DIFAR Department of Pharmacy, University of Genova, Genova, Italy.
DIFAR Department of Pharmacy, University of Genova, Genova, Italy.
Food Chem. 2021 May 1;343:128547. doi: 10.1016/j.foodchem.2020.128547. Epub 2020 Nov 7.
Cheese represents one of the most complex food matrices, for the high number of factors contributing to the chemical composition, and so its evaluation represents an important analytical challenge. The present study describes an innovative and non-destructive analytical approach, based on hyperspectral imaging in the near-infrared region (HSI-NIR) and multivariate pattern recognition, to study and monitor the extent - spatial and temporal - of biochemical phenomena responsible for cheese ripening. NIR spectral bands characterising dehydration, proteolysis and lipolysis were individuated and studied by exploiting a representative sample set of characteristic cheeses. The information obtained was employed to develop score maps based on principal component analysis (PCA), which permitted to monitor and visualise the ripening of Formaggetta, a commercial semi-hard cheese typical of Liguria, an Italian region, providing a deep understanding of the evolution of dehydration, proteolysis and lipolysis during the maturation period that precedes the placing on the market.
奶酪是一种成分非常复杂的食品,有很多因素会影响其化学组成,因此对奶酪进行评估是一项极具挑战性的分析任务。本研究描述了一种基于近红外光谱(HSI-NIR)和多元模式识别的创新、非破坏性分析方法,用于研究和监测导致奶酪成熟的生化现象的空间和时间范围。本研究通过对一组有代表性的典型奶酪进行分析,确定了能够反映脱水、蛋白质水解和脂肪分解的近红外光谱波段,并对这些波段进行了研究。本研究利用所获得的信息,基于主成分分析(PCA)开发了得分图,该得分图可用于监测和可视化 Formaggetta 的成熟过程,Formaggetta 是一种典型的产自意大利利古里亚地区的半硬质奶酪。该研究深入了解了在投放市场之前的成熟阶段,脱水、蛋白质水解和脂肪分解的演变过程。