Quality assessment of butter cookies applying multispectral imaging

Abstract

A method for characterization of butter cookie quality by assessing the surface browning and water content using multispectral images is presented. Based on evaluations of the browning of butter cookies, cookies were manually divided into groups. From this categorization, reference values were calculated for a statistical prediction model correlating multispectral images with a browning score. The browning score is calculated as a function of oven temperature and baking time. It is presented as a quadratic response surface. The investigated process window was the intervals 4–16 min and 160–200°C in a forced convection electrically heated oven. In addition to the browning score, a model for predicting the average water content based on the same images is presented. This shows how multispectral images of butter cookies may be used for the assessment of different quality parameters. Statistical analysis showed that the most significant wavelengths for browning predictions were in the interval 400–700 nm and the wavelengths significant for water prediction were primarily located in the near-infrared spectrum. The water prediction model was found to correctly estimate the average water content with an absolute error of 0.22%. From the images it was also possible to follow the browning and drying propagation from the cookie edge toward the center.

Biscuits: A Substitution of Wheat Flour with Purple Rice Flour

“…An understanding of the combination of the ingredients, together with baking process, has an important effect on the quality and color of the final product [19]. Andresen et al [88] suggested that the main drivers determining consumer preferences of biscuits are closely related to the major ingredients, the spreadability of the biscuits and appearance (i.e. width and thickness) because these aspects can make biscuits look delicious.…”

Process analytical technology for bakery industry: A review

“…Browning kinetics model was developed images gathered with computer vision system during baking process (Quevedo et al, 2018) HSI 224-band AVIRI Surface browning and moisture content in baking studied at 400-700 nm (Andresen, Dissing, & Løje, 2013) Dimension of cookies measured and browning, humidity assessment at 400-1000 nm (Carstensen, 2012) Cake moisture prediction done by building PLS-R model to HIS (Sun, 2016) Texture evaluation of bread prepared by cress seed gum and xanthun gum substituting gluten was performed (Naji-Tabasi & Mohebbi, 2015) Quality and aging of muffin sample was studied by applying algorithm to the images captured (Grillo et al, 2014) Morphological feature of baked biscuit analyzed (Bade, Dale, & Jemshid, 2016) Algorithm for color measurement developed in MATLAB 6.5 (Purlis & Salvadori, 2009) Crust thickness determined using cold cathode fluorescent lamp (Jusoh, Chin, Yusof, & Rahman, 2009) Quality and shape of baked breads determined using CVS with modified VJ algorithm. The CVS image analyzed by PCA showed a clear separation of cakes as a function of the storage time with a prediction value of 0.91 Color studied using CVS of light intensity 10-100% based on furan content in dough and baked product…”

“…HSI was done to assess the surface browning and moisture content in cookies at 400-700 nm during baking (Andresen et al, 2013).…”

Utilizing cocoyam (Xanthosoma sagittifolium) for food and nutrition security: A review

“…Here, light reflection at a large number of different wavelengths is used to produce a spectral image from which both spectral and spatial information can be obtained simultaneously. Thus, minute details in texture, color, microstructure, and surface chemistry of a heterogeneous matrix could be obtained in one test (Andresen, Dissing, & Løje, ). This simultaneous measure of different attributes in a single test positions the technology as an ideal cost‐effective technology for the ever‐changing and demanding food industry (Feng & Sun, ).…”