Potential of NIR spectroscopy to predict amygdalin content established by HPLC in intact almonds and classification based on almond bitterness

[EN] In this study, 360 intact almonds, half sweet and half bitter, were assessed by near-infrared (NIR) spectroscopy to predict amygdalin content (established by high performance liquid chromatography (HPLC)) and by applying partial least squares (PLS) to the spectral data. After optimising amygdalin extraction and chromatographic conditions, the amygdalin contents found by HPLC were not detected or below to 350 mg kg-1 for sweet almonds, and between 14,700 and 50,400mg kg 1 for bitter almonds. The intact almond spectra resulted in good predictions of amygdalin content with R2p of 0.939 and RMSEP of 0.373. Almonds were correctly classified into sweet and bitter by linear discriminant analysis (LDA), quadratic discriminant analysis (QDA) and PLS-DA, with sensitivity and specificity values higher than 0.94 for evaluation set samples. Based on these results, it can be concluded that NIR spectroscopy is a good non-destructive alternative to be used as an automatic in-line classification system by food industry.Victoria Cortes Lopez thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202). The authors wish to thank the cooperative Agricoop for kindly donating the almonds.Cortes-Lopez, V.; Talens Oliag, P.; Barat Baviera, JM.; Lerma-García, MJ. (2018). Potential of NIR spectroscopy to predict amygdalin content established by HPLC in intact almonds and classification based on almond bitterness. Food Control. 91:68-75. https://doi.org/10.1016/j.foodcont.2018.03.040S68759

Control of undeclared flavoring of cocoa powders by the determination of vanillin and ethyl vanillin by HPLC

[EN] A simple protocol for the extraction of vanillin and ethyl vanillin in cocoa powders, followed by analyte quantification using HPLC, has been proposed in this work. After optimizing both, extraction and separation conditions, both analytes were determined in less than 4 min, with relative standard deviation values lower than 2.05% in all cases. Detection limits within 0.04 and 0.06 mg L 1 were achieved. The applicability of the proposed method was evaluated by performing a recovery study, in which a cocoa sample was fortified with both flavors at different concentration levels. In all cases, the recovery values obtained were comprised between 97.5 and 103.1%. The developed method was also successfully applied to analyze 66 commercially available cocoa powders from different brands and markets finding that the 11% of powders contained vanillin and/or ethyl vanillin in concentration ranges comprised between 5.6 and 90.8, and 5.1 and 12.2 mg/100 g for vanillin and ethyl vanillin, respectively. Finally, during the sensory evaluation of cocoa powders, it was revealed that samples containing vanillin show a very round aromatic profile that is very appreciated by the consumers. Thus, the developed method could be useful to control undeclared flavoring and to guarantee food quality and for protecting good manufacturers. © 2016 Elsevier Ltd. All rights reserved.M.J. Lerma-Garcia thanks the Polytechnic University of Valencia for a postdoctoral contract (PAID-10-14).Pérez-Esteve, É.; Lerma García, MJ.; Fuentes López, A.; Palomares Cano, C.; Barat Baviera, JM. (2016). Control of undeclared flavoring of cocoa powders by the determination of vanillin and ethyl vanillin by HPLC. Food Control. 67:171-176. https://doi.org/10.1016/j.foodcont.2016.02.0481711766

Validation of Thin Layer Chromatographic Methods

Thin-layer and high-performance thin-layer chromatography (TLC/HPTLC) methods for assaying compound(s) in a sample must be validated to ensure that they are fit for their intended purpose and, where applicable, meet the strict regulatory requirements for controlled products. Two validation approaches are identified in the literature, i.e. the classic and the alternative, which is using accuracy profiles.Detailed procedures of the two approaches are discussed based on the validation of methods for pharmaceutical analysis, which is an area considered having more strict requirements. Estimation of the measurement uncertainty from the validation approach using accuracy profiles is also described.Examples of HPTLC methods, developed and validated to assay sulfamethoxazole and trimethoprim on the one hand and lamivudine, stavudine, and nevirapine on the other, in their fixed-dose combination tablets, are further elaborated.Chapter 13SCOPUS: ch.binfo:eu-repo/semantics/publishe