Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System

In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the r...

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Main Authors: Ning Liu, Gang Liu, Hong Sun
Format: Article
Language:English
Published: MDPI AG 2020-06-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/12/3430
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spelling doaj-774cc409f39b4d93be4dd0372e91521c2020-11-25T03:19:55ZengMDPI AGSensors1424-82202020-06-01203430343010.3390/s20123430Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor SystemNing Liu0Gang Liu1Hong Sun2Key Lab of Modern Precision Agriculture System Integration Research, Ministry of Education of China, China Agricultural University, Beijing 100083, ChinaKey Lab of Modern Precision Agriculture System Integration Research, Ministry of Education of China, China Agricultural University, Beijing 100083, ChinaKey Lab of Modern Precision Agriculture System Integration Research, Ministry of Education of China, China Agricultural University, Beijing 100083, ChinaIn this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the real-time detection of SPAD value, a recommended indicating parameter of chlorophyll content. The modified difference vegetation index (MDVI) linking the Otsu algorithm (OTSU) and the connected domain-labeling (CDL) method (MDVI–OTSU–CDL) is proposed to accurately extract the potato plant. Additionally, the segmentation accuracy under different modified coefficients of MDVI was analyzed. Then, the reflectance of potato plants was extracted by the segmented mask images. The partial least squares (PLS) regression was employed to establish the SPAD value detection model based on sensitive variables selected using the uninformative variable elimination (UVE) algorithm. Based on the segmented spectral image and the UVE–PLS model, the visualization distribution map of SPAD value was drawn by pseudo-color processing technology. Finally, the testing dataset was employed to measure the stability and practicality of the developed detection system. This study provides a powerful support for the real-time detection of SPAD value and the distribution of crops in the field.https://www.mdpi.com/1424-8220/20/12/3430spectral imaging sensorimage segmentationmodified difference vegetation index (MDVI)OTSUconnected domainpotato plants
collection DOAJ
language English
format Article
sources DOAJ
author Ning Liu
Gang Liu
Hong Sun
spellingShingle Ning Liu
Gang Liu
Hong Sun
Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
Sensors
spectral imaging sensor
image segmentation
modified difference vegetation index (MDVI)
OTSU
connected domain
potato plants
author_facet Ning Liu
Gang Liu
Hong Sun
author_sort Ning Liu
title Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
title_short Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
title_full Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
title_fullStr Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
title_full_unstemmed Real-Time Detection on SPAD Value of Potato Plant Using an In-Field Spectral Imaging Sensor System
title_sort real-time detection on spad value of potato plant using an in-field spectral imaging sensor system
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2020-06-01
description In this study, a SPAD value detection system was developed based on a 25-wavelength spectral sensor to give a real-time indication of the nutrition distribution of potato plants in the field. Two major advantages of the detection system include the automatic segmentation of spectral images and the real-time detection of SPAD value, a recommended indicating parameter of chlorophyll content. The modified difference vegetation index (MDVI) linking the Otsu algorithm (OTSU) and the connected domain-labeling (CDL) method (MDVI–OTSU–CDL) is proposed to accurately extract the potato plant. Additionally, the segmentation accuracy under different modified coefficients of MDVI was analyzed. Then, the reflectance of potato plants was extracted by the segmented mask images. The partial least squares (PLS) regression was employed to establish the SPAD value detection model based on sensitive variables selected using the uninformative variable elimination (UVE) algorithm. Based on the segmented spectral image and the UVE–PLS model, the visualization distribution map of SPAD value was drawn by pseudo-color processing technology. Finally, the testing dataset was employed to measure the stability and practicality of the developed detection system. This study provides a powerful support for the real-time detection of SPAD value and the distribution of crops in the field.
topic spectral imaging sensor
image segmentation
modified difference vegetation index (MDVI)
OTSU
connected domain
potato plants
url https://www.mdpi.com/1424-8220/20/12/3430
work_keys_str_mv AT ningliu realtimedetectiononspadvalueofpotatoplantusinganinfieldspectralimagingsensorsystem
AT gangliu realtimedetectiononspadvalueofpotatoplantusinganinfieldspectralimagingsensorsystem
AT hongsun realtimedetectiononspadvalueofpotatoplantusinganinfieldspectralimagingsensorsystem
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