A Novel Method for Soil Organic Matter Determination by Using an Artificial Olfactory System.
artificial olfactory system
gas sensor array
prediction methods
regression algorithms
soil organic matter
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
04 Aug 2019
04 Aug 2019
Historique:
received:
11
07
2019
revised:
01
08
2019
accepted:
02
08
2019
entrez:
7
8
2019
pubmed:
7
8
2019
medline:
7
1
2020
Statut:
epublish
Résumé
Soil organic matter (SOM) is a major indicator of soil fertility and nutrients. In this study, a soil organic matter measuring method based on an artificial olfactory system (AOS) was designed. An array composed of 10 identical gas sensors controlled at different temperatures was used to collect soil gases. From the response curve of each sensor, four features were extracted (maximum value, mean differential coefficient value, response area value, and the transient value at the 20th second). Then, soil organic matter regression prediction models were built based on back-propagation neural network (BPNN), support vector regression (SVR), and partial least squares regression (PLSR). The prediction performance of each model was evaluated using the coefficient of determination (R
Identifiants
pubmed: 31382683
pii: s19153417
doi: 10.3390/s19153417
pmc: PMC6696477
pii:
doi:
Substances chimiques
Gases
0
Soil
0
Volatile Organic Compounds
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Key R&D Plan project
ID : 2016YFD070030201
Organisme : Jilin Science and Technology Development Plan
ID : 20190302116GX
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