188
K. M. Sørensen et al.
22. T. Fearn, Multivariate Curve Resolution. NIR News 22(1), 18 (2011)
23. L. Nørgaard, M. Hahn, L.B. Knudsen, I.A. Farhat, S.B. Engelsen, Multivariate near-infrared and
Raman spectroscopic quantifications of the crystallinity of lactose in whey permeate powder.
Int. Dairy J. 15(12), 1261 (2005)
24. S. Navea, A. de Juan, R. Tauler, Modeling temperature-dependent protein structural transitions
by combined near-IR and mid-IR spectroscopies and multivariate curve resolution. Anal. Chem.
75(20), 5592 (2003)
25. K. Wojcicki, I. Khmelinskii, M. Sikorski, E. Sikorska, Near and mid infrared spectroscopy and
multivariate data analysis in studies of oxidation of edible oils. Food Chem. 187, 416 (2015)
26. K.M. Sørensen, S.B. Engelsen, The spatial composition of porcine adipose tissue investigated
by multivariate curve resolution of near infrared spectra: Relationships between fat, the degree
of unsaturation and water. J. Near Infrared Spectrosc. 25(1), 45 (2017)
27. T.R.M. De Beer, P. Vercruysse, A. Burggraeve, T. Quinten, J. Ouyang, X. Zhang, C. Vervaet, J.P.
Remon, W.R.G. Baeyens, In-line and real-time process monitoring of a freeze drying process
using Raman and NIR spectroscopy as complementary Process Analytical Technology (PAT)
tools. J. Pharm. Sci. 98(9), 3430 (2009)
28. J. Jaumot, A. de Juan, R. Tauler, MCR-ALS GUI 2.0: New features and applications.
Chemometr. Intell. Lab. Syst. 140, 1–12 (2014)
29. K. Pearson, On lines and planes of closest fit to systems of points in space. Phil. Mag. 2, 559
(1901)
30. H. Hotelling, Analysis of a complex of statistical variables into principal components. J. Educ.
Psychol. 24, 417 (1933)
31. S. Wold, K. Esbensen, P. Geladi, Principal component analysis. Chemometr. Intell. Lab. Syst.
2(1–3), 37 (1987)
32. S. Wold, H. Martens, H. Wold, The multivariate calibration-problem in chemistry solved by
the PLS method. Lect. Notes Math. 973, 286 (1983)
33. H. Hotelling, The relations of the newer multivariate statistical-methods to factor-analysis. Br.
J. Stat. Psychol. 10(2), 69 (1957)
34. H. Martens, S.A. Jensen, in Progress in Cereal Chemistry and Technology ed. by J. Holas, J.
Kratochvil, vol. 5a (Elsevier, Amsterdam, 1983)
35. A. Smilde, R. Bro, P. Geladi, Multi-Way Analysis with Applications in the Chemical Sciences
(John Wiley & Sons, Ltd, 2005)
36. H. Martens, T. Karstang, T. Næs, Improved selectivity in spectroscopy by multivariate
calibration. J. Chemom. 1(4), 201 (1987)
37. L. Ståhle, S. Wold, Partial least squares analysis with cross-validation for the two-class problem:
A Monte Carlo study. J Chemometrics 1 185 (1987)
38. J.A. Westerhuis, H.C.J. Hoefsloot, S. Smit, D.J. Vis, A.K. Smilde, E.J.J. van Velzen, J.P.M. van
Duijnhoven, F.A. van Dorsten, Assessment of PLSDA cross validation. Metabolomics 4(1), 81
(2008)
39. D.T. Berhe, C.E. Eskildsen, R. Lametsch, M.S. Hviid, F. van den Berg, S.B. Engelsen, Prediction of total fatty acid parameters and individual fatty acids in pork backfat using Raman spectroscopy and chemometrics: Understanding the cage of covariance between highly correlated
fat parameters. Meat Sci. 111, 18 (2016)
40. F.J. Anscombe, Graphs in statistical-analysis. Am. Stat. 27(1), 17 (1973)
41. T. Næs, T. Isaksson, SEP or RMSEP, which is best? NIR News 2(4), 16 (1991)
42. I.N. Wakeling, J.J. Morris, A test of significance for partial least squares regression. J. Chemom.
7(4), 291 (1993)
43. S. Wold, Cross-validatory estimation of the number of components in factor and principal
components models. Technometrics 20(4), 397 (1978)
44. H. Martens, P. Dardenne, Validation and verification of regression in small data sets.
Chemometr. Intell. Lab. Syst. 44(1–2), 99 (1998)
45. D.K. Pedersen, H. Martens, J.P. Nielsen, S.B. Engelsen, Near-infrared absorption and scattering separated by extended inverted signal correction (EISC): Analysis of near-infrared
transmittance spectra of single wheat seeds. Appl. Spectrosc. 56(9), 1206 (2002)
K. M. Sørensen et al.
22. T. Fearn, Multivariate Curve Resolution. NIR News 22(1), 18 (2011)
23. L. Nørgaard, M. Hahn, L.B. Knudsen, I.A. Farhat, S.B. Engelsen, Multivariate near-infrared and
Raman spectroscopic quantifications of the crystallinity of lactose in whey permeate powder.
Int. Dairy J. 15(12), 1261 (2005)
24. S. Navea, A. de Juan, R. Tauler, Modeling temperature-dependent protein structural transitions
by combined near-IR and mid-IR spectroscopies and multivariate curve resolution. Anal. Chem.
75(20), 5592 (2003)
25. K. Wojcicki, I. Khmelinskii, M. Sikorski, E. Sikorska, Near and mid infrared spectroscopy and
multivariate data analysis in studies of oxidation of edible oils. Food Chem. 187, 416 (2015)
26. K.M. Sørensen, S.B. Engelsen, The spatial composition of porcine adipose tissue investigated
by multivariate curve resolution of near infrared spectra: Relationships between fat, the degree
of unsaturation and water. J. Near Infrared Spectrosc. 25(1), 45 (2017)
27. T.R.M. De Beer, P. Vercruysse, A. Burggraeve, T. Quinten, J. Ouyang, X. Zhang, C. Vervaet, J.P.
Remon, W.R.G. Baeyens, In-line and real-time process monitoring of a freeze drying process
using Raman and NIR spectroscopy as complementary Process Analytical Technology (PAT)
tools. J. Pharm. Sci. 98(9), 3430 (2009)
28. J. Jaumot, A. de Juan, R. Tauler, MCR-ALS GUI 2.0: New features and applications.
Chemometr. Intell. Lab. Syst. 140, 1–12 (2014)
29. K. Pearson, On lines and planes of closest fit to systems of points in space. Phil. Mag. 2, 559
(1901)
30. H. Hotelling, Analysis of a complex of statistical variables into principal components. J. Educ.
Psychol. 24, 417 (1933)
31. S. Wold, K. Esbensen, P. Geladi, Principal component analysis. Chemometr. Intell. Lab. Syst.
2(1–3), 37 (1987)
32. S. Wold, H. Martens, H. Wold, The multivariate calibration-problem in chemistry solved by
the PLS method. Lect. Notes Math. 973, 286 (1983)
33. H. Hotelling, The relations of the newer multivariate statistical-methods to factor-analysis. Br.
J. Stat. Psychol. 10(2), 69 (1957)
34. H. Martens, S.A. Jensen, in Progress in Cereal Chemistry and Technology ed. by J. Holas, J.
Kratochvil, vol. 5a (Elsevier, Amsterdam, 1983)
35. A. Smilde, R. Bro, P. Geladi, Multi-Way Analysis with Applications in the Chemical Sciences
(John Wiley & Sons, Ltd, 2005)
36. H. Martens, T. Karstang, T. Næs, Improved selectivity in spectroscopy by multivariate
calibration. J. Chemom. 1(4), 201 (1987)
37. L. Ståhle, S. Wold, Partial least squares analysis with cross-validation for the two-class problem:
A Monte Carlo study. J Chemometrics 1 185 (1987)
38. J.A. Westerhuis, H.C.J. Hoefsloot, S. Smit, D.J. Vis, A.K. Smilde, E.J.J. van Velzen, J.P.M. van
Duijnhoven, F.A. van Dorsten, Assessment of PLSDA cross validation. Metabolomics 4(1), 81
(2008)
39. D.T. Berhe, C.E. Eskildsen, R. Lametsch, M.S. Hviid, F. van den Berg, S.B. Engelsen, Prediction of total fatty acid parameters and individual fatty acids in pork backfat using Raman spectroscopy and chemometrics: Understanding the cage of covariance between highly correlated
fat parameters. Meat Sci. 111, 18 (2016)
40. F.J. Anscombe, Graphs in statistical-analysis. Am. Stat. 27(1), 17 (1973)
41. T. Næs, T. Isaksson, SEP or RMSEP, which is best? NIR News 2(4), 16 (1991)
42. I.N. Wakeling, J.J. Morris, A test of significance for partial least squares regression. J. Chemom.
7(4), 291 (1993)
43. S. Wold, Cross-validatory estimation of the number of components in factor and principal
components models. Technometrics 20(4), 397 (1978)
44. H. Martens, P. Dardenne, Validation and verification of regression in small data sets.
Chemometr. Intell. Lab. Syst. 44(1–2), 99 (1998)
45. D.K. Pedersen, H. Martens, J.P. Nielsen, S.B. Engelsen, Near-infrared absorption and scattering separated by extended inverted signal correction (EISC): Analysis of near-infrared
transmittance spectra of single wheat seeds. Appl. Spectrosc. 56(9), 1206 (2002)