Cognitive chaos on spectrofluorometric data to quantitatively unmask adulterations of a PDO vinegar. (February 2020)

• Record Type: Journal Article
• Authors: Lastra-Mejías, Miguel; González-Flores, Ester; Izquierdo, Manuel; Cancilla, John C.; Torrecilla, José S.
• Is Part Of: Food control. Volume 108(2020)
• Publication Date: 2020-02
• Subjects: Adulteration -- Vinegar -- Chaotic algorithms -- Artificial neural networks -- Protected designation of origin; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2019.106860
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Different types of intelligent chaotic algorithms have been used for the determination and quantification of adulterants in Sherry vinegar. The product analyzed is one of the most exclusive and high-priced vinegars in the world, with protected designation of origin "Manzanilla-Sanlúcar de Barrameda", from the Spanish province of Cádiz. It is produced and stored following classic procedures that allow the consumer to enjoy the typical outstanding organoleptic characteristics of this vinegar. Derived from its prestige and price, a spectroscopic tool based on fluorescence has been designed to locate several adulterations including cheap and low-quality vinegars such as those obtained from molasses, rice, cider, and white wine (adulteration range from 1 to 15% in weight). For this purpose, 192 fluorescence spectra from different vinegar samples obtained after irradiating with a laser diode have been analyzed mathematically. The goals established have been to determine the specific type of adulteration as well as their amounts in the prepared mixtures. Among the most outstanding results, it is worth mentioning that the intelligent models can quantify any of the adulterations with relative errors ranging from 1.4 to 7.2%. Highlights: Laser diode and intelligent modeling to verify safe PDO Sherry vinegar. Emission spectroscopy combined with chaotic parameters to locate adulterations. Neural networks with chaotic inputs lead to accurate adulteration quantifiers. Dual validation ensures generalization capability of cognitive tools. MAPEs below 4% for adulterant concentrations ranging from 1 to 15%.