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Accueil > Biblio > Estimation of the minimum detectable value for the determination of PCBs in fatty food samples by GC-ECD: a curvilinear calibration case

Estimation of the minimum detectable value for the determination of PCBs in fatty food samples by GC-ECD: a curvilinear calibration case

Public Access

Published

Peer reviewed scientific article

DOI : http://dx.doi.org/10.1016/S0003-2670(02)01533-7 [1]

Auteurs

Joris Van Loco [2]; V. Hanot [3]; Huysmans,G. [4]; M. Elskens [5]; J-M Degroodt [6]; Beernaert,H. [7]

Mots-clés

  1. alternatives [8]
  2. at [9]
  3. Calibration [10]
  4. Casse [11]
  5. estimation [12]
  6. food [13]
  7. Impact [14]
  8. IS [15]
  9. method [16]
  10. methods [17]
  11. MODEL [18]
  12. models [19]
  13. ON [20]
  14. PCB [21]
  15. Pcbs [22]
  16. RANGE [23]
  17. regression [24]
  18. Regression model [25]
  19. result [26]
  20. résultats [27]
  21. Sample [28]
  22. Samples [29]
  23. Yield [30]

Résumé:

Electron capture detectors (ECDs) are known to have a limited linear calibration range. It was demonstrated that for ECDs, curvilinear calibration models yield more accurate results. To estimate the minimum detectable value (MDV), the ISO 11843-2 procedure was modified for curvilinear calibration graphs. At first, the graphs were linearized. The MDV was assessed with formulas based on the estimation of the MDV in the linear calibration case. Alternatively, the MDV was determined by a method based on confidence intervals for a second-order calibration plot. There was a close correspondence b…
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Résumé

Electron capture detectors (ECDs) are known to have a limited linear calibration range. It was demonstrated that for ECDs, curvilinear calibration models yield more accurate results. To estimate the minimum detectable value (MDV), the ISO 11843-2 procedure was modified for curvilinear calibration graphs. At first, the graphs were linearized. The MDV was assessed with formulas based on the estimation of the MDV in the linear calibration case. Alternatively, the MDV was determined by a method based on confidence intervals for a second-order calibration plot. There was a close correspondence between the MDVs calculated by both methods. Weighted regression models were used to correct heteroscedasticity. It was found that applying weighted regression decreased the MDV with a factor of

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Source URL:https://www.sciensano.be/fr/biblio/estimation-minimum-detectable-value-determination-pcbs-fatty-food-samples-gc-ecd-a-curvilinear

Liens
[1] http://dx.doi.org/10.1016/S0003-2670(02)01533-7 [2] https://www.sciensano.be/fr/people/joris-van-loco/biblio [3] https://www.sciensano.be/fr/biblio?f%5Bauthor%5D=867&f%5Bsearch%5D=V.%20Hanot [4] https://www.sciensano.be/fr/biblio?f%5Bauthor%5D=28767&f%5Bsearch%5D=Huysmans%2CG. [5] https://www.sciensano.be/fr/biblio?f%5Bauthor%5D=25761&f%5Bsearch%5D=M.%20Elskens [6] https://www.sciensano.be/fr/biblio?f%5Bauthor%5D=1392&f%5Bsearch%5D=J-M%20Degroodt [7] https://www.sciensano.be/fr/biblio?f%5Bauthor%5D=24327&f%5Bsearch%5D=Beernaert%2CH. [8] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=5682&f%5Bsearch%5D=alternatives [9] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=534&f%5Bsearch%5D=at [10] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=5322&f%5Bsearch%5D=Calibration [11] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1518&f%5Bsearch%5D=Casse [12] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=5595&f%5Bsearch%5D=estimation [13] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1008&f%5Bsearch%5D=food [14] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=891&f%5Bsearch%5D=Impact [15] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=525&f%5Bsearch%5D=IS [16] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1134&f%5Bsearch%5D=method [17] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1359&f%5Bsearch%5D=methods [18] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=657&f%5Bsearch%5D=MODEL [19] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=3801&f%5Bsearch%5D=models [20] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=912&f%5Bsearch%5D=ON [21] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=17868&f%5Bsearch%5D=PCB [22] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=18405&f%5Bsearch%5D=Pcbs [23] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=3876&f%5Bsearch%5D=RANGE [24] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=3330&f%5Bsearch%5D=regression [25] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=4401&f%5Bsearch%5D=Regression%20model [26] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1098&f%5Bsearch%5D=result [27] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1101&f%5Bsearch%5D=r%C3%A9sultats [28] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1020&f%5Bsearch%5D=Sample [29] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1023&f%5Bsearch%5D=Samples [30] https://www.sciensano.be/fr/biblio?f%5Bkeyword%5D=1536&f%5Bsearch%5D=Yield