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Non destructive monitoring of the yoghurt fermentation phase by an image analysis of laser-diffraction patterns: Characterization of cow's, goat's and sheep's milk

机译:通过激光衍射图的图像分析对酸奶发酵阶段进行无损监测:牛,山羊和绵羊奶的表征

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Monitoring yogurt fermentation by the image analysis of diffraction patterns generated by the laser-milk interaction was explored. Cow's, goat's and sheep's milks were tested. Destructive physico-chemical analyses were done after capturing images during the processes to study the relationships between data blocks. Information from images was explored by applying a spectral phasor from which regions of interest were determined in each image channel. The histograms of frequencies from each region were extracted, which showed evolution according to textural modifications. Examining the image data by multivariate analyses allowed us to know that the captured variance from the diffraction patterns affected both milk type and texture changes. When regression studies were performed to model the physico-chemical parameters, satisfactory quantifications were obtained (from R-2 = 0.82 to 0.99) for each milk type and for a hybrid model that included them all. This proved that the studied patterns had a common fraction of variance during this processing, independently of milk type.
机译:探索了通过激光-牛奶相互作用产生的衍射图样的图像分析监测酸奶发酵。测试了牛奶,山羊奶和绵羊奶。在研究过程中捕获图像后进行破坏性的理化分析,以研究数据块之间的关系。通过应用频谱相量探索来自图像的信息,从中确定每个图像通道中的关注区域。提取每个区域的频率直方图,显示根据纹理修改的演变。通过多变量分析检查图像数据,使我们知道从衍射图样捕获的差异会影响牛奶类型和质地变化。当进行回归研究以对物理化学参数进行建模时,对于每种牛奶类型以及包括所有这些类型的混合模型,都获得了令人满意的定量结果(R-2 = 0.82至0.99)。这证明了所研究的模式在此过程中具有共同的方差分数,而与牛奶类型无关。

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