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Cross-polarized VNIR hyperspectral reflectance imaging for non-destructive quality evaluation of dried banana slices, drying process monitoring and control

机译:交叉偏振VNIR高光谱反射成像技术用于香蕉干片的无损质量评估,干燥过程监控

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摘要

Banana and its dried products are one of the most common foods consumed all over the world. Quality attributes of dried banana slices are typically evaluated using time-consuming and labor intensive methods which do not allow to evaluate each individual slice. Replacement of the current destructive methods for quality evaluation of dried banana slices by fast, non-destructive methods would provide large added value to the food industry. Therefore, the aim of this study was to monitor the moisture content, texture and color of banana slices during the drying process in a fast and non-destructive way. VNIR hyperspectral reflectance imaging in the 400–1000 nm range was selected for this purpose. Thanks to a cross-polarized configuration the effects of glare or specular reflection on the banana slice surfaces in the hyperspectral diffuse reflectance images was largely reduced. Reference quality attributes for all the slices (moisture content, texture and color (L*, a*, b*values) obtained using conventional destructive methods and colorimeter were predicted from their corresponding average reflectance spectra extracted from the hyperspectral images by means of partial least squares regression (PLSR). The PLSR calibration models were validated on samples which had not been used for model calibration. The results were very good for water content (R2P = 0.97,RMSEP = 0.05 kg water/kg DM), quite good for andb*value (R2P = 0.83,RMSEP = 1.95), and reasonable for texture (R2P = 0.66,RMSEP = 11.8 N),a*value (R2P = 0.53,RMSEP = 1.32) andL*value (R2P = 0.61,RMSEP = 5.92). Subsequently, these calibration models were used to predict those quality attributes at pixel level for the validation slices to visualize the spatial distribution of these quality parameters at different stages during the drying process. The obtained results clearly indicate the potential of cross-polarized hyperspectral reflectance imaging for non-destructive monitoring of the quality attributes of banana slices during drying.
机译:香蕉及其干品是全世界消费最普遍的食品之一。香蕉干片的质量属性通常使用费时费力的方法进行评估,这种方法无法评估每个单独的片。快速,无损的方法代替目前用于干香蕉片质量评估的破坏性方法,将为食品工业带来巨大的附加值。因此,本研究的目的是以快速,无损的方式监测干燥过程中香蕉片的水分含量,质地和颜色。为此选择了400-1000 nm范围内的VNIR高光谱反射成像。由于采用了交叉极化配置,大大降低了高光谱漫反射图像中香蕉切片表面上的眩光或镜面反射的影响。使用常规破坏性方法和色度计获得的所有切片的参考质量属性(水分,质地和颜色(L *,a *,b *值))通过偏最小二乘法从高光谱图像中提取的相应平均反射光谱中进行预测平方回归(PLSR)。PLSR校准模型在未用于模型校准的样品上进行了验证,结果对水含量非常好(R2P =,0.97,RMSEP = 0.05 kg水/ kg DM),对b很好。 *值(R2P = 0.83,RMSEP = 1.95),并且对于纹理合理(R2P = 0.66,RMSEP = 11.8 N),a *值(R2P = 0.53,RMSEP = 1.32)和L *值(​​R2P = 0.61,RMSEP = 5.92) )。随后,使用这些校准模型预测验证切片在像素级别的质量属性,以可视化干燥过程中不同阶段这些质量参数的空间分布,所得结果清楚地表明了交叉极化的潜力高分辨率的高光谱反射成像技术可无损监控香蕉片在干燥过程中的质量属性。

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