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Development of an Apparatus for Crop-Growth Monitoring and Diagnosis

To non-destructively acquire leaf nitrogen content (LNC), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW) data at high speed and low cost, a portable apparatus for crop-growth monitoring and diagnosis (CGMD) was developed according to the spectral monitoring mechan...

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Autores principales: Ni, Jun, Zhang, Jingchao, Wu, Rusong, Pang, Fangrong, Zhu, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163955/
https://www.ncbi.nlm.nih.gov/pubmed/30227614
http://dx.doi.org/10.3390/s18093129
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author Ni, Jun
Zhang, Jingchao
Wu, Rusong
Pang, Fangrong
Zhu, Yan
author_facet Ni, Jun
Zhang, Jingchao
Wu, Rusong
Pang, Fangrong
Zhu, Yan
author_sort Ni, Jun
collection PubMed
description To non-destructively acquire leaf nitrogen content (LNC), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW) data at high speed and low cost, a portable apparatus for crop-growth monitoring and diagnosis (CGMD) was developed according to the spectral monitoring mechanisms of crop growth. According to the canopy characteristics of crops and actual requirements of field operation environments, splitting light beams by using an optical filter and proper structural parameters were determined for the sensors. Meanwhile, an integral-type weak optoelectronic signal processing circuit was designed, which changed the gain of the system and guaranteed the high resolution of the apparatus by automatically adjusting the integration period based on the irradiance received from ambient light. In addition, a coupling processor system for a sensor information and growth model based on the microcontroller chip was developed. Field experiments showed that normalised vegetation index (NDVI) measured separately through the CGMD apparatus and the ASD spectrometer showed a good linear correlation. For measurements of canopy reflectance spectra of rice and wheat, their linear determination coefficients (R(2)) were 0.95 and 0.92, respectively while the root mean square errors (RMSEs) were 0.02 and 0.03, respectively. NDVI value measured by using the CGMD apparatus and growth indices of rice and wheat exhibited a linear relationship. For the monitoring models for LNC, LNA, LAI, and LDW of rice based on linear fitting of NDVI, R(2) were 0.64, 0.67, 0.63 and 0.70, and RMSEs were 0.31, 2.29, 1.15 and 0.05, respectively. In addition, R(2) of the models for monitoring LNC, LNA, LAI, and LDW of wheat on the basis of linear fitting of NDVI were 0.82, 0.71, 0.72 and 0.70, and RMSEs were 0.26, 2.30, 1.43, and 0.05, respectively.
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spelling pubmed-61639552018-10-10 Development of an Apparatus for Crop-Growth Monitoring and Diagnosis Ni, Jun Zhang, Jingchao Wu, Rusong Pang, Fangrong Zhu, Yan Sensors (Basel) Article To non-destructively acquire leaf nitrogen content (LNC), leaf nitrogen accumulation (LNA), leaf area index (LAI), and leaf dry weight (LDW) data at high speed and low cost, a portable apparatus for crop-growth monitoring and diagnosis (CGMD) was developed according to the spectral monitoring mechanisms of crop growth. According to the canopy characteristics of crops and actual requirements of field operation environments, splitting light beams by using an optical filter and proper structural parameters were determined for the sensors. Meanwhile, an integral-type weak optoelectronic signal processing circuit was designed, which changed the gain of the system and guaranteed the high resolution of the apparatus by automatically adjusting the integration period based on the irradiance received from ambient light. In addition, a coupling processor system for a sensor information and growth model based on the microcontroller chip was developed. Field experiments showed that normalised vegetation index (NDVI) measured separately through the CGMD apparatus and the ASD spectrometer showed a good linear correlation. For measurements of canopy reflectance spectra of rice and wheat, their linear determination coefficients (R(2)) were 0.95 and 0.92, respectively while the root mean square errors (RMSEs) were 0.02 and 0.03, respectively. NDVI value measured by using the CGMD apparatus and growth indices of rice and wheat exhibited a linear relationship. For the monitoring models for LNC, LNA, LAI, and LDW of rice based on linear fitting of NDVI, R(2) were 0.64, 0.67, 0.63 and 0.70, and RMSEs were 0.31, 2.29, 1.15 and 0.05, respectively. In addition, R(2) of the models for monitoring LNC, LNA, LAI, and LDW of wheat on the basis of linear fitting of NDVI were 0.82, 0.71, 0.72 and 0.70, and RMSEs were 0.26, 2.30, 1.43, and 0.05, respectively. MDPI 2018-09-17 /pmc/articles/PMC6163955/ /pubmed/30227614 http://dx.doi.org/10.3390/s18093129 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ni, Jun
Zhang, Jingchao
Wu, Rusong
Pang, Fangrong
Zhu, Yan
Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title_full Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title_fullStr Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title_full_unstemmed Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title_short Development of an Apparatus for Crop-Growth Monitoring and Diagnosis
title_sort development of an apparatus for crop-growth monitoring and diagnosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163955/
https://www.ncbi.nlm.nih.gov/pubmed/30227614
http://dx.doi.org/10.3390/s18093129
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