Cheese yield is defined as the amount of cheese manufactured from a given amount of milk. It is considered a major factor affecting efficiency and profitability of cheese manufacturing. The characteristics of milk including its clotting ability evaluated with modern procedure based on near infrared technology was considered with the aim to develop an equation to predict yield of PDO Grana Padano cheese. Twenty nine 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; they were evaluated for: fat and caseins percentage, αs1, β and k-casein amount, α-lactoalbumin and β-lattoglobulin concentration (determined by official methods of analysis), protein amount (as the sum of serum protein and casein concentration) and for the aptitude to coagulate (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 Unscrumbler software 9.2 (Camo inc., Oslo Norvegia) using PLS analysis to built a statistical model considering as variables fat (kg), casein (kg), curd firmness, total protein and fat percentage to predict cheese yield. Curd firmness, fat and protein content showed to be three not correlated variables; it seemed that the amount of fat did not influence the coagulum strength nor it was able to be completely retained during the cheese making process and protein content was influenced by the relative casein composition. The relationship between curd firmness and cheese yield was no linear. The PLS analysis could be able to predict the cheese yield, and the obtained model overestimated the actual yield by an average of 0.23%. These preliminary results, suggested the suitability of NIR spectroscopy to evaluate the milk clotting behaviour in order to predict the cheese yield.
Cattaneo, T. M. P., Care', S., Marinoni, L., Perrone, A., Aleandri, R., Prediction of cheese yield using near infrared spectroscopy (NIRS), Paper, in Proceedings of 15th International Conference on Near Infrared Spectroscopy, (Cape Town, 13-20 May 2011), ICNIRS, Cape Town 2012: 416-419 [http://hdl.handle.net/10807/57403]
Prediction of cheese yield using near infrared spectroscopy (NIRS)
Marinoni, Laura;
2012
Abstract
Cheese yield is defined as the amount of cheese manufactured from a given amount of milk. It is considered a major factor affecting efficiency and profitability of cheese manufacturing. The characteristics of milk including its clotting ability evaluated with modern procedure based on near infrared technology was considered with the aim to develop an equation to predict yield of PDO Grana Padano cheese. Twenty nine 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; they were evaluated for: fat and caseins percentage, αs1, β and k-casein amount, α-lactoalbumin and β-lattoglobulin concentration (determined by official methods of analysis), protein amount (as the sum of serum protein and casein concentration) and for the aptitude to coagulate (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 Unscrumbler software 9.2 (Camo inc., Oslo Norvegia) using PLS analysis to built a statistical model considering as variables fat (kg), casein (kg), curd firmness, total protein and fat percentage to predict cheese yield. Curd firmness, fat and protein content showed to be three not correlated variables; it seemed that the amount of fat did not influence the coagulum strength nor it was able to be completely retained during the cheese making process and protein content was influenced by the relative casein composition. The relationship between curd firmness and cheese yield was no linear. The PLS analysis could be able to predict the cheese yield, and the obtained model overestimated the actual yield by an average of 0.23%. These preliminary results, suggested the suitability of NIR spectroscopy to evaluate the milk clotting behaviour in order to predict the cheese yield.
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