AOAC 133rd Annual Meeting - Final Program

Poster Abstracts | Monday

P-M-036 Ping Feng , Nestlé, Shanghai, China; Tie Gao , Hongxu Chen , SCIEX, Beijing, China; Ruyun Du , Shanghai Institute of Quality Inspection and Technical Research, Shanghai, China; Xiaojing Ding , Beijing Center for Disease Control and Prevention, Beijing, China Quantification of A2 Variant and Total β -Casein Content in Cow Milk Based Liquid and Powder Products by Capillary Zone Electrophoresis (CZE) β -casein is one of the major casein proteins in cow milk- based products. There are 13 different variants documented for β -casein in cow milk, among which, A1 and A2 are the major variants. A new capillary zone electrophoresis (CZE) method with UV detection at 214 nm was established for the quantification of A2 variant and total β -casein content in cow milk-based milk products. The separation of β -casein variants was performed on either N-CHO coated or bare capillary. A 4 M urea and hydroxypropyl methylcellulose in a combined citrate and phosphate at pH 2.7 was used as the separation buffer. Good linearity with R 2 values ranging from 0.9968-0.9997 for A2 variant and total β -casein with 6 levels of β -casein refer- ence standard in 4 days were obtained. The intra- and inter-day precision for A2 β -casein and total β -casein determination in two pasteurized milk and two milk powder samples with differ- ent A2 β -casein content were in the ranges of 2.4 to 4.7% and 4.0 to 6.3%; 2.6 to 4.8% and 3.9 to 6.7%, respectively. A2 β -casein variant and the total β -casein protein contents in bovine milk products including liquid and powder could be accurately analyzed by the newly established CZE method. The analytical results for total β -casein content in the milk products are compa- rable with predicted values calculated based on the literature. Presenter: Ping Feng, Nestlé, Shanghai, China, Email: ping.feng@wyethnutrition.com

carbohydrates, in which the fructose and glucose are the major components. The rest of carbohydrates include dozens of di- and trisaccharides. The sugar profile or fingerprint in honey could be used for the determination of type and origin of honey, as well as the detection of adulteration. HPLC techniques, such as HILIC and HPAEC, are commonly used for the sugar analysis. Recently, a new HILIC-MS method based on Waters BEH Amide column has been developed for the sugar analysis in foods. It has improved separation resolution for sugars, such as a base- line separation of galactose and glucose, and high detection sensitivity. Here we extend this HILIC-MS approach to honey samples. The HILIC-MS method has been optimized for the profiling of the sugars in honey modified, and honey and syrup samples have been tested using this method. Presenter: Jinchuan Yang, Waters Corp., Milford, MA, USA, Email: Jinchuan_yang@waters.com P-M-035 Elisa Robotti , Elettra Barberis , Marcello Manfredi , Emilio Marengo , Università del Piemonte Orientale, Alessandria, Italy; Paola Brizio , Stefania Squadrone , Caterina Stella , Sabina Pederiva , Martino Mantia , Angelo Ferrari , Maria Cesarina Abete , Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, CReAA, National Reference Centre for the Surveillance and Monitoring of Animal Feed, Turin, Italy Chemical Characterization of Cuneo PGI Red Apples and Multivariate Statistics for Authentication Purposes The presence of PGI, PDO, CDO labelled products and food- stuffs is very important for the economic development of a Country. The value of foodstuffs can be improved by traceabil- ity and authentication studies aimed to link a product to the geographical area from which it originated (traceability) or characterize a product with respect to similar ones belong- ing to a different area or produced by different procedures (authentication). Traceability usually exploits the elemental profile while authentication can be performed exploiting different chemical characterization techniques. In this work we focused on Cuneo PGI red apples, a product typical of the North West of Italy, consisting in 4 different red apple cultivars (Gala, Red Delicious, Braeburn and Fuji) produced in a quite spread area in Piedmont. We studied the two most widespread cultivars (Gala and Red Delicious) from different years of production and exploring three different sub-areas within the Cuneo PGI area, by the elemental profile (ICP-MS) and the profile of small molecules (by extraction followed by GC X GC-MS). The data were then treated by means of multivariate statistical tools, i.e. pattern recognition (Principal Component Analysis, Kohonen Self Organizing Maps etc), and classification methods (SIMCA, PLS-DA etc.), to identify traceability and/or authentication models and provide infor- mation about the eventual grouping of the samples in the area under investigation due to geographical reasons. Presenter: Sabina Pederiva, Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d’Aosta, CReAA, National Reference Centre for the Surveillance and Monitoring of Animal Feed, Turin, Italy, Email: sabina.pederiva@izsto.it

44 SEPTEMBER 6–12, 2019 SHERATON DENVER DOWNTOWN HOTEL