Mid-infrared spectroscopy and authenticity problems in selected meats:A feasibility study

This paper describes the results of a feasibility study into the use of mid-infrared spectroscopy for addressing certain authenticity problems with selected fresh meats. Preliminary analyses for meat speciation, the detection of 'frozen-thawed' meat, and semi-quantitative analysis of meat mixtures are reported. Fourier transform mid-infrared spectroscopy, attenuated total reflectance sample presentation, principal component analysis and partial least squares regression were used. It was possible to distinguish minced chicken, pork and turkey meats from their infrared spectra, and for each meat species it was possible to differentiate between fresh and frozen-thawed samples. Mid-infrared spectroscopy was also able to semi-quantitatively measure the levels of turkey and pork mixed with chicken meat. The method, which is rapid and easy to use, could with further development have the potential for authentication and quality control of meat products

Evaluation of three field-based methods for quantifying soil carbon

Citation: Izaurralde, Roberto C., Charles W. Rice, Lucian Wielopolski, Michael H. Ebinger, James B. Reeves Iii, Allison M. Thomson, Ronny Harris, et al. “Evaluation of Three Field-Based Methods for Quantifying Soil Carbon.” PLOS ONE 8, no. 1 (January 31, 2013): e55560. https://doi.org/10.1371/journal.pone.0055560.Three advanced technologies to measure soil carbon (C) density (g C mˉ²) are deployed in the field and the results compared against those obtained by the dry combustion (DC) method. The advanced methods are: a) Laser Induced Breakdown Spectroscopy (LIBS), b) Diffuse Reflectance Fourier Transform Infrared Spectroscopy (DRIFTS), and c) Inelastic Neutron Scattering (INS). The measurements and soil samples were acquired at Beltsville, MD, USA and at Centro International para el Mejoramiento del Maı´z y el Trigo (CIMMYT) at El Bata´n, Mexico. At Beltsville, soil samples were extracted at three depth intervals (0–5, 5–15, and 15–30 cm) and processed for analysis in the field with the LIBS and DRIFTS instruments. The INS instrument determined soil C density to a depth of 30 cm via scanning and stationary measurements. Subsequently, soil core samples were analyzed in the laboratory for soil bulk density (kg mˉ³), C concentration (g kgˉ¹) by DC, and results reported as soil C density (kg mˉ²). Results from each technique were derived independently and contributed to a blind test against results from the reference (DC) method. A similar procedure was employed at CIMMYT in Mexico employing but only with the LIBS and DRIFTS instruments. Following conversion to common units, we found that the LIBS, DRIFTS, and INS results can be compared directly with those obtained by the DC method. The first two methods and the standard DC require soil sampling and need soil bulk density information to convert soil C concentrations to soil C densities while the INS method does not require soil sampling. We conclude that, in comparison with the DC method, the three instruments (a) showed acceptable performances although further work is needed to improve calibration techniques and (b) demonstrated their portability and their capacity to perform under field conditions

FTIR Spectroscopy and Multivariate Analysis Can Distinguish the Geographic Origin of Extra Virgin Olive Oils

This work investigates whether Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis, can distinguish extra virgin olive oils from different producing countries. Duplicate spectra were collected from 60 oils from four European countries. Two approaches to data analysis were used as follows:  first, the “whole spectrum” method of partial least squares (PLS) followed by distance-based linear discriminant analysis (LDA) applied to the PLS scores, and second, a genetic algorithm (GA) for variate selection from the raw data, followed by LDA applied to the selected subset. The PLS−LDA approach produced a cross-validation success rate of 96%, whereas the GA−LDA approach achieved a 100% cross-validation success rate, from subsets comprising only eight variates. Neither the selected variate nor the whole spectrum approach was able to offer insight into the origin of the discrimination in biochemical terms. However, FTIR analysis is rapid, and this work shows that it has the required discriminatory power to potentially offer a “black box” method of screening oils to verify their country of origin