Department of Food and Drug, University of Parma, Strada del Taglio 10, 43126 Parma, Italy.
Department of Veterinary Medical Science, University of Bologna, Via Tolara di Sopra 50, 40064 Ozzano dell'Emilia, Bologna, Italy.
Food Chem. 2019 May 15;280:321-327. doi: 10.1016/j.foodchem.2018.12.075. Epub 2018 Dec 21.
Chemometric analysis of near-infrared spectroscopy (NIRS) data was applied to investigate the possibility to rapidly authenticate European sea bass (Dicentrarchus labrax L.) according to production method (wild or farmed), rearing system (extensive, semi-intensive or intensive), and geographical origin (Western, Central or Eastern Mediterranean Sea). NIR spectra from 1100 to 2500 nm were subjected to an exploratory principal component analysis (PCA) followed by orthogonal partial last square-discriminant analysis (OPLS-DA) to develop classifiers able to distinguish samples according to the various conditions under study. Models provided a correct classification rate of 100% for both wild and farmed sea bass, and of 67%, 80%, 100% for extensively, semi-intensively, and intensively-reared subjects, respectively. As for geographical provenance, 100% of Eastern, 88% of Central and 85% of Western Mediterranean Sea samples were correctly discriminated. The successful results obtained confirmed suitability of chemometric analysis applied to NIRS data for fast authentication of European sea bass origin.
化学计量学分析近红外光谱(NIRS)数据被应用于研究根据生产方法(野生或养殖)、养殖系统(粗放型、半集约型或集约型)和地理起源(西、中或东地中海)快速鉴别欧洲海鲈(Dicentrarchus labrax L.)的可能性。对 1100 至 2500nm 的 NIR 光谱进行探索性主成分分析(PCA),然后进行正交偏最小二乘判别分析(OPLS-DA),以开发能够根据研究的各种条件区分样本的分类器。对于野生和养殖的海鲈,模型的正确分类率均为 100%;对于粗放型、半集约型和集约型养殖的海鲈,其正确分类率分别为 67%、80%和 100%。至于地理起源,正确区分了 100%的东地中海、88%的中地中海和 85%的西地中海样本。所获得的成功结果证实了化学计量学分析应用于 NIRS 数据快速鉴别欧洲海鲈起源的适用性。