Abstract
This study analyzed the meat and bone meal (MBM) matrix complexity from the perspective of fraction composition diversity and a classification strategy was proposed to accurately and rapidly identify the MBM species based on near infrared spectroscopy (NIRS). Partial Least Squares-Discrimination Analysis (PLS-DA) based on full samples, meat meal (MM), MBM and bone meal (BM) performed with decreasing classification errors of 0.115, 0.079, 0.044 and 0.039 which were partly caused by wide sample range; bone fraction content had positive correlation with most of MBM species differences reflected by principal component scores; and PLS-DA classification errors among MM, MBM and BM were lower than 0.013. To take fully advantage of the above results, a sequential classification strategy was proposed; near infrared spectra were selected (belong to MM, MBM or BM) and then species discrimination analysis was conducted based on the specific PLS-DA model.
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