Estimation of doses absorbed by potato tubers under electron beam or X-ray irradiation using an optical fingerprinting strategy

High-energy electron beam and X-ray processing of foods can be used for extending their storage life and for combating pests and pathogens. Several instrumental techniques are used to estimate irradiation doses in foods, but these methods are complex and laborious, require expensive equipment, and do not always allow to determine low doses. This study was aimed at developing simple methods for detecting irradiation in potato tubers and for dose estimation. We used a "fingerprinting" strategy that does not involve quantitation of any compound; instead, the rate of indicator reactions involving carbocyanine dyes is measured. The dye content was monitored by its near-infrared fluorescence intensity and visible-light absorption. Potatoes not subjected to treatment and those irradiated with different doses (10, 100, 1000, 5000, or 10,000 Gray) could be distinguished by linear discriminant analysis. Thus, the order of magnitude of the absorbed dose can be estimated with 89% ± 3% accuracy for a mixture of tubers of two potato varieties irradiated with an electron beam or with 95% ± 8% accuracy for one variety irradiated with an X-ray source.

Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting

In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2'-bipyridyl) dichlororuthenium(II) (Ru(bpy)₃²⁺), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400-600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)₃²⁺ fluorophore.