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使用分类与回归树(CART)分析开发单取代苯磺酰胺甜味剂的结构-味觉关系

Development of structure-taste relationships for monosubstituted phenylsulfamate sweeteners using classification and regression tree (CART) analysis.

作者信息

Kelly Damien P, Spillane William J, Newell John

机构信息

Department of Chemistry, National University of Ireland, Galway, Ireland.

出版信息

J Agric Food Chem. 2005 Aug 24;53(17):6750-8. doi: 10.1021/jf0507137.

Abstract

Twenty monosubstituted phenylsulfamates (cyclamates) have been synthesized and have had their taste portfolios determined. These have been combined with 63 compounds already in the literature to give a database of 83 ortho, meta, and para compounds. A training set of 75 compounds was randomly selected leaving eight compounds as a test set. A series of nine predictors determined with Corey-Pauling-Koltun models, calculated from the PC SPARTAN PRO program and Hammett sigma values taken mainly from the literature, have been used to establish structure-taste relationships for these types of sweeteners. The taste panel data for all compounds were categorized into three classes, namely, sweet (S), nonsweet (N), and sweet/nonsweet (N/S), and a novel "sweetness value" or weighting was also calculated for each compound. Linear and quadratic discriminant analysis were first used with the S, N, and N/S data, but the results were somewhat disappointing. Classification and regression tree analysis using the sweetness values for all 75 compounds was more successful, and only 14 were misclassified and six of the eight test set compounds were correctly classified. For the 29 meta compounds, one subset using just two parameters classified 83% of these compounds. Finally, using various methods, predictions were made on the likely tastes of a number of meta compounds and a striking agreement was found between the tree prediction and those given by earlier models. This appears to offer a strong vindication of the tree approach.

摘要

已合成了20种单取代苯磺酸盐(甜蜜素)并测定了它们的味觉特征。这些化合物与文献中已有的63种化合物相结合,形成了一个包含83种邻位、间位和对位化合物的数据库。随机选择75种化合物作为训练集,剩下8种化合物作为测试集。使用由PC SPARTAN PRO程序计算得出的Corey-Pauling-Koltun模型确定的一系列9个预测因子以及主要从文献中获取的哈米特σ值,来建立这类甜味剂的结构-味觉关系。所有化合物的味觉小组数据被分为三类,即甜(S)、非甜(N)和甜/非甜(N/S),并且还为每种化合物计算了一个新的“甜度值”或权重。首先对S、N和N/S数据使用线性和二次判别分析,但结果有些令人失望。使用所有75种化合物的甜度值进行分类和回归树分析更为成功,只有14种被错误分类,8种测试集化合物中有6种被正确分类。对于29种间位化合物,仅使用两个参数的一个子集对其中83%的化合物进行了分类。最后,使用各种方法对一些间位化合物的可能味道进行了预测,发现树预测与早期模型给出的预测之间存在惊人的一致性。这似乎有力地证明了树方法的合理性。

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