Study On Protein Feed Material Discrimination Using The Two Dimensional Correlation NIRS/NIRM

To monitor the feed quality and ensure the feed safety, this research focuses on the two-dimensional correlation spectroscopy, variable-scale near-infrared spectroscopy and their combination technique to effectively discriminate protein feed material. The research work is of important scientific and practical value in enriching rapid detection method of protein feed. The main research contents and conclusions of are as follows:Effective near-infrared microscopic discrimination of compound feed and meat and bone meal has been investigated via a variable selection by two-dimensional correlation spectroscopy. The variable selection method is proposed based on autopeaks and cross peaks of two-dimensional correlation synchronous.12main sensitive variables are identified, and they are6852,6388,6320,5788,5600,5244,4900,4768,4572,4336,4256and4192cm-1. These sensitive variables are then used to build a discrimination model, which yields a correct classification of99%. This method presents the advantages of introducing an interpretive aspect to variable selection; enabling efficient compression and analysis of spectral data; and enabling result transferability to discriminant analysis.Effective near-infrared microscopic discrimination of fishmeal and meat and bone meal has been investigated via a variable selection by two-dimensional correlation spectroscopy. The variable selection method is proposed based on autopeaks of two-dimensional correlation near-infrared microscopy.11main sensitive variables are identified, and they are5788,5748,5676,4900,4468,4368,4336,4300,4264,4232and4196cm-1. These sensitive variables are then used to build a discrimination model, which yields a correct classification more than98%. This method presents the advantages of introducing an interpretive aspect for variable selection, enabling efficient compression and analysis of spectral data.Visualized recognition of fishmeal and meat and bone meal has been investigated via temperature-dependent two-dimensional correlation near-infrared spectroscopy. Fingerprint visual pattern differences are observed from20-60℃temperature-dependent synchronous maps between fishmeal and meat and bone meal. Its visual discrimination method is proposed:the two-dimensional correlation synchronous calculated from dynamic spectra at the range of6000-5400cm-1with the pretreatment of baseline correction and wavelet transform. This method presents the advantages of clearly clarifying the discrimination mechanism; enabling visualized and intuitive recognition; and improving sharing of the model.Visualized recognition of different specific meat and bone meal has been investigated via temperature-dependent two-dimensional correlation near-infrared spectroscopy. Fingerprint visual pattern differences are observed from10-65℃synchronous maps between poultry, bovine and porcine originated meat and bone meal. The visual discrimination methods are proposed:the two-dimensional correlation synchronous calculated from dynamic spectra at the range of8600-8200cm-1with the baseline correction pretreatment and the spectral reconstruction; synchronous calculated from dynamic spectra at the range of6000-5500cm-1with the second derivative pretreatment and the spectral reconstruction. This method presents the advantages of enabling visualized and intuitive recognition; and improving sharing of the model.Rapid identification of fishmeal and soybean meal has been investigated via a sample-sample two-dimensional correlation near-infrared spectroscopy. Numerical information for differentiating fishmeal and soybean meal is extracted by synchronous slice spectrum, it is further developed for qualitative discrimination threshold. Validation samples are100%correctly classified by these thresholds. Sample-sample two-dimensional correlation near-infrared spectroscopy is capable to discriminate fishmeal and soybean meal samples, and it presents the advantages of enabling simple computation and rapid identification.