A Non-destructive method to assess freshness of raw bovine milk using FT-NIR spectroscopy.

Abstract

A non-destructive method to analyze the freshness of raw milk was developed using a FT-NIR spectrometer and a fiber optic probe. Diffuse transmittance spectra were acquired in the spectral range 833 ~ 2,500nm from raw milk samples collected from Northwest A&F University Animal Husbandry Station. After each spectral acquisition, quality parameters such as acidity, pH, and lactose content were measured by traditional detection methods. For all milk samples, PLS (partial least square regression), MLR (multiple linear regression), and ANN (artificial neural networks) analyses were carried out in order to develop models to predict parameters that were indicative of freshness. Predictive models showed R(2) values up to 0.9647, 0.9876 and 0.8772 for acidity, pH, and lactose content, respectively (validation set validations). The similarity analysis and classification between raw milk freshness during storage was also conducted by means of hierarchical cluster analysis. Over an 8day storage period, the highest heterogeneity was evident between days 1 and 2.