Color changes in the surface of fresh cut meat: A fractal kinetic application

Quevedo, Roberto; Valencia, Emir; Cuevas, G.; Ronceros, Betty; Pedreschi, Franco; Bastías-Montes, José Miguel

doi:10.1016/j.foodres.2013.10.006

Cited by 41 publications

(31 citation statements)

References 36 publications

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“…[20,22,28] The FD value was used as an indicator of changes in the non-homogenous distribution of the surface colours of meat during oxidation. [25] Lacunarity of the sample images was estimated at the end of CUT at different temperatures. As shown in Fig.…”

Section: Effect Of Cut On Lightness Of the Colourmentioning

confidence: 99%

“…[24] Fractal dimension (FD) shows the degree of ruggedness and geometric complexities of both natural and synthetic particles. [25] The more heterogeneous or irregular structure has the higher FD, but the more homogeneous or smooth one has the lower FD. Lacunarity describes the homogeneity of an image, and it is defined as 'gappiness' and visual texture in the morphological analysis which characterises the difference between two images having similar FD.…”

Section: Introductionmentioning

confidence: 99%

“…[23] FD was used to study the changes in the intensity of the redness colour in meat during oxidation as an indicator of alterations in the non-homogenous distribution of the colours associated with redness intensity and content of metmyoglobin and Thiobarbituric acid reactive substances (TBARS). [25] It was also found that FD could be applied to describe the enzymatic browning of avocado puree and slices of pear, apple, banana, and avocado. [20][21][22]27,28] The formed fractal structures by aggregation of colloidal particles were also applied to understanding the structure, aggregation, and stability of particles that are responsible for the cloudy appearance of apple juice.…”

Section: Introductionmentioning

confidence: 99%

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Cloud stability of sour orange juice as affected by pectin methylesterase during come up time: Approached through fractal dimension

Aghajanzadeh

Kashaninejad

Ziaiifar

2017

International Journal of Food Properties

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Cloud stability of the juice is affected by pectin methylesterase (PME) activity. Come up time (CUT) of thermal treatment showed inactivation effect on PME. In this study, lacunarity and fractal dimension (FD) were used to evaluate the effect of CUT on PME activity and appearance of the sour orange juice. The CUT lasted 2.68, 2.58, 2.51, 2.46, 2.43, 2.33, and 2.28 min at 60, 65, 70, 75, 80, 85, and 90°C, respectively. The fractal dimension and lacunarity were estimated using the box counting method. PME activity, cloud value and lightness were measured according to Kimball, spectroscopy methods, and image processing, respectively. Higher PME inactivation and cloud value and lower lightness of the juice were obtained at a higher temperature. FD showed a high correlation with changes in PME activity, cloud, and lightness of the juice. Lacunarity was used to describe the shape and gap distribution within the image. As the combination of FD and lacunarity was useful in the study of the image, these factors could be applied to evaluate the effect of CUT on some of the physical and chemical properties of fruit juice. ARTICLE HISTORY

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Section: Effect Of Cut On Lightness Of the Colourmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cloud stability of sour orange juice as affected by pectin methylesterase during come up time: Approached through fractal dimension

Aghajanzadeh

Kashaninejad

Ziaiifar

2017

International Journal of Food Properties

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“…In the muscle of living animal, the iron atoms in myoglobin are in the ferrous (Fe 2+ )‐reduced form (deoxymyoglobin and oxymyoglobin) giving the red color. During meat storage, the Fe 2+ myoglobins are oxidized to Fe 3+ myoglobin (metmyoglobin) that gives the brownish‐red color …”

Section: Introductionmentioning

confidence: 99%

“…The chemical ones are destructive, laborious, and have a low analytical frequency. Standard spectrophotometric methods using Commission Internationale de L'Eclairage ‐ CIE, luminosity – L*, redness – a* and yellowness – b* (CIELab) or Red, Green and Blue (RGB) color spaces are non‐destructive methods and have higher analytical frequency than the chemical ones . In both cases, the need to have the instruments and chemical reagents in the laboratory is crucial.…”

Section: Introductionmentioning

confidence: 99%

Prediction of beef color using time‐domain nuclear magnetic resonance (TD‐NMR) relaxometry data and multivariate analyses

Moreira

Ferrari²,

Moraes

et al. 2016

Magnetic Reson in Chemistry

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Time-domain nuclear magnetic resonance and chemometrics were used to predict color parameters, such as lightness (L*), redness (a*), and yellowness (b*) of beef (Longissimus dorsi muscle) samples. Analyzing the relaxation decays with multivariate models performed with partial least-squares regression, color quality parameters were predicted. The partial least-squares models showed low errors independent of the sample size, indicating the potentiality of the method. Minced procedure and weighing were not necessary to improve the predictive performance of the models. The reduction of transverse relaxation time (T ) measured by Carr-Purcell-Meiboom-Gill pulse sequence in darker beef in comparison with lighter ones can be explained by the lower relaxivity Fe present in deoxymyoglobin and oxymyoglobin (red beef) to the higher relaxivity of Fe present in metmyoglobin (brown beef). These results point that time-domain nuclear magnetic resonance spectroscopy can become a useful tool for quality assessment of beef cattle on bulk of the sample and through-packages, because this technique is also widely applied to measure sensorial parameters, such as flavor, juiciness and tenderness, and physicochemical parameters, cooking loss, fat and moisture content, and instrumental tenderness using Warner Bratzler shear force. Copyright © 2016 John Wiley & Sons, Ltd.

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Supervision of Food Manufacturing Processes Using Optical Process Analyzers – An Overview

et al. 2016

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The food industry is the fourth largest industrial sector in Germany. The eagerness for innovation is classified as low. The food industry faces significantly larger challenges compared to the chemical industry since the demands of raw materials on processing are higher and more complex. In this contribution, the characteristics of food manufacturing are presented. The potential of optical process analyzers based on NIR, fluorescence, and Raman spectroscopy as well as on digital image analysis is demonstrated. These process analyzers can provide important information on raw materials, intermediate and end products, and improve the automation grade of production processes.

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Color changes in the surface of fresh cut meat: A fractal kinetic application

Cited by 41 publications

References 36 publications

Cloud stability of sour orange juice as affected by pectin methylesterase during come up time: Approached through fractal dimension

Cloud stability of sour orange juice as affected by pectin methylesterase during come up time: Approached through fractal dimension

Prediction of beef color using time‐domain nuclear magnetic resonance (TD‐NMR) relaxometry data and multivariate analyses

Supervision of Food Manufacturing Processes Using Optical Process Analyzers – An Overview

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