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    Detection of minced beef adulteration with turkey meat by UV-vis, NIR and MIR spectroscopy

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    The aim of this work was to investigate the potential of UV-visible (UV-vis), near infrared (NIR) and mid infrared (MIR) spectroscopy, coupled with chemometric techniques, to detect minced beef adulteration with turkey meat. Besides 44 minced meat samples of pure bovine and 44 of pure turkey, 154 mixtures of minced beef adulterated with turkey meat in the range 5-50% (w/w) were prepared and analyzed. The spectral data, standardized by different pre-treatments, were processed, separately or fused, using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Partial Least Squares (PLS) regression. Moreover, a variable selection method was performed before classification and regression analysis. Among the three spectroscopic techniques, comparing the PLS models in terms of errors in prediction (RMSEP), the best results were obtained with NIR and MIR spectroscopy, whereas the UV-vis results were less satisfactory. Finally, combining information from UV-vis, NIR and MIR spectroscopy improved the overall results

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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