Discrimination of crumb grain visual appearance of organic and non-organic bread loaves by image texture analysis (original) (raw)
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Evaluation of Image Analysis Tools for Characterization of Sweet Bread Crumb Structure
Food and Bioprocess Technology
Many approaches to evaluate bread crumb features by applying free or at least not too expensive image analysis (IA) software have been published; however, the described procedures showed noticeable differences. The aim of this work was to compare different image scanning resolutions and thresholding techniques to quantify sweet bread crumb features (cell density, mean cell area, shape factor) and their relation with fractal dimension. Two sets of experiments were carried out, one to determine the effect of scanning resolution and thersholding method and the other to validate the previous results by evaluating breads with different crumb structures. Nine different scanning resolutions (75, 100, 150, 200, 300, 355, 435, 515, 555 dpi) and two segmentation procedures (Otsu and Manual) were tested. Three different types of commercial sweet breads and a yeasted sweet bread added with different concentrations (six, 12%) of Chia flour (Salvia hispanica) were evaluated. Results showed that the percentage of particles with areas between 0.1 and 4.0 mm2 remained almost constant when using 350 dpi or larger resolution values, while the smallest particles (<0.1 mm2) increased their proportion up to 87% at the highest scanning resolution for both thresholding methods. IA was useful to detect crumb structure differences among commercial breads and breads added with Chia flour as obtained from cell density (154 ± 4.6–246 ± 2.5) and mean cell area (0.81 ± 0.02–0.7 ± 0.03) results. However, the number of selected objects to calculate these parameters produced different results. The addition of 6% of Chia flour did not affect the bread crumb features, while at the largest proportion more and smaller pores were obtained. Fractal texture was useful to evaluate bread crumb structure, as it not depends on the number of particles detected.
Introducing an Automatic Bread Quality Assessment Algorithm using Image Processing Techniques
European Journal of Electrical Engineering and Computer Science
In this research, an automatic algorithm of bread quality assessment using image processing techniques, is proposed. First, color images of bread with different qualities are photographed and a database of 1250 bread images is prepared. Then 2320 color and texture features are extracted from each bread images. Then, from this number of features, only 15 features containing sufficient information are selected. In addition, 54 appearance features are extracted from each bread image to determine its shape and size. Finally, bread images are classified using the multilevel Support Vector Machine classifier. The classification process is divided into five "one-against-all" classification problems. The proposed algorithm correctly identifies the bread appearance defects, including cuts, fractures, folds, non-uniformity, black and burnt areas in baking, deformity, color and size. The proposed algorithm, considering the extraction of only 15 features per an image, has a speed that...
Texture Analysis of Spelt Wheat Bread
The Journal of Microbiology, Biotechnology and Food Sciences, 2013
The bread quality is considerably dependent on the texture characteristic of bread crumb. Texture analysis is primarily concerned with the evaluation of mechanical characteristics where a material is subjected to a controlled force from which a deformation curve of its response is generated. It is an objective physical examination of baked products and gives direct information on the product quality, oppositely to dough rheology tests what are inform on the baking suitability of the flour, as raw material. This is why the texture analysis is one of the most helpful analytical methods of the product development. In the framework of our research during the years 2008 – 2009 were analyzed selected indicators of bread crumb for texture quality of three Triticum spelta L. cultivars – Oberkulmer Rotkorn, Rubiota and Franckenkorn grown in an ecological system at the locality of Dolna Malanta near Nitra. The bread texture quality was evaluated on texture analyzer TA.XT Plus and expressed as...
Journal of Cereal Science, 2017
Consumption of bread and the demands concerning its quality features, being one of them its appearance , have been experiencing rapid growth. Thus, the standardization of its production aiming to keep its quality, applying new methods. The objective of this research was to develop a method to optimize the bread-making processes based on the acceptability of its crust color. For this effect, bread was experimentally produced using a Box-Behnken experimental design with three factors (sugar-flour relation, Baking temperature and Baking time) and three answer variables (L*, a*, b* ¼ parameters of CIELab color space); determination of color, by means of the acquisition, pre-processing, and analysis of images of bread samples until getting the color expressed in CIELab coordinates; an analysis of sensorial acceptance was made determining the L*, a*, and b* with the highest acceptance by consumers; finally, the optimization of the production process was made based on the L*, a*, and b* parameters, getting the optimal production parameters. The results show that by using the proposed method, it is possible to correlate the parameters of CIELab color space and the acceptance of the final consumer aiming to optimize bread making processes, it means getting bread with crust color of maximum acceptability.