Pennisi Francesco, Giraudo Alessandro, Cavallini Nicola, Esposito Giovanna, Merlo Gabriele, Geobaldo Francesco, Acutis Pier Luigi, Pezzolato Marzia, Savorani Francesco, Bozzetta Elena
Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, Via Bologna 148, 10154 Turin, Italy.
Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy.
Foods. 2021 Mar 3;10(3):528. doi: 10.3390/foods10030528.
The sale of frozen-thawed fish and fish products, labeled as fresh, is currently one of the most common and insidious commercial food frauds. For this reason, the demand of reliable tools to identify the storage conditions is increasing. The present study was performed on two species, commonly sold in large-scale distribution: Cuttlefish () and musky octopus ( spp.). Fifty fresh cephalopod specimens were analyzed at refrigeration temperature (2 ± 2 °C), then frozen at -20 °C for 10 days and finally thawed and analyzed again. The performance of three near-infrared (NIR) instruments in identifying storage conditions were compared: The benchtop NIR Multi Purpose Analyzer (MPA) by Bruker, the portable MicroNIR by VIAVI and the handheld NIR SCiO by Consumer Physics. All collected spectra were processed and analyzed with chemometric methods. The SCiO data were also analyzed using the analytical tools available in the online application provided by the manufacturer to evaluate its performance. NIR spectroscopy, coupled with chemometrics, allowed discriminating between fresh and thawed samples with high accuracy: Cuttlefish between 82.3-94.1%, musky octopus between 91.2-97.1%, global model between 86.8-95.6%. Results show how food frauds could be detected directly in the marketplace, through small, ultra-fast and simplified handheld devices, whereas official control laboratories could use benchtop analytical instruments, coupled with chemometric approaches, to develop accurate and validated methods, suitable for regulatory purposes.
销售标示为新鲜的冻融鱼及鱼产品,是目前最常见且隐蔽的商业食品欺诈行为之一。因此,对用于识别储存条件的可靠工具的需求日益增加。本研究针对两种在大规模销售中常见的物种进行:乌贼()和麝香蛸( 属)。五十个新鲜头足类标本在冷藏温度(2±2°C)下进行分析,然后在-20°C冷冻10天,最后解冻并再次分析。比较了三种近红外(NIR)仪器在识别储存条件方面的性能:布鲁克的台式近红外多功能分析仪(MPA)、Viavi的便携式微型近红外光谱仪和消费者物理公司的手持式近红外SCiO。所有收集的光谱均采用化学计量学方法进行处理和分析。SCiO数据还使用制造商在线应用程序中提供的分析工具进行分析,以评估其性能。近红外光谱结合化学计量学,能够高精度地区分新鲜样品和解冻样品:乌贼的准确率在82.3%-94.1%之间,麝香蛸在91.2%-97.1%之间,全局模型在86.8%-95.6%之间。结果表明,食品欺诈行为可以通过小型、超快速且简化的手持式设备在市场上直接检测出来,而官方控制实验室可以使用台式分析仪器,结合化学计量学方法,开发适用于监管目的的准确且经过验证的方法。