ToF-SIMS data analysis for complex plant tissue samples using multivariate analysis and G-SIMS

Recently, controlled production of plants to enhance specific ingredients, such as sinigrin in Wasabi effective for antibacterial and anticancer, in the plants has become more important in order to use the ingredients efficiently. It is, however, difficult to develop a plant production method for controlling the sinigrin amount, because the sinigrin production mechanism is not clear. Therefore, it is crucial to evaluate distribution and metabolic pathways of sinigrin and related molecules in the wasabi tissue. Because time-of-flight (ToF)-SIMS provides molecular distributions of insulation samples including plant tissues on a submicron scale, it is useful for such a purpose. On the other hand, interpretation of intricate ToF-SIMS spectra of complex samples is often difficult. Recently, multivariate analysis techniques, such as principal component analysis and multivariate curve resolution, successfully applied into a variety of scientific fields have been also introduced into ToF-SIMS data. Moreover, gentle secondary ion mass spectrometry (G-SIMS), developed for analyzing static-SIMS spectra in terms of the degree of fragmentation, has recently been applied to various samples. In this study, sections of Wasabi petioles were evaluated with ToF-SIMS and the data analysis techniques to clarify the distribution of sinigrin molecule in the wasabi tissue. A combination of multivariate analysis and G-SIMS worked effectively to interpret the complex ToF-SIMS data of the plant tissue. As a result, the detailed distribution of sinigrin in the plant tissue was indicated by ToF-SIMS and the data analysis techniques. Copyright (c) 2014 John Wiley & Sons, Ltd.