Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools

Abstract

Argentina is a beekeeping country and one of the drawbacks is the exposure of the hives to pollutants. Therefore, the aim of this Thesis is the development of an electroanalytical methods to evaluate the hygienic-sanitary quality of bee products of Buenos Aires province. The following works were performed: ➢ A "lab-made" solid bismuth electrode was designed for cadmium determination in corbicular pollen and raw propolis samples. For this proposed, Square Wave Anodic Stripping Voltammetry was used as electroanalytical technique. ➢ An "in-situ" antimony film electrode was developed for tetracyclines residues determination in honey samples, using Square Wave Cathodic Stripping Voltammetry. ➢ The use of an electrochemically activated glassy carbon electrode and Square Wave Adsorptive Stripping Voltammetry was implemented for the amitraz determination from its final metabolite, 2,4 dimethylaniline, in honey samples. The proposed methods are simple, fast, low cost and may be a good alternative for the determination of these analytes in bee products. Furthermore, the results obtained were satisfactorily validated using recovery study. Certifico que fueron incluidos los cambios y correcciones sugeridas por los jurados

Chemometrics‐assisted color histogram‐based analytical systems

“…Moreover, a 91.9% accuracy rate was achieved for the classification of the aged cachaças into nonadulterated and adulterated samples and a 100% classification accuracy to identify wood types alone using blue histogram. Fernandes et al 15 identified adulterations in chicken hamburgers with a fat content higher than 20% (w/w), as limited by Argentinean legislation. SPA-LDA coupled with grayscale + HSI histogram attained the most satisfactory result with correct classifications of 92.0% and 95.8%, sensitivities of 94.1% and 90.0% and specificities of 90.9% and 100% for both training and test sets, respectively.…”

“…Similar to what happens in applications involving classification, the main publications that use multivariate calibration in CACHAS has been directed mostly to food analysis. 15,30,31,[43][44][45]55,56,58 In addition, applications in agricultural, 46,49 microbiological 53 biological, 54 drug, 18 biofuel, 57 and mineral insulating oil 59 analyses have also been carried out. Here, although most of the studies do not also employ sample pretreatment, solvents, or reagents, the calibration models are dependent on the values obtained by reference methods or similar accurate measurements of the target property/analyte.…”

“…For this, a suitable image capturing system must be rigorously designed to maintain fixed positioning, luminosity, focus, and sample‐to‐camera distance 3,5,25 . As a consequence, the color histograms obtained from the recorded digital images are resistant to position and orientation changes and, therefore, avoids image preprocessing/correction employing further mathematical operations (such as noise reduction, gray level correction, and blurring correction) to enhance the quality of the image and/or remove defects 14,15 …”

“…The use of white light enables the differentiation between different tones, hues, and shades when histograms are constructed from a digital image. Common sources include fluorescent lamps (either external or internal to a scanner 15,21,25,28,32,[34][35][36][37][38][39][42][43][44]46,48,49,[54][55][56][57] ) and white-light LED (light-emitting diode) lamps 26,27,30,33,40,41,45,47,58,59 or LED strips, 17,31,50 and they must be suitably disposed in the system in order to avoid shadows and illumination gradients under the ROI. Ultraviolet (UV) lamps, 18,51 near infrared (NIR) LEDs, 29 internal flash lamp, 52,61 white-light-transilluminator, 53 and luminoscope 60 have been also used.…”

“…3 An image capturing device to register the images of the chemical system under consideration. Simple commercial devices include digital cameras, 15,25,30,41,45,52,53,59,60 scanners, 21,28,34,35,39,43,46,[54][55][56][57]61 webcams, 26,29,32,33,[36][37][38]40,42,44,[47][48][49] and smartphones, 17,18,27,31,50,51,58 and the choice of one of them shall be according to its availability in each laboratory or specific need for a given application. However, it is important to note that the portability of systems through the use of smartphones has become a remarkable trend in the literature, mainly in applications involving univariate calibration for colorimetric analysis.…”