Advances in Flexible Wearable Biosensors for Early Warning of Crop Stress and Disease-pest Infestation： A Comprehensive Review

doi:10.13560/j.cnki.biotech.bull.1985.2025-0911

Abstract

Abstract:

Flexible wearable biosensors have high sensitivity, stability, flexibility, and stretchability, enabling conformal adhesion to crop epidermis and real-time conversion of physiological signals into electrical signals for dynamic monitoring of plant physiological changes. In recent years, such sensors have rapidly advanced in the field of crop health monitoring and stress early-warning, providing a novel paradigm for real-time diagnosis of growth status, diseases, pests, and abiotic stresses. However, their large-scale application has been limited by key factors including long-term stable adhesion, environmental tolerance, multi-signal integration capability, and cost-effectiveness. This review summarized recent advances in plant wearable flexible sensors for crop health monitoring and stress early-warning, with a focus on their core characteristics, primary classifications, and sensing performance. Furthermore, it analyzed the critical bottlenecks in the translation of flexible wearable sensors into agricultural practices from multiple dimensions: early identification of diseases and pests, water status, metabolic changes, pesticide residues, and morphological strain. It also prospected the future pathways of their integration with artificial intelligence, nanotechnology, and advanced materials, which may provide important references for theoretical breakthroughs and technological implementation in crop health management within the context of smart agriculture.

Key words: flexible wearable biosensors, crop growth stress, pest and disease, pre-alarming monitoring, smart agriculture

HE Jun-jie, HE Yang, YU Wei, GUAN Hua-nan. Advances in Flexible Wearable Biosensors for Early Warning of Crop Stress and Disease-pest Infestation： A Comprehensive Review[J]. Biotechnology Bulletin, 2026, 42(4): 38-52.

Figures/Tables 4

References 98

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传感器构成 Sensor composition	传感对象 Sensing object	检测对象 Detecting object	检测指标 Testing index	检测范围 Detection range	响应时间 Response time	传感方式 Detecting means	传感器安装部位 Sensor installation site	参考文献 Reference
聚酰亚胺、丝网印刷银、激光诱导石墨烯、ZnIn₂S₄（ZIS）纳米片	瓜栗	蒸腾作用	光照、水分	相对湿度30%-90%	<4 ms	非接触式	植物叶片下表面	［36］
碳化丝绸乔其纱（CSG）	番茄、西瓜、大豆、菜豆	蒸腾作用	水分	6 cm传感器相对湿度响应范围≥0.17%、12 cm传感器相对湿度响应范围≥0.08%、30 cm传感器相对湿度响应范围≥0.03%	<70 ms	非侵入式	茎与果实	［38］
PI、激光诱导石墨烯（LIG）、氧化石墨烯（GO）	绿萝	蒸腾作用	水分	相对湿度响应范围10%-90%	15.8 s	非侵入式	植物叶片的下表面	［28］
聚酰亚胺、氧化石墨烯	玉米	蒸腾作用、光合作用	水分、光照	相对湿度响应范围11%-95%	20.3 s	非侵入式	植物叶片的下表面	［43］
COF_MOP-TAPB、COF_PDA-TAPPy、COF_BPDA-TAPPy、MXene、银纳米线、聚二甲基硅氧烷（PDMS）	番茄	叶片表面湿度	微环境	相对湿度响应范围10%-98%	5 s	非侵入式	茎、植物叶片的下表面	［44］
激光诱导石墨烯（LIG）、MXene、二硫化钼纳米片、丝网印刷电极SPE	草莓	没食子酸	植物代谢物	≥625 nmol/L	0.5 s	侵入式	叶片	［41］
激光诱导石墨烯（LIG）、银电极、聚酰亚胺（PI）基底	鳄梨	水杨酸	植物代谢物	≥8 200 nmol/L	20 s	非侵入式	叶片	［45］
MIL-88B（Fe）、MIL-53（Fe）、DUT-8（Ni）、Cd（PNMI）、Co（5-NH₂-bdc）（bpy）、［Cu₂（bdc）₂（bpy）］n、［Cu₂（bdc）₂（bpe）］n	番茄	（E）-2-己烯醇、1-己醛、（E）-2-己烯醛、水杨酸甲酯、苯甲醛、4-乙基愈创木酚	挥发性有机化合物	未提及	3 600 s	非侵入式	无接触	［46］
Au@AgNWs、多壁碳纳米管（MWCNTs）、疏水溶胶-凝胶层、PDMS	番茄	叶醛类、酮类和醛类	挥发性有机化合物、温度、湿度	≥100 ppm	120 s	非侵入式	叶片下表皮	［30］
氧化还原石墨烯（rGO）、AgNW、ITP ［碘硫酚］、BPT ［溴硫酚］、CTP ［氯硫酚］和FTP ［氟硫酚］	番茄	（E）-2-己烯醛和2-苯乙醇、（Z）-3-己烯醛、1-己烯醛、（E）-2-己烯醇和（E）-2-乙酸己烯酯、茉莉酸甲酯和水杨酸甲酯、苯甲醛、4-乙基愈创木酚、4-乙基苯酚、吲哚和苯并噻唑	挥发性有机化合物	ITP-AuNP@rGO：≥0.17 ppm、 BTP-AuNP@rGO：≥0.55 ppm CTP-AuNP@rGO：≥2.0 ppm NTP-AuNP@rGO：≥3.9 ppm	100 s	非侵入式	叶片或茎	［47］
nanoMIP微丝传感器、nanoMIP纤维丝传感器	番茄	D-葡萄糖	代谢产物	nanoMIP微丝传感器：≥79.4 nmol/L nanoMIP纤维丝传感器：≥251 000 nmol/L	300 s	侵入式	茎	［48］
激光诱导石墨烯（LIG）、金纳米颗粒（AuNPs）和黑磷纳米片（BP）	草莓、苹果	槲皮素	代谢产物	≥650 nmol/L	未提及	侵入式	叶片、果实表皮	［49］
碳纳米管纳米带（IONCs-CNR）、明胶水凝胶	芝麻、生菜、番茄、苹果	N-（1，3-二甲基丁基）-N'-苯基对苯二胺（6-PPD）	污染物	≥2.93 nmol/L	1 800 s	非侵入式	叶片、果实	［50］
醋酸纤维素、丙酮、水	番茄、生菜	多菌灵、百草枯	农药残留	多菌灵：≥54.9 nmol/L 百草枯：≥19.8 nmol/L	50 s	非侵入式	表皮	［39］
聚酰亚胺（PI）、PDMS、激光诱导石墨烯-金纳米颗粒（LIG-Au）	绿萝、生菜	甲基对硫磷	农药残留	≥0.646 nmol/L	38.65 s	非侵入式	叶片	［51］

传感器构成 Sensor composition	传感对象 Sensing object	检测对象 Detecting object	检测指标 Testing index	检测范围 Detection range	响应时间 Response time	传感方式 Detecting means	传感器安装部位 Sensor installation site	参考文献 Reference
聚酰亚胺、丝网印刷银、激光诱导石墨烯、ZnIn₂S₄（ZIS）纳米片	瓜栗	蒸腾作用	光照、水分	相对湿度30%-90%	<4 ms	非接触式	植物叶片下表面	［36］
碳化丝绸乔其纱（CSG）	番茄、西瓜、大豆、菜豆	蒸腾作用	水分	6 cm传感器相对湿度响应范围≥0.17%、12 cm传感器相对湿度响应范围≥0.08%、30 cm传感器相对湿度响应范围≥0.03%	<70 ms	非侵入式	茎与果实	［38］
PI、激光诱导石墨烯（LIG）、氧化石墨烯（GO）	绿萝	蒸腾作用	水分	相对湿度响应范围10%-90%	15.8 s	非侵入式	植物叶片的下表面	［28］
聚酰亚胺、氧化石墨烯	玉米	蒸腾作用、光合作用	水分、光照	相对湿度响应范围11%-95%	20.3 s	非侵入式	植物叶片的下表面	［43］
COF_MOP-TAPB、COF_PDA-TAPPy、COF_BPDA-TAPPy、MXene、银纳米线、聚二甲基硅氧烷（PDMS）	番茄	叶片表面湿度	微环境	相对湿度响应范围10%-98%	5 s	非侵入式	茎、植物叶片的下表面	［44］
激光诱导石墨烯（LIG）、MXene、二硫化钼纳米片、丝网印刷电极SPE	草莓	没食子酸	植物代谢物	≥625 nmol/L	0.5 s	侵入式	叶片	［41］
激光诱导石墨烯（LIG）、银电极、聚酰亚胺（PI）基底	鳄梨	水杨酸	植物代谢物	≥8 200 nmol/L	20 s	非侵入式	叶片	［45］
MIL-88B（Fe）、MIL-53（Fe）、DUT-8（Ni）、Cd（PNMI）、Co（5-NH₂-bdc）（bpy）、［Cu₂（bdc）₂（bpy）］n、［Cu₂（bdc）₂（bpe）］n	番茄	（E）-2-己烯醇、1-己醛、（E）-2-己烯醛、水杨酸甲酯、苯甲醛、4-乙基愈创木酚	挥发性有机化合物	未提及	3 600 s	非侵入式	无接触	［46］
Au@AgNWs、多壁碳纳米管（MWCNTs）、疏水溶胶-凝胶层、PDMS	番茄	叶醛类、酮类和醛类	挥发性有机化合物、温度、湿度	≥100 ppm	120 s	非侵入式	叶片下表皮	［30］
氧化还原石墨烯（rGO）、AgNW、ITP ［碘硫酚］、BPT ［溴硫酚］、CTP ［氯硫酚］和FTP ［氟硫酚］	番茄	（E）-2-己烯醛和2-苯乙醇、（Z）-3-己烯醛、1-己烯醛、（E）-2-己烯醇和（E）-2-乙酸己烯酯、茉莉酸甲酯和水杨酸甲酯、苯甲醛、4-乙基愈创木酚、4-乙基苯酚、吲哚和苯并噻唑	挥发性有机化合物	ITP-AuNP@rGO：≥0.17 ppm、 BTP-AuNP@rGO：≥0.55 ppm CTP-AuNP@rGO：≥2.0 ppm NTP-AuNP@rGO：≥3.9 ppm	100 s	非侵入式	叶片或茎	［47］
nanoMIP微丝传感器、nanoMIP纤维丝传感器	番茄	D-葡萄糖	代谢产物	nanoMIP微丝传感器：≥79.4 nmol/L nanoMIP纤维丝传感器：≥251 000 nmol/L	300 s	侵入式	茎	［48］
激光诱导石墨烯（LIG）、金纳米颗粒（AuNPs）和黑磷纳米片（BP）	草莓、苹果	槲皮素	代谢产物	≥650 nmol/L	未提及	侵入式	叶片、果实表皮	［49］
碳纳米管纳米带（IONCs-CNR）、明胶水凝胶	芝麻、生菜、番茄、苹果	N-（1，3-二甲基丁基）-N'-苯基对苯二胺（6-PPD）	污染物	≥2.93 nmol/L	1 800 s	非侵入式	叶片、果实	［50］
醋酸纤维素、丙酮、水	番茄、生菜	多菌灵、百草枯	农药残留	多菌灵：≥54.9 nmol/L 百草枯：≥19.8 nmol/L	50 s	非侵入式	表皮	［39］
聚酰亚胺（PI）、PDMS、激光诱导石墨烯-金纳米颗粒（LIG-Au）	绿萝、生菜	甲基对硫磷	农药残留	≥0.646 nmol/L	38.65 s	非侵入式	叶片	［51］