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Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring
Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting v...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096584/ https://www.ncbi.nlm.nih.gov/pubmed/37043563 http://dx.doi.org/10.1126/sciadv.ade2232 |
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author | Lee, Giwon Hossain, Oindrila Jamalzadegan, Sina Liu, Yuxuan Wang, Hongyu Saville, Amanda C. Shymanovich, Tatsiana Paul, Rajesh Rotenberg, Dorith Whitfield, Anna E. Ristaino, Jean B. Zhu, Yong Wei, Qingshan |
author_facet | Lee, Giwon Hossain, Oindrila Jamalzadegan, Sina Liu, Yuxuan Wang, Hongyu Saville, Amanda C. Shymanovich, Tatsiana Paul, Rajesh Rotenberg, Dorith Whitfield, Anna E. Ristaino, Jean B. Zhu, Yong Wei, Qingshan |
author_sort | Lee, Giwon |
collection | PubMed |
description | Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting volatile organic compounds (VOCs), temperature, and humidity are integrated into a single platform. The abaxial leaf attachment position is selected on the basis of the stomata density to improve the sensor signal strength. This versatile platform enables various stress monitoring applications, ranging from tracking plant water loss to early detection of plant pathogens. A machine learning model was also developed to analyze multichannel sensor data for quantitative detection of tomato spotted wilt virus as early as 4 days after inoculation. The model also evaluates different sensor combinations for early disease detection and predicts that minimally three sensors are required including the VOC sensors. |
format | Online Article Text |
id | pubmed-10096584 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-100965842023-04-13 Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring Lee, Giwon Hossain, Oindrila Jamalzadegan, Sina Liu, Yuxuan Wang, Hongyu Saville, Amanda C. Shymanovich, Tatsiana Paul, Rajesh Rotenberg, Dorith Whitfield, Anna E. Ristaino, Jean B. Zhu, Yong Wei, Qingshan Sci Adv Physical and Materials Sciences Wearable plant sensors hold tremendous potential for smart agriculture. We report a lower leaf surface-attached multimodal wearable sensor for continuous monitoring of plant physiology by tracking both biochemical and biophysical signals of the plant and its microenvironment. Sensors for detecting volatile organic compounds (VOCs), temperature, and humidity are integrated into a single platform. The abaxial leaf attachment position is selected on the basis of the stomata density to improve the sensor signal strength. This versatile platform enables various stress monitoring applications, ranging from tracking plant water loss to early detection of plant pathogens. A machine learning model was also developed to analyze multichannel sensor data for quantitative detection of tomato spotted wilt virus as early as 4 days after inoculation. The model also evaluates different sensor combinations for early disease detection and predicts that minimally three sensors are required including the VOC sensors. American Association for the Advancement of Science 2023-04-12 /pmc/articles/PMC10096584/ /pubmed/37043563 http://dx.doi.org/10.1126/sciadv.ade2232 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Lee, Giwon Hossain, Oindrila Jamalzadegan, Sina Liu, Yuxuan Wang, Hongyu Saville, Amanda C. Shymanovich, Tatsiana Paul, Rajesh Rotenberg, Dorith Whitfield, Anna E. Ristaino, Jean B. Zhu, Yong Wei, Qingshan Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title | Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title_full | Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title_fullStr | Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title_full_unstemmed | Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title_short | Abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
title_sort | abaxial leaf surface-mounted multimodal wearable sensor for continuous plant physiology monitoring |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10096584/ https://www.ncbi.nlm.nih.gov/pubmed/37043563 http://dx.doi.org/10.1126/sciadv.ade2232 |
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