Near-infrared hyperspectral image analysis for monitoring the cheese-ripening process

• Published in: Journal of Dairy Science
• Main Authors: Alinaghi, Masoumeh (University of Veterinary Medicine Vienna / Umeå University), Trygg, Johan (Umeå University), Saedén, Karin Hallin (Norrmejerier), Höjer, Annika (Norrmejerier), Nilsson, David (Umeå University), Singh, Nikita (Umeå University)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2023
• Subjects: Northern Sweden; Bovine-Milk; Dairy Farms; Proteolysis; Goat; Spectroscopy; Prediction; Acids; Tool
• Online Access: https://doi.org/10.3168/jds.2023-23377; https://phaidra.vetmeduni.ac.at/o:2491

Ripening is the most crucial process step in cheese manufacturing and constitutes multiple biochemical alterations that describe the final cheese quality and its perceived sensory attributes. The assessment of the cheese-ripening process is challenging and requires the effective analysis of a multitude of biochemical changes occurring during the process. This study monitored the biochemical and sensory attribute changes of paraffin wax-covered long-ripening hard cheeses (n = 79) during ripening by collecting samples at different stages of ripening. Near-infrared hyperspectral (NIR-HS) imaging, together with free amino acid, chemical composition, and sensory attributes, was studied to monitor the biochemical changes during the ripening process. Orthogonal projection-based multivariate calibration methods were used to characterize ripening-related and orthogonal components as well as the distribution map of chemical components. The results approve the NIR-HS imaging as a rapid tool for monitoring cheese maturity during ripening. Moreover, the pixelwise evaluation of images shows the homogeneity of cheese maturation at different stages of ripening. Among the chemical compositions, fat content and moisture are the most important variables correlating to NIR-HS images during the ripening process.