Prediction of Secondary Metabolites Content of Laurel (Laurus nobilis L.) with Artificial Neural Networks Based on Different Temperatures and Storage times

Bay laurel leaves, also known as bay are an important herb in many cuisines around the world. In addition to their use cooking, leaves have been used for medicinal properties and thought anti-inflammatory antimicrobial effects. Gas chromatography/mass spectrometry (GC-MS) device was determine secondary metabolites essential oil of samples kept at different temperatures (−22, −20, −18, 2, 4, 6, 22°C) storage times (1, 3 months). this research, temperature (°C) time (month) were input parameters neural network. On other hand, alpha-pinene, beta-pinene, sabinene, 1.8-cineole, gamma-terpinene, cymenol, linalool, borneol, 4-terpineol, caryophyllene, alpha-terpineol, germacrene-D, alpha-selinene, methyl eugenol, caryophyllene oxide, spathulenol, beta-selinenol output parameter. Considering R2 values obtained from artificial network analysis, 0.97156 test, 0.98978 training, 0.98998 validation value, 0.98831 all obtained.