Fernandes Cristiana L, Carvalho Daniel O, Guido Luis F
REQUIMTE - Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto, Portugal.
Foods. 2019 Nov 20;8(12):597. doi: 10.3390/foods8120597.
Acrylamide (AA), a molecule which potentially increases the risk of developing cancer, is easily formed in food rich in carbohydrates, such as biscuits, wafers, and breakfast cereals, at temperatures above 120 °C. Thus, the need to detect and quantify the AA content in processed foodstuffs is eminent, in order to delineate the limits and mitigation strategies. This work reports the development and validation of a high-resolution mass spectrometry-based methodology for identification and quantification of AA in specific food matrices of biscuits, by using LC-MS with electrospray ionization and Orbitrap as the mass analyser. The developed analytical method showed good repeatability (RSD 11.1%) and 3.55 and 11.8 μg kg as limit of detection (LOD) and limit of quantification (LOQ), respectively. The choice of multiplexed targeted-SIM mode (t-SIM) for AA and AA-d3 isolated ions provided enhanced detection sensitivity, as demonstrated in this work. Statistical processing of data was performed in order to compare the AA levels with several production parameters, such as time/cooking temperature, placement on the cooking conveyor belt, color, and moisture for different biscuits. The composition of the raw materials was statistically the most correlated factor with the AA content when all samples are considered. The statistical treatment presented herein enables an important prediction of factors influencing AA formation in biscuits contributing to putting in place effective mitigation strategies.
丙烯酰胺(AA)是一种可能增加患癌风险的分子,在温度高于120°C时,很容易在富含碳水化合物的食品中形成,如饼干、威化饼和早餐谷物。因此,为了确定限量和缓解策略,检测和量化加工食品中AA含量的需求迫在眉睫。这项工作报告了一种基于高分辨率质谱的方法的开发和验证,该方法用于通过使用配备电喷雾电离和Orbitrap作为质量分析器的液相色谱-质谱联用技术,对饼干特定食品基质中的AA进行鉴定和定量。所开发的分析方法显示出良好的重复性(相对标准偏差为11.1%),检测限(LOD)和定量限(LOQ)分别为3.55和11.8 μg/kg。如本研究所示,对AA和AA-d3分离离子选择多重靶向-选择离子监测模式(t-SIM)可提高检测灵敏度。为了将AA水平与几个生产参数进行比较,对数据进行了统计处理,这些参数包括不同饼干的时间/烹饪温度、在烹饪传送带上的位置、颜色和水分。当考虑所有样品时,原料组成在统计学上是与AA含量相关性最高的因素。本文提出的统计处理方法能够对影响饼干中AA形成的因素进行重要预测,有助于制定有效的缓解策略。