The technological quality of milk plays a fundamental role in the production of the PDO Grana Padano cheese, a north Italian cheese. To maximize the cheese yield, milk must have specific chemical characteristics (high content of casein and fat) and an ‘excellent’ ability to coagulate. Modern automated on-line methods, using near infrared technology have been studied to evaluate the milk clotting ability. Forty eight raw milk samples were collected monthly (from July to October 2008). For each sampling, milk was put in 2 tanks for creaming and was divided into copper vats to obtain PDO Grana Padano cheese. Samples were representative of the collected milk daily used in an Italian cheese making factory. Fat and caseins percentage, αs1, β and k-casein amount, α-lactoalbumin and β-lattoglobulin concentration were determined by official methods of analysis and the aptitude to coagulate was measured by Optigraph (Ysebaert Dairy Division, Frepillon-France) based on NIR principles (measure at 890nm). The cheese yield was expressed as cheese weight (1kg)/milk weight (100kg). Data were processed using Unscrambler software 9.2 (Camo inc., Oslo Norvegia) using PCA and PLS models. The PCA preliminary results showed that samples were separated according to the day of sampling due to seasonal variations. According to PC1 (60% of the total variance), samples were divided by: fat, total casein content, K-casein, α-lactoalbumin and β-lattoglobulin, curd firming, aggregation rate, gel density (determined by Optigraph); while to PC2 (16% of the total variance) by: αs1 and β-casein. The PLS analysis, calculated considering as variables both chemical values and measures of the milk clotting ability obtained by Optigraph, showed that the cheese yield can be well predicted by casein content but also by the milk clotting ability determined by NIR spectroscopy (n =48; range = 7.94-8.59; SD = 0.23; R2 = 0.98; RMSEC = 0.047 for calibration and R2 = 0.97; RMSEP = 0.057 and RPD = 4.89 for validation). These results, confirmed the close relationship between both total casein content, its fractions and cheese yield.
Cattaneo, T. M. P., Care', S., Marinoni, L., Perrone, A., Aleandri, R., Near infrared spectroscopy (NIRS) as a tool for the evaluation of milk quality for Grana Padano cheese production, Paper, in Proceedings of 15th International Conference on Near Infrared Spectroscopy, (Cape Town, 13-20 May 2011), ICNIRS, Cape Town 2012: 412-415 [http://hdl.handle.net/10807/57401]
Near infrared spectroscopy (NIRS) as a tool for the evaluation of milk quality for Grana Padano cheese production
Marinoni, Laura;
2012
Abstract
The technological quality of milk plays a fundamental role in the production of the PDO Grana Padano cheese, a north Italian cheese. To maximize the cheese yield, milk must have specific chemical characteristics (high content of casein and fat) and an ‘excellent’ ability to coagulate. Modern automated on-line methods, using near infrared technology have been studied to evaluate the milk clotting ability. Forty eight raw milk samples were collected monthly (from July to October 2008). For each sampling, milk was put in 2 tanks for creaming and was divided into copper vats to obtain PDO Grana Padano cheese. Samples were representative of the collected milk daily used in an Italian cheese making factory. Fat and caseins percentage, αs1, β and k-casein amount, α-lactoalbumin and β-lattoglobulin concentration were determined by official methods of analysis and the aptitude to coagulate was measured by Optigraph (Ysebaert Dairy Division, Frepillon-France) based on NIR principles (measure at 890nm). The cheese yield was expressed as cheese weight (1kg)/milk weight (100kg). Data were processed using Unscrambler software 9.2 (Camo inc., Oslo Norvegia) using PCA and PLS models. The PCA preliminary results showed that samples were separated according to the day of sampling due to seasonal variations. According to PC1 (60% of the total variance), samples were divided by: fat, total casein content, K-casein, α-lactoalbumin and β-lattoglobulin, curd firming, aggregation rate, gel density (determined by Optigraph); while to PC2 (16% of the total variance) by: αs1 and β-casein. The PLS analysis, calculated considering as variables both chemical values and measures of the milk clotting ability obtained by Optigraph, showed that the cheese yield can be well predicted by casein content but also by the milk clotting ability determined by NIR spectroscopy (n =48; range = 7.94-8.59; SD = 0.23; R2 = 0.98; RMSEC = 0.047 for calibration and R2 = 0.97; RMSEP = 0.057 and RPD = 4.89 for validation). These results, confirmed the close relationship between both total casein content, its fractions and cheese yield.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.