Discrimination of crumb grain visual appearance of organic and non-organic bread loaves by image texture analysis (original) (raw)
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Statistical and spectral texture analysis methods for discrimination of bread crumb images
13th World Congress of Food Science & Technology, 2006
The objectives of this study were: (i) to assess the performance of three statistical texture analysis methods (grey-level co-occurrence matrix, neighbourhood grey-level difference matrix and geometrical method) and two spectral texture analysis methods (Fourier power spe ctrum features and spectral features sensitive to additive noise) to differentiate bread crumb grain loaves produced with five different flours, and (ii) to find the textural features that presented high discriminant capacity. The stepwise-selected textural features from the neighbourhood difference matrix and the geometrical method could classify 85% and 80% of the samples by flour type, respectively, using cross-validation. As a whole, the statistical texture analysis depicted the bread crumb visual texture better than the transform methods as the factor analysis for the two principal components for the statistical methods explained 91.2 -95.9% of the total variability. The method of wedges and rings from the Fourier power spectrum performed poorly for distinguishing the bread crumb grains produced with the different flours (correct classification of 58% and total variability accounted for of 75.4%).
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.
Food Science and Technology (Campinas), 2015
The cellular structure of healthy food products, with added dietary fiber and low in calories, is an important factor that contributes to the assessment of quality, which can be quantified by image analysis of visual texture. This study seeks to compare image analysis techniques (binarization using Dtsu's method and the default ImageJ algorithm, a variation of the iterative intermeans method) for quantification of differences in the crumb structure of breads made with different percentages of whole-wheat flour and fat replacer, and discuss the behavior of the parameters number of cells, mean cell area, cell density, and circularity using response surface methodology. Comparative analysis of the results achieved with the Dtsu and default ImageJ algorithms showed a significant difference between the studied parameters. The Dtsu method demonstrated the crumb structure of the analyzed breads more reliably than the default ImageJ algorithm, and is thus the most suitable in terms of structural representation of the crumb texture.
Bread crumb quality assessment: a plural physical approach
European Food Research and Technology, 2009
The aim of this study was the assessment of pan bread crumb quality attributes of commercial samples using a plural physical approach to better match consumer awareness. Static (texture profile analysis, firmness AACC and relaxation test) and dynamic (innovative oscillatory test) deformation techniques, image analysis, sensory analysis and colour measurements (colorimeter and Photoshop system) were used for white/whole commercial pan bread quality evaluation over 10 days of storage. Static (k 1 , k 2 , cohesiveness, springiness, hardness, chewiness and resilience) and dynamic (stress) bread crumb rheological properties were correlated illustrating that both techniques can be useful in evaluating crumb physical characteristics. In addition, sensory perceiveness with regard to softness and overall acceptability exhibited dependence with either dynamic stress or static firmness. Despite the fact that empirical measurements are closely linked to macroscopic features whilst dynamic tests are strongly linked to molecular characteristics, the obtained results support that both techniques are complementary since derived instrumental parameters are related to some sensory attributes. As data achieved using the proposed novel approaches might be better linked to the consumer awareness than those obtained from classical analyses, the obtained results are promising for a proper bread crumb quality assessment.
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...
Chemometric and image analysis of Croatian wheat cultivars and their bread making quality
ITI 2002. Proceedings of the 24th International Conference on Information Technology Interfaces (IEEE Cat. No.02EX534), 2002
Fourteen physical and chemical properties of flours obtained from eleven Croatian wheat cultivars, eleven physical dough properties, seven standard bread quality tests, and a computer image analysis of bread porosity are by chemometric analysis investigated. Since complexity of sensory evaluation determination bread-making quality of wheat is difficult, it motivates investigation of computer image analysis of bread quality. Images of medium loaf surface are digitised and processed using original computer program for medium part porosity determination. Due to high correlation between chemical, physical and quality data, chemometric analysis is applied to determine minimal number of latent variables for determination of clusters of samples and properties (variables) in two dimensional score planes. Robust partial least squares models for prediction of bread quality based on only four latent variables are developed.
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 Texture Studies, 2015
Food texture is one of the most widely measured quality attributes during processing and consumption, being measured by instrumental and sensory means. The aims of this study were to measure the textural parameters of the crumb of 14 whole-wheat bread loaves made with whole-wheat flour and fat replacer using instrumental methods and a sensory trained panel, and to determine the relationship between instrumental and sensory assessments. The data of instrumental and sensory texture were individually subjected to analysis of variance and correlated using principal component analysis. The analyses showed that for both (instrumental and sensory texture), the less firm, more elastic and more cohesive bread loaves have <60% whole-wheat flour, regardless of the content of fat replacer. The hardness attribute, measured with a texturometer, was consistent with the results of other published works and with our sensory evaluation as the matrix showed correlation coefficients with high values. PRACTICAL APPLICATIONS Wheat bread is a common staple food around the world that can be used to deliver ingredients for specific health purposes. Diets rich in whole grain foods and low fat may be suggested to help to protect against several chronic diseases, as well as for weight management. At a pilot plant scale, it is very difficult to keep good quality standards for whole-wheat products. Therefore, instrumental and sensory studies on loaf texture were used to perform texture profile analysis on the crumb structure of 14 different types of whole-wheat bread loaves made with fat replacer (enzymatically modified corn starch).
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.