Abstract
According to European food safety authorities, one of the major control parameters for mechanically separated meat is calcium content, which is an indicator of residual bone. Residual bone in mechanically separated meat can also be measured as total ash content. Despite the need to measure both ash and/or calcium content of mechanically separated meat, there is no rapid analytical technique that can be used in an industrial environment. In the current study, we are presenting the first application of Raman spectroscopy as a rapid tool for estimating calcium and ash contents in bone and meat mixtures from mechanical deboning of chicken meat. Raman-based partial least squares regression models were developed for prediction of both ash and calcium content in 79 samples gathered from four different production days. Two different data pre-processing methods, i.e., polynomial background fitting and extended multiplicative scatter correction with polynomial extension, were applied to the raw Raman data and the prediction models were compared. The prediction model based on EMSC treated data afforded the lowest root mean square error of cross-validation (RMSECV = 0.333 g/100 g for calcium and RMSECV = 0.634 g/100 g for ash) and the highest coefficient of determination (R2 = 0.775 for calcium and R2 = 0.894 for ash).
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