Journal
FOOD CONTROL
Volume 112, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.foodcont.2020.107111
Keywords
Grated cheese; Rind percentage; NIR hyperspectral imaging; Multivariate calibration; Multivariate image analysis
Categories
Funding
- Consorzio del Formaggio Parmigiano Reggiano (Italy)
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Parmigiano Reggiano (P-R) is one of the most important Italian food products labelled with Protected Designation of Origin (PDO). The PDO denomination is applied also to grated P-R cheese products meeting the requirements regulated by the Specifications of Parmigiano Reggiano Cheese. Different quality parameters are monitored, including the percentage of rind, which is edible and should not exceed the limit of 18% (w/w). The present study aims at evaluating the possibility of using near infrared hyperspectral imaging (NIR-HSI) to quantify the rind percentage in grated Parmigiano Reggiano cheese samples in a fast and non-destructive manner. Indeed, NIR-HSI allows the simultaneous acquisition of both spatial and spectral information from a sample, which is more suitable than classical single-point spectroscopy for the analysis of heterogeneous samples like grated cheese. Hyperspectral images of grated P-R cheese samples containing increasing levels of rind were acquired in the 900-1700 nm spectral range. Each hyperspectral image was firstly converted into a one-dimensional signal, named hyperspectrogram, which codifies the relevant information contained in the image. Then, the matrix of hypes-spectrograms was used to calculate a calibration model for the prediction of the rind percentage using Partial Least Squares (PIS) regression. The calibration model was validated considering two external test sets of samples, confirming the effectiveness of the proposed approach.
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