Department of Food Engineering, Faculty of Engineering, Adnan Menderes University, Aydin 09100, Turkey.
Department of Food Science and Technology, The Ohio State University, 100 Parker Food Science and Technology Building, 2015 Fyffe Road, Columbus, OH 43210, USA.
Molecules. 2022 Feb 9;27(4):1161. doi: 10.3390/molecules27041161.
Current assays for acrylamide screening rely heavily on LC-MS/MS or GC-MS, techniques that are not suitable to support point of manufacturing verification because it can take several weeks to receive results from a laboratory. A portable sensor that can detect acrylamide levels in real-time would enable in-house testing to safeguard both the safety of the consumer and the economic security of the agricultural supplier. Our objective was to develop a rapid, accurate, and real-time screening technique to detect the acrylamide content in par-fried frozen French fries based on a portable infrared device. Par-fried French fries ( = 70) were manufactured at times ranging from 1 to 5.5 min at 180 °C to yield a wide range of acrylamide levels. Spectra of samples were collected using a portable FT-IR device operating from 4000 to 700 cm. Acrylamide was extracted using QuEChERS and quantified using uHPLC-MS/MS. Predictive algorithms were generated using partial least squares regression (PLSR). Acrylamide levels in French fries ranged from 52.0 to 812.8 µg/kg. The best performance of the prediction algorithms required transformation of the acrylamide levels using a logarithm function with models giving a coefficient of correlation (Rcv) of 0.93 and RPD as 3.8, which means the mid-IR model can be used for process control applications. Our data corroborate the potential of portable infrared devices for acrylamide screening of high-risk foods.
目前用于丙烯酰胺筛选的检测方法主要依赖于 LC-MS/MS 或 GC-MS，这些技术不适用于支持制造现场的验证，因为从实验室获得结果可能需要数周的时间。一种能够实时检测丙烯酰胺水平的便携式传感器将能够进行内部测试，从而保障消费者的安全和农业供应商的经济安全。我们的目标是开发一种快速、准确、实时的筛选技术，基于便携式红外设备检测预炸冷冻法式薯条中的丙烯酰胺含量。在 180°C 下，将预炸薯条（=70）的制备时间从 1 分钟到 5.5 分钟不等，以产生广泛的丙烯酰胺水平。使用便携式 FT-IR 设备从 4000 到 700 cm 采集样品光谱。使用 QuEChERS 提取丙烯酰胺，并使用 uHPLC-MS/MS 定量。使用偏最小二乘回归（PLSR）生成预测算法。薯条中的丙烯酰胺含量范围为 52.0 至 812.8 µg/kg。预测算法的最佳性能要求使用对数函数对丙烯酰胺水平进行转换，模型的相关系数（Rcv）为 0.93，RPD 为 3.8，这意味着中红外模型可用于过程控制应用。我们的数据证实了便携式红外设备在高风险食品的丙烯酰胺筛选方面的潜力。
