The increasing demand for reliable traceability tools in the meat supply chain has prompted the exploration of innovative approaches that meet stringent quality standards. In this work, 57 elements were quantified by inductively coupled plasma mass spectrometry and direct mercury analysis in 80 muscle and 80 liver samples of Italian heavy pigs to investigate the potential of new tools based on multi-elemental profiles in supporting value-added meat supply chains. Samples from three groups of animals belonging to the protected designation of origin (PDO) Parma Ham circuit (conventionally raised; raised with genetically modified organism (GMO)-free feeds; raised with GMO-free feeds plus the supplementation of omega-3 polyunsaturated fatty acids (n-3 PUFA)) and a fourth group of samples from animals not compliant with the PDO Parma Ham production process were analyzed. Hierarchical cluster analysis allowed for the identification of three macro-clusters of liver or muscle samples, highlighting some inhomogeneities among the target groups. Following SIMCA analysis, better classification models were obtained by using liver elemental profiles (95% correct classification rate), with the highest classification accuracy observed for GMO-free livers (100%). The elements contributing the most to the separation of livers by class membership were La, Ce, and Pb for conventional, Li, Cr, Fe, As, and Sr for GMO-free + n-3 PUFA, and Lu for non-PDO samples. Given these findings, the analysis of the elemental profiles of pig tissues can be regarded as a promising method to confirm the declared pig meat label attributes, deter potential complex fraud, and support meat traceability systems.

Elemental profiles of swine tissues as descriptors for the traceability of value-added Italian heavy pig production chains / Varrà, Maria Olga; Husáková, Lenka; Zanardi, Emanuela; Alborali, Giovanni Loris; Patočka, Jan; Ianieri, Adriana; Ghidini, Sergio. - In: MEAT SCIENCE. - ISSN 0309-1740. - 204:(2023). [10.1016/j.meatsci.2023.109285]

Elemental profiles of swine tissues as descriptors for the traceability of value-added Italian heavy pig production chains

Varrà, Maria Olga;Zanardi, Emanuela
;
Ianieri, Adriana;Ghidini, Sergio
2023-01-01

Abstract

The increasing demand for reliable traceability tools in the meat supply chain has prompted the exploration of innovative approaches that meet stringent quality standards. In this work, 57 elements were quantified by inductively coupled plasma mass spectrometry and direct mercury analysis in 80 muscle and 80 liver samples of Italian heavy pigs to investigate the potential of new tools based on multi-elemental profiles in supporting value-added meat supply chains. Samples from three groups of animals belonging to the protected designation of origin (PDO) Parma Ham circuit (conventionally raised; raised with genetically modified organism (GMO)-free feeds; raised with GMO-free feeds plus the supplementation of omega-3 polyunsaturated fatty acids (n-3 PUFA)) and a fourth group of samples from animals not compliant with the PDO Parma Ham production process were analyzed. Hierarchical cluster analysis allowed for the identification of three macro-clusters of liver or muscle samples, highlighting some inhomogeneities among the target groups. Following SIMCA analysis, better classification models were obtained by using liver elemental profiles (95% correct classification rate), with the highest classification accuracy observed for GMO-free livers (100%). The elements contributing the most to the separation of livers by class membership were La, Ce, and Pb for conventional, Li, Cr, Fe, As, and Sr for GMO-free + n-3 PUFA, and Lu for non-PDO samples. Given these findings, the analysis of the elemental profiles of pig tissues can be regarded as a promising method to confirm the declared pig meat label attributes, deter potential complex fraud, and support meat traceability systems.
2023
Elemental profiles of swine tissues as descriptors for the traceability of value-added Italian heavy pig production chains / Varrà, Maria Olga; Husáková, Lenka; Zanardi, Emanuela; Alborali, Giovanni Loris; Patočka, Jan; Ianieri, Adriana; Ghidini, Sergio. - In: MEAT SCIENCE. - ISSN 0309-1740. - 204:(2023). [10.1016/j.meatsci.2023.109285]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2955012
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