On site monitoring of Grana Padano cheese production using portable spectrometers

  • Laura Marinoni
  • Angelo Stroppa
  • Stefania Barzaghi
  • Katia Cremonesi
  • Nicolò Pricca
  • Aurora Meucci
  • Giulia Maria Pedrolini
  • Andrea Galli
  • Giovanni Cabassi
Consorzio per la tutela del Formaggio Grana Padano, Desenzano del Garda, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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Università degli Studi di Milano, Milano, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy

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 Corresponding Author
CREA-ZA, Council for Agricultural Research and Economics - Research Centre for Animal Production and Aquaculture, Lodi, Italy
[email protected]
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The GRANIR project founded by the Grana Padano Protection Consortium and developed by CREA-ZA research centre is devoted to the development of a rapid and economic method for the chemical characterisation of Grana Padano PDO cheese based on near infrared (NIR) spectroscopy technology. For this purpose, the Consortium purchased several portable spectrometers XNIRTM (dinamica generale®, Poggio Rusco, MN, Italy), to be assigned to the Consortium staff for screening operations of production batches in the fire-branding step, in warehouses and at the packaging step, on cheese paste. To develop predictive models and to evaluate the performance of the portable instruments, 195 samples of Grana Padano were scanned directly on the whole open wheel, scanning both rind and cheese paste. Robust models were built for the prediction of dry matter, fat, fat/dry matter, proteins and proteins/dry matter content using average spectra of rind and paste and chemical data of cheese paste. Additional spectra acquired with two other instruments were included in order to make the models less sensitive to different instruments. Spectra of the same samples acquired at different temperatures (10, 16 and 25 °C) were also added to the dataset in order to reduce the influence of temperature on prediction results. The obtained results showed a satisfactory predictive ability of the models built with portable NIR spectrometers, with respect to the chemical composition of Grana Padano cheese, showing root mean square errors in prediction comparable to that obtained with a Fourier-Transform NIR benchtop instrument. This allows the estimation of average cheese composition, at batch level, using multiple scans taken on a high number of wheels.


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