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Prediction of sensory properties of low-fat yoghurt and cream cheese from surface images.

机译:从表面图像预测低脂酸奶和奶油干酪的感官特性。

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摘要

The sensory properties of 25 plain yoghurts and 18 low-fat cream cheeses were investigated by descriptive analysis. In parallel with sensory analysis digital images of sample surfaces were captured and the relationship between image properties and sensory properties were investigated. Global image features of the yoghurt and cream cheese surfaces were extracted using the Angle Measure Technique (AMT). Multivariate data analyses (Partial Least Squares Regression) were applied for investigation of the relation between digital image global features and sensory properties. For both product categories all sensory properties could be predicted with Root Mean Square Error of Cross Validation (RMSECV) for the yoghurts in the range [1.00;1.97] and for the cream cheeses [0.29;2.80]. For yoghurts, the largest RMSECV is for the prediction of Creaminess, indicating that it is not well predicted from structure alone. Due to covariation with appearance and structure, sensory properties relating to different modalities (taste and flavour) could also be predicted. All rights reserved, Elsevier.
机译:通过描述性分析研究了25种普通酸奶和18种低脂奶油干酪的感官特性。在进行感官分析的同时,捕获了样品表面的数字图像,并研究了图像特性与感官特性之间的关系。使用角度测量技术(AMT)提取了酸奶和奶油干酪表面的整体图像特征。多变量数据分析(偏最小二乘回归)用于研究数字图像全局特征与感官特性之间的关系。对于这两种产品,可以用交叉验证的均方根误差(RMSECV)来预测酸奶的[1.00; 1.97]和奶油干酪的所有感官特性[0.29; 2.80]。对于酸奶,最大的RMSECV用于预测乳脂状,表明仅从结构上不能很好地预测。由于外观和结构的变化,还可以预测与不同形态(味觉和风味)有关的感官特性。保留所有权利,Elsevier。

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