Literature DB >> 35972950

Correction: Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

Elizabeth Jeanne Parent, Serge-Étienne Parent, Léon Etienne Parent.   

Abstract

[This corrects the article DOI: 10.1371/journal.pone.0233242.].

Entities:  

Year:  2022        PMID: 35972950      PMCID: PMC9380913          DOI: 10.1371/journal.pone.0273277

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


In the “Spectral data modeling” subsection of the “Results” section, there is an error in the fifth sentence of the first paragraph. The correct sentence is: “Combining laser and sedimentation methods in Set2 improved the clay predictions with R2 values of 0.80–0.85.” In Fig 4, incorrect titles were used on the left-hand side to correspond to the values of the Mean ilr differences. The authors have provided a corrected version here.
Fig 4
There are errors in Table 2. Please see the correct Table 2 here.
Table 2

Comparison of methods (method1 minus method2) using paired t-test and confidence intervals (p ≤ 0.05).

Target variableMethod1Method2p.valueN
[Carbon | Clay,Silt,Sand]Sedimentation 2-point No peroxideSedimentation 2-point peroxidens38
[Carbon | Clay,Silt,Sand]Sedimentation 2-point No peroxideLaser 0 min **** 46
[Carbon | Clay,Silt,Sand]Sedimentation 2-point No peroxideLaser 2 min **** 106
[Carbon | Clay,Silt,Sand]Sedimentation 2-point No peroxideSedimentation multi-point No peroxide **** 763
[Carbon | Clay,Silt,Sand]Sedimentation 2-point No peroxideSedimentation multi-point peroxide **** 206
[Clay | Silt,Sand]Sedimentation 2-point No peroxideSedimentation 2-point peroxide ** 38
[Clay | Silt,Sand]Sedimentation 2-point No peroxideLaser 0 min **** 46
[Clay | Silt,Sand]Sedimentation 2-point No peroxide **** **** 106
[Clay | Silt,Sand]Sedimentation 2-point No peroxideSedimentation multi-point No peroxide **** 763
[Clay | Silt,Sand]Sedimentation 2-point No peroxideSedimentation multi-point peroxidens206
[Silt | Sand]Sedimentation 2-point No peroxideSedimentation 2-point peroxidens38
[Silt | Sand]Sedimentation 2-point No peroxideLaser 0 min **** 46
[Silt | Sand]Sedimentation 2-point No peroxideLaser 2 min * 106
[Silt | Sand]Sedimentation 2-point No peroxideSedimentation multi-point No peroxide ** 763
[Silt | Sand]Sedimentation 2-point No peroxideSedimentation multi-point peroxide * 206
SandSedimentation 2-point No peroxideSieving * 746
SandSedimentation 2-point peroxideSievingns26
SandLaser 0 minSieving **** 34
SandLaser 2 minSieving * 77
SandSedimentation multi-point No peroxideSievingns358
SandSedimentation multi-point peroxideSieving **** 84

ns: non-significant (> 0.05),

*: significant at p ≤ 0.05,

**: significant at p ≤ 0.01,

***: significant at p ≤ 0.005,

****: significant at p ≤ 0.001,

N: Sample size.

ns: non-significant (> 0.05), *: significant at p ≤ 0.05, **: significant at p ≤ 0.01, ***: significant at p ≤ 0.005, ****: significant at p ≤ 0.001, N: Sample size.
  1 in total

1.  Determining soil particle-size distribution from infrared spectra using machine learning predictions: Methodology and modeling.

Authors:  Elizabeth Jeanne Parent; Serge-Étienne Parent; Léon Etienne Parent
Journal:  PLoS One       Date:  2021-07-20       Impact factor: 3.752

  1 in total

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