期刊
ANALYTICA CHIMICA ACTA
卷 706, 期 2, 页码 238-245出版社
ELSEVIER
DOI: 10.1016/j.aca.2011.08.046
关键词
RGB digital image analysis; Multivariate calibration; Wavelet transform; Colour; Food aspect; Pigments; Sensory evaluation
In the present paper, the possibility to use the information contained in RGB digital images to gain a fast and inexpensive quantification of colour-related properties of food is explored. To this aim, we present an approach which consists, as first step, in condensing the colour related information contained in RGB digital images of the analysed samples in one-dimensional signals, named colourgrams. These signals are then used as descriptor variables in multivariate calibration models. The feasibility of this approach has been tested using as a benchmark a series of samples of pesto sauce. whose RGB images have been used to predict both visual attributes defined by a panel test and the content of various pigments (chlorophylls a and b, pheophytins a and b, beta-carotene and lutein). The possibility to predict correctly the values of some of the studied parameters suggests the feasibility of this approach for fast monitoring of the main aspect-related properties of a food matrix. The values of the squared correlation coefficient computed in prediction on a test set (R-pred(2)) for green and yellow hues were greater than 0.75, while R-pred(2) values greater than 0.85 were obtained for the prediction of total chlorophylls content and of chlorophylls/pheophytins ratio. The great flexibility of this blind analysis method for the quantitative evaluation of colour related features of matrices with an inhomogeneous aspect suggests that it is possible to implement automated, objective, and transferable systems for fast monitoring of raw materials, different stages of the manufacture and end products, not necessarily for the food industry only. (C) 2011 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据