Mobile Laser-Induced Breakdown Spectroscopy for Future Application in Precision Agriculture-A Case Study.

LIBS feature selection multivariate methods precision agriculture soil

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
15 Aug 2023
Historique:
received: 28 06 2023
revised: 25 07 2023
accepted: 28 07 2023
medline: 26 8 2023
pubmed: 26 8 2023
entrez: 26 8 2023
Statut: epublish

Résumé

In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.

Identifiants

pubmed: 37631715
pii: s23167178
doi: 10.3390/s23167178
pmc: PMC10459606
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Federal Ministry of Education and Research
ID : 031B0513H

Références

Sensors (Basel). 2020 Jan 11;20(2):
pubmed: 31940811
Sci Total Environ. 2016 Sep 15;565:1116-1123
pubmed: 27261426
Sensors (Basel). 2019 Nov 28;19(23):
pubmed: 31795286
Appl Spectrosc. 2012 Apr;66(4):347-419
pubmed: 22449322
Anal Chim Acta. 2009 Aug 19;648(1):77-84
pubmed: 19616692

Auteurs

Alexander Erler (A)

Physical Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.

Daniel Riebe (D)

Physical Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.

Toralf Beitz (T)

Physical Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.

Hans-Gerd Löhmannsröben (HG)

Physical Chemistry, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany.

Mathias Leenen (M)

Soil Science and Soil Ecology, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Nussallee 13, 53115 Bonn, Germany.

Stefan Pätzold (S)

Soil Science and Soil Ecology, Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Nussallee 13, 53115 Bonn, Germany.

Markus Ostermann (M)

Process Analytical Technology, Federal Institute for Materials Research and Testing (BAM), Richard-Willstätter-Straße 11, 12489 Berlin, Germany.

Michal Wójcik (M)

Department of Field Theory, Electronic Circuits and Optoelectronics, Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50370 Wroclaw, Poland.

Classifications MeSH