000126890 001__ 126890
000126890 005__ 20241125101156.0
000126890 0247_ $$2doi$$a10.1016/j.foodcont.2023.109868
000126890 0248_ $$2sideral$$a134259
000126890 037__ $$aART-2023-134259
000126890 041__ $$aeng
000126890 100__ $$0(orcid)0000-0001-7719-6388$$aCivera, Alba$$uUniversidad de Zaragoza
000126890 245__ $$aDevelopment and validation of sensitive and rapid immunoassays to detect minute amounts of hazelnut in processed food and working surfaces
000126890 260__ $$c2023
000126890 5060_ $$aAccess copy available to the general public$$fUnrestricted
000126890 5203_ $$aHazelnut (Corylus avellana L.) represents one of the most allergenic nuts and it can be found as a hidden allergen in processed food due to cross contamination. Therefore, sensitive and specific analytical techniques are in high demand to be used in allergen risk management plans at food industry. In this study, sandwich ELISA and Lateral Flow Immunoassay (LFIA) to detect hazelnut have been developed based on the determination of Cor a 9, one of the most abundant and allergenic proteins of hazelnut. Results showed that cross-reactivity was only found with walnut and Pecan nut, which was lower than 0.1%. When analyzing food spiked with a hazelnut extract or blended with hazelnut flour, ELISA and LFIA were able to detect 0.1 ppm and 0.5 ppm of hazelnut protein with a recovery from 82 to 110%. ELISA and LFIA could also detect 0.15 and 0.6 ppm of hazelnut protein in baked cookies incurred with ground hazelnut, respectively. Furthermore, LFIA could detect 1.25 μg of hazelnut protein in working surfaces of stainless steel and melamine. The sandwich ELISA was in-house validated, showing acceptable results of precision. Likewise, ELISA and LFIA showed to be robust tests. The combined use of both assays could improve the allergen risk management plans in food industry to monitor the presence of hazelnut traces in raw ingredients, processed food and working surfaces.
000126890 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FEDER/A02-20R
000126890 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000126890 590__ $$a5.6$$b2023
000126890 592__ $$a1.146$$b2023
000126890 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b24 / 173 = 0.139$$c2023$$dQ1$$eT1
000126890 593__ $$aFood Science$$c2023$$dQ1
000126890 593__ $$aBiotechnology$$c2023$$dQ1
000126890 594__ $$a12.2$$b2023
000126890 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000126890 700__ $$aGalan-Malo, Patricia$$uUniversidad de Zaragoza
000126890 700__ $$aMata, Luis
000126890 700__ $$0(orcid)0000-0002-2646-5733$$aTobajas, Ana P.$$uUniversidad de Zaragoza
000126890 700__ $$0(orcid)0000-0001-5964-823X$$aSánchez, Lourdes$$uUniversidad de Zaragoza
000126890 700__ $$0(orcid)0000-0003-2555-8425$$aPérez, María D.$$uUniversidad de Zaragoza
000126890 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000126890 7102_ $$12008$$2780$$aUniversidad de Zaragoza$$bDpto. Produc.Animal Cienc.Ali.$$cÁrea Tecnología de Alimentos
000126890 773__ $$g152 (2023), 109868 [9 pp.]$$pFood control$$tFood Control$$x0956-7135
000126890 8564_ $$s1098972$$uhttps://zaguan.unizar.es/record/126890/files/texto_completo.pdf$$yVersión publicada
000126890 8564_ $$s2553879$$uhttps://zaguan.unizar.es/record/126890/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000126890 909CO $$ooai:zaguan.unizar.es:126890$$particulos$$pdriver
000126890 951__ $$a2024-11-22-12:09:33
000126890 980__ $$aARTICLE