Aroma Quality Differentiation of Pyrazine Derivatives Using Self-Organizing Molecular Field Analysis and Artificial Neural Network

Abstract

The encoding of various aroma impressions and the distinction between different aroma qualities are unsolved problems, as differences between aroma impressions can be described only in a qualitative but not in a quantitative manner. As a consequence, classifications of various aroma qualities cannot easily be performed by standard QSAR methods. To find a proper way to encode aroma impressions for SAR studies, a total of 50 pyrazine-based aroma compounds showing the aroma quality of earthy, green-earthy, or green are analyzed. Special attention is thereby turned on the mixed aroma impression green-earthy. Classifications on the whole data set as well as on smaller subsets are calculated using self-organizing molecular field analysis (SOMFA) and artificial neural networks (ANNs). SOMFA classifies between two or three aroma impressions, leading to models satisfying in predictive power. ANN analysis using multilayer perceptron network architecture with one hidden layer and nominal output as well as genetic regression neural network) with two hidden layers and numerical output both lead to a rather good performance rate of 94%.

Multivariate statistical analysis of a large odorants database aimed at revealing similarities and links between odorants and odors

“…Nevertheless, several structure‐odor relationships have been successfully established, e.g., for rigid odorants, either to discriminate hedonic qualities or to characterize the odor similarity of odorant mixtures . A crucial point is that the use of sophisticated molecular descriptors is necessary to develop a metric for odorants …”

Influence of microwave heating time on the structure and properties of chitosan films

“…These molecules consisted of a heterocyclic aromatic organic compound with one or several nitrogen atoms in different positions on the aromatic ring. These compounds were strongly correlated with the occurrence of the Maillard reaction and were responsible for aroma development in processed food . To allow the Maillard reaction, three elements were needed: amine, reductor sugar, and heat.…”

“…These compounds were strongly correlated with the occurrence of the Maillard reaction and were responsible for aroma development in processed food. 48 To allow the Maillard reaction, three elements were needed: amine, reductor sugar, and heat. A Fehling liquor test was performed to confirm the presence of the reductor sugars; amines were present because of the chitosan structure itself, and the films reached 100-110 C during the microwave heating time.…”

Quantitative Structure Property Relations (QSPR) for Predicting Molar Diamagnetic Susceptibilities, χm, of Inorganic Compounds

“…The most common tasks approached by the use of neural networks are modeling and classification problems. Numerous application areas to chemistry [47][48][49][50][51][52][53][54][55][56][57][58][59][60] include QSAR/QSPR studies, spectroscopy (IR, NMR, and UV spectra), protein folding, process control in chemical industry, etc.…”