Gold-Assisted Molecular Imaging of Organic Tissue by MeV Secondary Ion Mass Spectrometry.

The quality of molecular imaging by means of MeV primary ion-induced secondary ion mass spectrometry by coating with gold was evaluated on different reference organic molecules and plant samples. The enhancement of the secondary ion yield was evident for the majority of the studied analytes, reaching the highest values at gold thicknesses between 0.5 and 2 nm, and increased the intensity up to 5-fold for reference samples and >2-fold for specific peaks within the plant sample. Improved propagation of the electric field due to the target potential on otherwise electrically insulating plant samples was also evident through improved image resolution and by reducing the background in mass spectra. However, detection of several molecules was significantly decreased at even at 1 nm thick gold layer. The results indicated that an optimized sequence of analysis is required to reliably interpret results.

Legume Fingerprinting through Lipid Composition: Utilizing GC/MS with Multivariate Statistics.

This study presents a tentative analysis of the lipid composition of 47 legume samples, encompassing species such as Phaseolus spp., Vicia spp., Pisum spp., and Lathyrus spp. Lipid extraction and GC/MS (gas chromatography with mass spectrometric detection) analysis were conducted, followed by multivariate statistical methods for data interpretation. Hierarchical Cluster Analysis (HCA) revealed two major clusters, distinguishing beans and snap beans (Phaseolus spp.) from faba beans (Vicia faba), peas (Pisum sativum), and grass peas (Lathyrus sativus). Principal Component Analysis (PCA) yielded 2D and 3D score plots, effectively discriminating legume species. Linear Discriminant Analysis (LDA) achieved a 100% accurate classification of the training set and a 90% accuracy of the test set. The lipid-based fingerprinting elucidated compounds crucial for discrimination. Both PCA and LDA biplots highlighted squalene and fatty acid methyl esters (FAMEs) of 9,12,15-octadecatrienoic acid (C18:3) and 5,11,14,17-eicosatetraenoic acid (C20:4) as influential in the clustering of beans and snap beans. Unique compounds, including 13-docosenoic acid (C22:1) and γ-tocopherol, O-methyl-, characterized grass pea samples. Faba bean samples were discriminated by FAMEs of heneicosanoic acid (C21:0) and oxiraneoctanoic acid, 3-octyl- (C18-ox). However, C18-ox was also found in pea samples, but in significantly lower amounts. This research demonstrates the efficacy of lipid analysis coupled with multivariate statistics for accurate differentiation and classification of legumes, according to their botanical origins.