瓶颈问题与未来发展方向进行了系统性展望。

Abstract

The development of intelligent agriculture urgently needs to transcend traditional environmental monitoring to achieve precise and real-time perception of the internal physiological state of plants. Nano-sensors provide unprecedented technological tools for the

in situ

， non-destructive， and dynamic analysis of plant physiological processes due to its ultra-high sensitivity， excellent specificity， and good biocompatibility with biological systems brought about by nanoscale effects. This article systematically reviewed the principles of design， material systems， and cutting-edge applications of nano-sensors for monitoring plant growth， with a focus on analyzing the mechanisms and efficacy of nano-sensors in the dy

namic detection of key physiological signaling molecules including H₂O₂， Ca²⁺， phytohormones within plants. The new challenges and emerging solutions presented by the unique properties of nano-sensing data including near-infrared fluorescence imaging and high-frequency electrochemical signals for agricultural Internet of Things （IoT）， data mining， and intelligent modeling were discussed. The full-chain integration pathway from data acquisition and intelligent processing to decision support was elaborated in detail by combining an example of an “Intelligent planting analysis system” that integrates multi-source nano-sensing data. The bottlenecks and development directions of nano-sensors in moving towards large-scale field applications in the future was systematically prospected from four dimensions including material innovation， intelligent anti-interference， system integration， and risk assessment. It will provide a solid theoretical reference for studying the intersection of intelligent agriculture and nanotechnology.

关键词

Keywords

references

WHEELER T，VON BRAUN J.Climate change impacts on global food security［J］.Science，2013，341（6145）：508-513.

LIPPER L，THORNTON P，CAMPBELL B M，et al.Climate-smart agriculture for food security［J］.Nature climate change，2014，4（12）：1068-1072.

赵春江.智慧农业发展现状及战略目标研究［J］.智慧农业，2019，1（1）：1-7.ZHAO C J.State-of-the-art and recommended developmental strategic objectivs of smart agriculture［J］.Smart agriculture，2019，1（1）：1-7 （in Chinese with English abstract） .

ALI J，MUKARRAM M，OJO J，et al.Harnessing phytohormones：advancing plant growth and defence strategies for sustainable agriculture［J/OL］.Physiologia plantarum，2024， 176（3）：e14307［2025-09-03］.https：//doi.org/10.1111/ppl.14307.

KWAK S Y，WONG M H，LEW T T S，et al.Nanosensor technology applied to living plant systems［J］.Annual review of analytical chemistry，2017，10（1）：113-140.

GIRALDO J P，WU H H，NEWKIRK G M，et al.Nanobiotechnology approaches for engineering smart plant sensors［J］.Nature nanotechnology，2019，14（6）：541-553.

National Academies of Sciences， Engineering， and Medicine.Science breakthroughs to advance food and agricultural research by 2030［R］.Washington， DC：The National Academies Press， 2019.

JAVAID M，HALEEM A，SINGH R P，et al.Exploring the potential of nanosensors：a brief overview［J/OL］.Sensors international，2021，2：100130［2025-09-03］.https：//doi.org/10.1016/j.sintl.2021.100130.

HUANG L，HE X Y，HU J M，et al.Wearable sensor based on covalent organic framework humidity films for long-term monitoring of tomato physiology under abiotic stress［J］.ACS nano，2024，18（48）：33105-33118.

SUN T，LU C Z，SHI Z，et al.PlantRing：a high-throughput wearable sensor system for decoding plant growth，water relations，and innovating irrigation［J/OL］.Plant communications，2025，6（5）：101322［2025-09-03］.https：//doi.org/10.1016/j.xplc.2025.101322.

GIUST D，LUCÍO M I，EL-SAGHEER A H，et al.Graphene oxide-upconversion nanoparticle based portable sensors for assessing nutritional deficiencies in crops［J］.ACS nano，2018，12（6）：6273-6279.

王志豪，樊成孝，王焯，等.一种对作物Mg 2+ 活体检测的全固态微针型传感器制备及应用［J］.农业工程学报，2025，41（9）：29-36.WANG Z H，FAN C X，WANG Z，et al.Development and application of an all-solid-state Mg 2+ microneedle sensorfor crop in situ detection ［J］.Transactions of the CSAE，2025，41（9）：29-36 （in Chinese with English abstract） .

HU H，YUAN H，SUN S C，et al.Machine learning-powered activatable NIR-II fluorescent nanosensor for in vivo monitoring of plant stress responses［J/OL］.Nature communications，2025，16：5114［2025-09-03］.https：//doi.org/10.1038/s41467-025-60182-w.

KIM J H，HELLER D A，JIN H，et al.The rational design of nitric oxide selectivity in single-walled carbon nanotube near-infrared fluorescence sensors for biological detection［J］.Nature chemistry，2009，1（6）：473-481.

KREBS M，HELD K，BINDER A，et al.FRET-based genetically encoded sensors allow high-resolution live cell imaging of Ca²⁺ dynamics［J］.The plant journal，2012，69（1）：181-192.

WU B F，XU H T，SHI Y F，et al.Online monitoring of indole-3-acetic acid in living plants based on nitrogen-doped carbon nanotubes/core–shell Au@Cu 2 O nanoparticles/carbon fiber electrochemical microsensor［J］.ACS sustainable chemistry & engineering，2022，10（40）：13465-13475.

WANG Z，XUE L F，LI M J，et al.Au@SnO 2 -vertical graphene-based microneedle sensor for in situ determination of abscisic acid in plants［J/OL］.Materials science and engineering：C，2021，127：112237［2025-09-03］.https：//doi.org/10.1016/j.msec.2021.112237.

LI X，SUN R J，PAN J Y，et al.All-MXene-printed RF resonators as wireless plant wearable sensors for in situ ethylene detection［J/OL］.Small，2023，19（24）：2207889［2025-09-03］.https：//doi.org/10.1002/smll.202207889.

BOONYAVES K，ANG M C，PARK M，et al.Near-infrared fluorescent carbon nanotube sensors for the plant hormone family gibberellins［J］.Nano letters，2023，23（3）：916-924.

BUKHAMSIN A，AIT LAHCEN A，DE OLIVEIRA FILHO J，et al.Minimally-invasive，real-time，non-destructive，species-independent phytohormone biosensor for precision farming［J/OL］.Biosensors and bioelectronics，2022，214：114515 ［2025-09-03］.https：//doi.org/10.1016/j.bios.2022.114515.

LI Z，LIU Y X，HOSSAIN O，et al.Real-time mon itoring of plant stresses via chemiresistive profiling of leaf volatiles by a wearable sensor［J］.Matter，2021，4（7）：2553-2570.

ZHU C M，KANG S M，WU S C，et al.A self-reporting nanosensor for detecting bacterial exploitation in plants through extracellular DNA［J］.Nano letters，2024，24（48）：15464-15472.

LI Y F，XU H Y，HAN C L，et al.Plant-wearable sensors for intelligent forestry monitoring［J/OL］.Advanced sustainable systems，2023，7（2）：2200333 ［2025-09-03］.https：//doi.org/10.1002/adsu.202200333.

YIN H Y，CAO Y T，MARELLI B，et al.Soil sensors and plant wearables for smart and precision agriculture［J/OL］.Advanced materials，2021，33（20）：2007764［2025-09-03］.https：//doi.org/10.1002/adma.202007764.

YIN S H，IBRAHIM H，SCHNABLE P S，et al.A field-deployable，wearable leaf sensor for continuous monitoring of vapor-pressure deficit［J/OL］.Advanced materials technologies，2021，6（6）：2001246［2025-09-03］.https：//doi.org/10.1002/admt.202001246.

BANERJI S，HÕRAK H，TOROP J，et al.Unravelling the secrets of plants：emerging wearable sensors for plants signals and physiology［J/OL］.Advanced sensor research，2024，3（3）：2300023［2025-09-03］.https：//doi.org/10.1002/adsr.202300023.

DI TOCCO J，LO PRESTI D，MASSARONI C，et al.Plant-wear：a multi-sensor plant wearable platform for growth and microclimate monitoring［J/OL］.Sensors，2023，23（1）：549 ［2025-09-03］.https：//doi.org/10.3390/s23010549.

LEE G，HOSSAIN O，JAMALZADEGAN S，et al.Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring［J/OL］.Science advances，2023，9（15）：eade2232［2025-09-03］.https：//doi.org/10.1126/sciadv.ade2232.

LI X J，JIANG C M，ZHAO F N，et al.Fully stretchable triboelectric nanogenerator for energy harvesting and self-powered sensing［J］.Nano energy，2019，61：78-85.

KIM J J，ALLISON L K，ANDREW T L.Vapor-printed polymer electrodes for long-term，on-demand health monitoring［J/OL］.Science advances，2019，5（3）：eaaw0463［2025-09-03］.https：//doi.org/10.1126/sciadv.aaw0463.

LEE K，PARK J，LEE M S，et al. In situ synthesis of carbon nanotube-graphite electronic devices and their integrations onto surfaces of live plants and insects［J］.Nano letters，2014，14（5）：2647-2654.

LEE G，WEI Q S，ZHU Y.Emerging wearable sensors for plant health monitoring［J/OL］.Advanced functional materials，2021，31（52）：2106475［2025-09-03］.https：//doi.org/10.1002/adfm.202106475.

ZHANG Q，YING Y B，PING J F.Recent advances in plant nanoscience［J/OL］.Advanced science，2022，9（2）：2103414 ［2025-09-03］.https：//doi.org/10.1002/advs.202103414.

MITTLER R，VANDERAUWERA S，SUZUKI N，et al.ROS signaling：the new wave？［J］.Trends in plant science，2011，16（6）：300-309.

VARADARAJ K，KUMARI S S.Lens aquaporins function as peroxiporins to facilitate membrane transport of hydrogen peroxide［J］.Biochemical and biophysical research communications，2020，524（4）：1025-1029.

LEW T T S，KOMAN V B，SILMORE K S，et al.Real-time detection of wound-induced H 2 O 2 signalling waves in plants with optical nanosensors［J］.Nature plants，2020，6（4）：404-415.

WU H H，NIßLER R，MORRIS V，et al.Monitoring plant health with near-infrared fluorescent H 2 O 2 nanosensors［J］.Nano letters，2020，20（4）：2432-2442.

YAN Y，NI M，WANG F，et al.Metal⁃organic framework-based biosensor for detecting hydrogen peroxide in plants through color-to-thermal signal conversion［J］.ACS nano，2022，16（9）：15175-15187.

SHAW D S，HONEYCHURCH K C，SHAW D S，et al.Nanosensor applications in plant science［J/OL］.Biosensors，2022，12（9）：675［2025-09-03］.https：//doi.org/10.3390/bios12090675.

徐雯颍，叶婷，姚雪，等.智慧农业背景下的纳米智能作物构建［J］.智慧农业导刊，2021，1（9）：9-13.XU W Y，YE T，YAO X，et al.Construction of nanosensor-enabled smart plants in the context of smart agriculture［J］.Journal of smart agriculture，2021，1（9）：9-13 （in Chinese with English abstract） .

ZHAI Z Y，MARTÍNEZ J F，BELTRAN V，et al.Decision support systems for agriculture 4.0：survey and challenges［J/OL］.Computers and electronics in agriculture，2020，170：105256［2025-09-03］.https：//doi.org/10.1016/j.compag.2020.105256.

叶婷，马宏娟，卢锐，等.人工智能在智慧农业中的应用：以数据挖掘与机器学习为例［J］.智慧农业导刊，2022，2（18）：27-29.YE T，MA H J，LU R，et al.Application of artificial intelligence in smart agriculture：taking data mining and machine learning as examples ［J］.Journal of smart agriculture，2022，2（18）：27-29 （in Chinese with English abstract） .

GIRALDO J P，LANDRY M P，FALTERMEIER S M，et al.Plant nanobionics approach to augment photosynthesis and biochemical sensing［J］.Nature materials，2014，13（4）：400-408.

MAJUMDAR J，NARASEEYAPPA S，ANKALAKI S.Analysis of agriculture data using data mining techniques：application of big data［J/OL］.Journal of big data，2017，4（1）：20 ［2025-09-03］.https：//doi.org/10.1186/s40537-017-0077-4.

胡荣群.基于大数据的农业模型建构及应用［J］.中国农业资源与区划，2022，43（10）：256-266.HU R Q.Construction and application of agricultural models based on big data［J］.Chinese journal of agricultural resources and regional planning，2022，43（10）：256-266 （in Chinese with English abstract） .

郭博健，王娜，王君姣.数字孪生系统在农业领域的建构路径探究［J］.现代农业装备，2024，45（2）：29-33.GUO B J，WANG N，WANG J J.An exploration of the path of constructing digital twin systems in agricultural field［J］.Modern agricultural equipment，2024，45（2）：29-33 （in Chinese with English abstract） .

叶婷，徐雯颍，龚袁源，等.智慧农业数据分析系统V1.0［CP］.软件著作权登记号：2024SR0067804，证书号：软著登字第12471677，2023.YE T，XU W Y ，GONG Y Y，et al.Smart agriculture data analysis system V1.0［CP］.Software copyright registration number：2024SR0067804，certificate number：Ruan Zhu Deng Zi No.12471677，2023 （in Chinese） .

曾晨，周詹杭，柯新利，等.全球气候变化下农业可持续发展的研究现状和学科交叉分析［J］.华中农业大学学报，2024，43（6）：6-16.ZENG C，ZHOU Z H，KE X L，et al.Review and interdisciplinary analysis of sustainable development of agriculture in context of global climate change ［J］.Journal of Huazhong Agricultural University，2024，43（6）：6-16 （in Chinese with English abstract） .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Method of automatically measuring body size of pigs based on stereo-infrared multi-source data

Hydroponic planting of lettuce with pig-farm biogas slurry UF-NF-RO concentration

Design and experiment of U-shaped hanging-cup-type transplanter for seedlings of water chestnut

Effects of content of biomass ash added on properties of greening substrate block prepared with self-propagating synthesis

Metabolomic comparison of muscle quality in Chinese hooksnout carp （Opsariichthys bidens） between integrated photovoltaic-fishery and conventional pond aquaculture modes

Related Author

XU Dihong

CHEN Mengfang

ZHU Zhihui

ZHOU Mingyan

LI Xuan

Run ZHU

Ke HE

Sixuan LUO

Related Institution

College of Information， Huazhong Agricultural University

Ministry of Agriculture and Rural Affairs Key Laboratory of Smart Farming for Agricultural Animals

College of Engineering， Huazhong Agricultural University

China Academy for Rural Revitalization， Renmin University of China

Hubei Rural Development Research Center， Huazhong Agricultural University

AI问答

⁰