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小麦品种分类:对于无法通过基质辅助激光解吸/电离飞行时间质谱和人工神经网络进行分类的品种,采用二维凝胶电泳法。

Classification of wheat varieties: use of two-dimensional gel electrophoresis for varieties that can not be classified by matrix assisted laser desorpiton/ionization-time of flight-mass spectrometry and an artificial neural network.

作者信息

Jacobsen S, Nesić L, Petersen M, Søndergaard I

机构信息

BioCentrum-DTU, Biochemistry and Nutrition, Søltofts Plads, Technical University of Denmark, Lyngby.

出版信息

Electrophoresis. 2001 Apr;22(6):1242-5. doi: 10.1002/1522-2683()22:6<1242::AID-ELPS1242>3.0.CO;2-Q.

Abstract

Analyzing a gliadin extract by matrix assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) combined with an artificial neural network (ANN) is a suitable method for identification of wheat varieties. However, the ANN can not distinguish between all different wheat varieties. Two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) was applied to three pairs of wheat varieties, which can not be classified correctly by ANN. By 2-D PAGE the varieties in the three pairs can be discriminated and these six wheat varieties can be separated from each other, which could not be separated by MALDI-TOF-MS and NN.

摘要

通过基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF-MS)结合人工神经网络(ANN)分析麦醇溶蛋白提取物是鉴定小麦品种的一种合适方法。然而,人工神经网络无法区分所有不同的小麦品种。二维聚丙烯酰胺凝胶电泳(2-D PAGE)应用于三对不能被人工神经网络正确分类的小麦品种。通过二维聚丙烯酰胺凝胶电泳,可以区分这三对中的品种,并且这六个小麦品种可以彼此分离,而这是基质辅助激光解吸/电离飞行时间质谱和神经网络无法做到的。

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