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Prediction of Meat Spectral Signatures in the Near Infrared Region Using Optical Properties of MainChromophores

机译:MainChoromophors光学性质预测近红外区域近红外区域的肉谱鉴定

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An approximation model for predicting spectral signatures of minced meat samples was developed depending on the concentrations and optical properties of the major chemical constituents. Minced beef samples of different compositions scanned on a near infrared (NIR) spectroscopy and on a hyperspectral imaging system were examined. Chemical composition determined heuristically and optical properties collected from authenticated references were modeled to approximate meat' spectral signatures. By assuming homogeneous distributions of the main chromophores in the mince samples, the obtained absorption spectra are found to be a linear combination of the absorption spectra of the major chromophores present in the sample. Results revealed that the developedmodels were good enough to derive spectral signatures of minced meat samples with a reasonable level of robustness and agreement index value more than 0.90 and ratio of performance to deviation (RPD) more than 1.4.
机译:根据主要化学成分的浓度和光学性质开发了用于预测碎肉样品光谱签名的近似模型。检查扫描在近红外(NIR)光谱和高光谱成像系统上扫描的不同组合物的碎牛肉样品。化学成分测定的启发式和从经过认证的参考文献收集的光学性质被建模为近似肉类光谱签名。通过假设Mince样品中主要发色团的均匀分布,发现所获得的吸收光谱是样品中存在的主要发色团的吸收光谱的线性组合。结果表明,培养的模型足以使碎肉样品的光谱签名具有合理的鲁棒性和协议指标值超过0.90,并且性能与偏差比(RPD)的比例超过1.4。

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