Development of carboxylic acid search prefilters for spectral library matching

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• 作者：Barry K. Lavine^a ; ^{bklab@chem.okstate.edu} ; Kadambari Nuguru^a ; Nikhil Mirjankar^a ; Jerome Workman^b ; ^c
• 关键词：Carboxylic acid search prefilters ; Library searching ; Spectral matching ; Spectral pattern recognition
• 刊名：Microchemical Journal
• 出版年：2012
• 期刊代码：64_0026265x
• 类别：ce
• 出版时间：July, 2012
• 卷：103
• 期：Complete
• 页码：21-36
• 文件大小：1194 K

摘要

435 infrared (IR) absorbance spectra of 140 carboxylic acids and 295 noncarboxylic acids which included aldehydes, ketones, esters, amides as well as compounds containing both carbonyls and alcohols were preprocessed using the wavelet packet tree to enhance subtle but important features in the data. Wavelet coefficients that optimized the separation of the spectra by functional group in a plot of the two largest principal components of the data were identified using a genetic algorithm (GA) for pattern recognition analysis. Because principal components maximize variance, the bulk of the information encoded by the wavelet coefficients selected by the pattern recognition GA is characteristic of the carboxylic acid functional group. The carboxylic acid search prefilter developed as part of this study was successfully validated using two external validation sets. The first validation set consisted of 24 carboxylic acids and 61 noncarboxylic acids and the second validation set consisted of 264 carboxylic acids and 72 noncarboxylic acids.