Application on infrared spectroscopy for the analysis of total phenolic compounds in fruits

Recent studies have demonstrated the metabolic benefits of phenolic compounds on human health. However, traditional analytical methods used for quantification of total phenolic compounds are time-consuming, laborious, require a high volume of reagents, mostly toxic substances, and involve several steps that can result in systematic and instrumental errors. Spectroscopic techniques have been used as alternatives to these methods for the determination of bioactive compounds directly in the food matrix by minimal sample preparation, without using toxic reagents. Therefore, this overview presents the advantages of nondestructive methods focusing on infrared spectroscopy (IR), for the quantification of total phenolic compounds in fruits. In addition, the main difficulties in applying these spectroscopic techniques are presented, as well as a comparison between the quantification of total phenolic compounds by traditional and IR methods. This review concludes by focusing on model building, highlighting that IR data are mainly processed using the partial least-squares (PLS) regression method to predict total phenolic content. The development of portable and inexpensive IR instruments, combined with multivariate data processing, could give to the consumers a straightforward technology to evaluate the total phenolic content of fruits prior to purchase.

Near-infrared hyperspectral imaging (NIR-HSI) and normalized difference image (NDI) data processing: An advanced method to map collagen in archaeological bones

In the present study, an innovative and highly efficient near-infrared hyperspectral imaging (NIR-HSI) method is proposed to provide spectral maps able to reveal collagen distribution in large-size bones, also offering semi-quantitative estimations. A recently introduced method for the construction of chemical maps, based on Normalized Difference Images (NDI), is declined in an innovative approach, through the exploitation of the NDI values computed for each pixel of the hyperspectral image to localize collagen and to extract information on its content by a direct comparison with known reference samples. The developed approach addresses an urgent issue of the analytical chemistry applied to bioarcheology researches, which rely on well-preserved collagen in bones to obtain key information on chronology, paleoecology and taxonomy. Indeed, the high demand for large-sample datasets and the consequent application of a wide variety of destructive analytical methods led to the considerable destruction of precious bone samples. NIR-HSI pre-screening allows researchers to properly select the sampling points for subsequent specific analyses, to minimize costs and time and to preserve integrity of archaeological bones (which are available in a very limited amount), providing further opportunities to understand our past.

Combining spectroscopic techniques and chemometrics for the interpretation of lichen biomonitoring of air pollution

A screening evaluation of lichen thalli, based on spectroscopic techniques coupled with chemometrics, is proposed as fast, simple and "green" method for the biomonitoring of air pollution. For two consecutive years, lichen thalli of Pseudevernia furfuracea were exposed for three months in selected sites of Liguria (NW-Italy) according to different levels and types of air pollution. At the end of the exposure period, transplanted thalli were analyzed by a set of monitoring techniques, including Front-Face Fluorescence Spectroscopy (FFFS), Near Infrared Spectroscopy (NIRS) and Plant Efficiency Analyser (PEA). Data were compared with values of air pollutants recorded during the exposure period by the Regional Agency for Environmental Protection, in order to relate lichen physiological indicators with the effects of atmospheric concentrations. A chemometric evaluation of the analytical signals, including principal component analysis (PCA) and quadratic discriminant analysis (QDA), was performed; the mean prediction rate of the discriminant models calculated on the FFFS emission spectra ranged from 70 to 75% on the external test sets. Front-face fluorescence spectroscopy proved to be a promising technique for the determination of level and type of pollutants in lichen thalli.