Abstract
Advancement in the flexible substrate led to the sensor fabrication, which offers light weight and low-cost sensors. Such sensors are very important to monitor the plant health on regular intervals and describe the germination of the plant microbial diseases. Numerous climatic and soil characteristics, including rainfall, soil moisture, leaf wetness duration, ambient temperature, and ambient humidity, are used to monitor plant disease. In this paper, we described the reported work for sensing the aforementioned parameters on the flexible substrates. The emphasis has been given on the fabrication of these sensors and their sensor transfer function such as sensitivity, response time, stability, and hysteresis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chouhan SS, Kaul A, Singh UP, Jain S (2018) Bacterial foraging optimization based radial basis function neural network (BRBFNN) for identification and classification of plant leaf diseases: an automatic approach towards plant pathology. IEEE Access 6:8852–8863
Fang Y, Ramasamy RP (2015) Current and prospective methods for plant disease detection. Biosensors 4:537–561. www.mdpi.com/journal/biosensors/
Golhani K, Balasundram SK, Vadamalai G, Pradhan B (2018) A review of neural networks in plant disease detection using hyperspectral data. INFORM
Iqbal Z et al (2018) An automated detection and classification of citrus plant diseases using image processing techniques: a review. Comput Electron Agric 153:12–32
Jain A, Sarsaiya S, Wu Q, Lu Y, Shi J (2019) A review of plant leaf fungal diseases and its environment speciation. Bioengineered 409–424
Kumar M, Kumar A, Palaparthy VS (2021) Soil sensors based prediction system for plant diseases using exploratory data analysis and machine learning. IEEE Sens J 21(16):17455–17468
Patle KS, Saini R, Kumar A, Palaparthy VS (2021a) Field evaluation of smart sensor system for plant disease prediction using LSTM network. IEEE Sens J 22(4):3715–3725
Patle KS, Saini R, Kumar A, Surya SG, Palaparthy VS, Salama KN (2021b) IoT enabled, leaf wetness sensor on the flexible substrates for in-situ plant disease management. IEEE Sens J 21(17):19481–19491
Patle KS, Dehingia B, Kalita H, Palaparthy VS (2022) Highly sensitive graphene oxide leaf wetness sensor for disease supervision on medicinal plants. Elsevier Comput Electron Agric 200:107225
Su P-G, Wang C-S (2007) Novel flexible resistive-type humidity sensor. Sens Actuators, B Chem 123(2):1071–1076
United Nations, Department of Economic and Social Affairs, Population Division (2019) World population prospects 2019: highlights (ST/ESA/SER.A/423)
Wang YF, et al. (2020) Fully printed PEDOT: PSS-based temperature sensor with high humidity stability for wireless healthcare monitoring. Sci Rep 10(1):2467
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Patle, K.S., Khaparde, P., Bhatti, G., Agrawal, Y., Palaparthy, V.S. (2024). Flexible Sensors for Plant Disease Monitoring. In: Agrawal, Y., Mummaneni, K., Sathyakam, P.U. (eds) Interconnect Technologies for Integrated Circuits and Flexible Electronics. Springer Tracts in Electrical and Electronics Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-4476-7_15
Download citation
DOI: https://doi.org/10.1007/978-981-99-4476-7_15
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-4475-0
Online ISBN: 978-981-99-4476-7
eBook Packages: EngineeringEngineering (R0)