Matches in SemOpenAlex for { <https://semopenalex.org/work/W2991049069> ?p ?o ?g. }
- W2991049069 endingPage "5244" @default.
- W2991049069 startingPage "5244" @default.
- W2991049069 abstract "The lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method." @default.
- W2991049069 created "2019-12-05" @default.
- W2991049069 creator A5007357357 @default.
- W2991049069 creator A5010179296 @default.
- W2991049069 creator A5068150893 @default.
- W2991049069 creator A5069227968 @default.
- W2991049069 creator A5079216533 @default.
- W2991049069 creator A5080568497 @default.
- W2991049069 date "2019-11-28" @default.
- W2991049069 modified "2023-09-27" @default.
- W2991049069 title "Comparison of Calibration Approaches in Laser-Induced Breakdown Spectroscopy for Proximal Soil Sensing in Precision Agriculture" @default.
- W2991049069 cites W1581044602 @default.
- W2991049069 cites W1592341820 @default.
- W2991049069 cites W1969839347 @default.
- W2991049069 cites W1981768708 @default.
- W2991049069 cites W1992982045 @default.
- W2991049069 cites W1993662670 @default.
- W2991049069 cites W2017926751 @default.
- W2991049069 cites W2019046374 @default.
- W2991049069 cites W2022314704 @default.
- W2991049069 cites W2047482657 @default.
- W2991049069 cites W2053185220 @default.
- W2991049069 cites W2071060304 @default.
- W2991049069 cites W2075140015 @default.
- W2991049069 cites W2082966315 @default.
- W2991049069 cites W2090684728 @default.
- W2991049069 cites W2111408234 @default.
- W2991049069 cites W2120620624 @default.
- W2991049069 cites W2132355204 @default.
- W2991049069 cites W2145855871 @default.
- W2991049069 cites W2258720274 @default.
- W2991049069 cites W2495691485 @default.
- W2991049069 cites W2552035859 @default.
- W2991049069 cites W2570322674 @default.
- W2991049069 cites W2617720169 @default.
- W2991049069 cites W2626765719 @default.
- W2991049069 cites W2756540409 @default.
- W2991049069 cites W2774019083 @default.
- W2991049069 cites W2802704953 @default.
- W2991049069 cites W2829446111 @default.
- W2991049069 cites W2937023005 @default.
- W2991049069 cites W2945374171 @default.
- W2991049069 cites W40397213 @default.
- W2991049069 doi "https://doi.org/10.3390/s19235244" @default.
- W2991049069 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6928797" @default.
- W2991049069 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31795286" @default.
- W2991049069 hasPublicationYear "2019" @default.
- W2991049069 type Work @default.
- W2991049069 sameAs 2991049069 @default.
- W2991049069 citedByCount "13" @default.
- W2991049069 countsByYear W29910490692020 @default.
- W2991049069 countsByYear W29910490692021 @default.
- W2991049069 countsByYear W29910490692022 @default.
- W2991049069 countsByYear W29910490692023 @default.
- W2991049069 crossrefType "journal-article" @default.
- W2991049069 hasAuthorship W2991049069A5007357357 @default.
- W2991049069 hasAuthorship W2991049069A5010179296 @default.
- W2991049069 hasAuthorship W2991049069A5068150893 @default.
- W2991049069 hasAuthorship W2991049069A5069227968 @default.
- W2991049069 hasAuthorship W2991049069A5079216533 @default.
- W2991049069 hasAuthorship W2991049069A5080568497 @default.
- W2991049069 hasBestOaLocation W29910490691 @default.
- W2991049069 hasConcept C105795698 @default.
- W2991049069 hasConcept C107872376 @default.
- W2991049069 hasConcept C113196181 @default.
- W2991049069 hasConcept C118518473 @default.
- W2991049069 hasConcept C119857082 @default.
- W2991049069 hasConcept C120217122 @default.
- W2991049069 hasConcept C121332964 @default.
- W2991049069 hasConcept C127313418 @default.
- W2991049069 hasConcept C151304367 @default.
- W2991049069 hasConcept C159390177 @default.
- W2991049069 hasConcept C159750122 @default.
- W2991049069 hasConcept C161584116 @default.
- W2991049069 hasConcept C165838908 @default.
- W2991049069 hasConcept C166957645 @default.
- W2991049069 hasConcept C185592680 @default.
- W2991049069 hasConcept C199163554 @default.
- W2991049069 hasConcept C205649164 @default.
- W2991049069 hasConcept C22354355 @default.
- W2991049069 hasConcept C32891209 @default.
- W2991049069 hasConcept C33923547 @default.
- W2991049069 hasConcept C39432304 @default.
- W2991049069 hasConcept C41008148 @default.
- W2991049069 hasConcept C50497907 @default.
- W2991049069 hasConcept C50516716 @default.
- W2991049069 hasConcept C62520636 @default.
- W2991049069 hasConcept C62649853 @default.
- W2991049069 hasConceptScore W2991049069C105795698 @default.
- W2991049069 hasConceptScore W2991049069C107872376 @default.
- W2991049069 hasConceptScore W2991049069C113196181 @default.
- W2991049069 hasConceptScore W2991049069C118518473 @default.
- W2991049069 hasConceptScore W2991049069C119857082 @default.
- W2991049069 hasConceptScore W2991049069C120217122 @default.
- W2991049069 hasConceptScore W2991049069C121332964 @default.
- W2991049069 hasConceptScore W2991049069C127313418 @default.
- W2991049069 hasConceptScore W2991049069C151304367 @default.
- W2991049069 hasConceptScore W2991049069C159390177 @default.