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Feasibility of the Detection of Carrageenan Adulteration in Chicken Meat Using Visible/Near-Infrared (Vis/NIR) Hyperspectral Imaging

机译:使用可见/近红外线(VI / NIR)高光谱成像检测鸡肉中角叉菜蜡掺假的可行性

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The detection of carrageenan adulteration in chicken meat using a hyperspectral imaging (HSI) technique associated with three spectroscopic transforms was investigated. Minced chicken was adulterated with carrageenan solution (2% w/v) in the volume range of 0–5 mL at an increment of 1 mL. Hyperspectral images of prepared samples were captured in a reflectance mode in a Visible/Near-Infrared (Vis/NIR, 400–1000 nm) region. The reflectance (R) spectra were first extracted from regions of interest (ROIs) by applying a mask that was built using band math combined with thresholding and were then transformed into two other spectral units, absorbance (A) and Kubelka-Munck (KM). Partial least squares regression (PLSR) models based on full raw and preprocessed spectra in the three profiles were established and A spectra were found to perform best with R p 2 = 0.92, root mean square error of prediction set (RMSEP) = 0.48, and residual predictive deviation (RPD) = 6.18. To simplify the models, several wavelengths were selected using regression coefficients (RC) based on all three spectral units, and 10 wavelengths selected from A spectra (409, 425, 444, 521, 582, 621, 763, 840, 893, and 939 nm) still performed best with the R p 2 , RMSEP, and RPD of 0.85, 0.93, and 3.20, respectively. Thus, the preferred simplified RC-A-PLSR model was selected and transferred into each pixel to obtain the distribution maps and finally, the general different adulteration levels of different samples were readily discernible. The overall results ascertained that the HSI technique demonstrated to be an effective tool for detecting and visualizing carrageenan adulteration in authentic chicken meat, especially in the absorbance mode.
机译:研究了使用高光谱成像(HSI)与三个光谱转化相关的高光谱成像(HSI)技术检测鸡肉中的角叉菜簇掺杂。碎鸡以0-5ml的羧烷烷溶液(2%w / v)掺杂,以0-5ml的增量为1ml。在可见/近红外(VI / NIR,400-1000nm)区域的反射模式中捕获制备样品的高光谱图像。首先通过应用使用带数学建造的掩模来从感兴趣的区域(ROIS)中提取反射率(R)光谱,然后将其改为阈值化,然后转化为另外两种光谱单元,吸光度(a)和kubelka-munck(km) 。建立了基于完全原始和预处理光谱的局部最小二乘(PLSR)模型建立了三种型材中,发现光谱最佳地以R p 2 = 0.92,预测集的根均方误差(RMSEP)= 0.48,以及残留预测偏差(RPD)= 6.18。为了简化模型,使用基于所有三个光谱单元的回归系数(RC)选择多个波长,以及从光谱(409,425,444,521,582,621,763,840,893和939的10个波长NM)仍然最适用于R P 2,RMSEP和0.85,0.93和3.20的RPD。因此,选择优选的简化RC-A-PLSR模型并将其转移到每个像素中以获得分布图,最后,易于辨别出不同样本的一般不同样本的普遍不同掺杂水平。总体结果确定了HSI技术作为一种有效的工具,用于检测和可视化正宗鸡肉中的角叉菜胶掺杂,特别是在吸光度模式中。

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