Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis

Publication: Research - peer-review › Journal article – Annual report year: 2001

Standard

Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis. / Sørensen, Helle Aagaard ; Sperotto, Maria Maddalena; Petersen, M.; Kesmir, Can ; Radzikowski, Louise ; Jacobsen, Susanne ; Søndergaard, Ib.

In: Rapid communications in mass spectrometry, Vol. 16, No. 12, 2002, p. 1232-1237.

Publication: Research - peer-review › Journal article – Annual report year: 2001

In: Rapid communications in mass spectrometry, Vol. 16, No. 12, 2002, p. 1232-1237.

Publication: Research - peer-review › Journal article – Annual report year: 2001

Bibtex

@article{2e8a7a683348475dafa3c92b3aac1c36,

title = "Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis",

publisher = "John/Wiley & Sons Ltd.",

author = "Sørensen, {Helle Aagaard} and Sperotto, {Maria Maddalena} and M. Petersen and Can Kesmir and Louise Radzikowski and Susanne Jacobsen and Ib Søndergaard",

year = "2002",

volume = "16",

number = "12",

pages = "1232--1237",

journal = "Rapid communications in mass spectrometry",

issn = "0951-4198",

}

RIS

TY - JOUR

T1 - Variety identification of wheat using mass spectrometry with neural networks and the influence of mass spectra processing prior to neural network analysis

A1 - Sørensen,Helle Aagaard

A1 - Sperotto,Maria Maddalena

A1 - Petersen,M.

A1 - Kesmir,Can

A1 - Radzikowski,Louise

A1 - Jacobsen,Susanne

A1 - Søndergaard,Ib

AU - Sørensen,Helle Aagaard

AU - Sperotto,Maria Maddalena

AU - Petersen,M.

AU - Kesmir,Can

AU - Radzikowski,Louise

AU - Jacobsen,Susanne

AU - Søndergaard,Ib

PB - John/Wiley & Sons Ltd.

PY - 2002

Y1 - 2002

N2 - The performance of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks in wheat variety classification is further evaluated.(1) Two principal issues were studied: (a) the number of varieties that could be classified correctly; and (b) various means of preprocessing mass spectrometric data. The number of wheat varieties tested was increased from 10 to 30. The main pre-processing method investigated was based on Gaussian smoothing of the spectra, but other methods based on normalisation procedures and multiplicative scatter correction of data were also used. With the final method, it was possible to classify 30 wheat varieties with 87% correctly classified mass spectra and a correlation coefficient of 0.90.

AB - The performance of matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry with neural networks in wheat variety classification is further evaluated.(1) Two principal issues were studied: (a) the number of varieties that could be classified correctly; and (b) various means of preprocessing mass spectrometric data. The number of wheat varieties tested was increased from 10 to 30. The main pre-processing method investigated was based on Gaussian smoothing of the spectra, but other methods based on normalisation procedures and multiplicative scatter correction of data were also used. With the final method, it was possible to classify 30 wheat varieties with 87% correctly classified mass spectra and a correlation coefficient of 0.90.

U2 - 10.1002/rcm.709

DO - 10.1002/rcm.709

JO - Rapid communications in mass spectrometry

JF - Rapid communications in mass spectrometry

SN - 0951-4198

IS - 12

VL - 16

SP - 1232

EP - 1237

ER -