Discrimination of seasonality in cheeses by near-infrared technology
Inmaculada González-Martín1, José Miguel Hernández-Hierro, Javier Salvador-Esteban
1Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Ciencias Químicas, C/Plaza de la Merced s/n, E-37008 Salamanca, Spain. inmaglez@usal.es
Background:
Owing to the importance of the season of collection of milk for cheese quality, a study was made of the usefulness of near-infrared spectroscopy (NIRS) for discriminating the seasonal origin (winter or summer) of milk and quantifying the fat content of cheeses, since fat is one of the components most affected by the season of collection of milk for the elaboration of cheeses.
Results:
In the internal validation, 96% of samples from winter milk and 97% of samples from summer milk were correctly classified, while in the external validation the prediction rate of samples correctly classified was 92%. Moreover, quantitative models allowed the determination of fat in winter, summer and winter + summer cheeses.
Conclusion:
Rapid prediction of the fat content of cheeses and the seasonal origin (winter or summer) of milk was achieved using NIRS without previous destruction or treatment of samples.
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