Enzymatic browning in sliced and puréed avocado: A fractal kinetic study

Quevedo, Roberto; Ronceros, Betty; Garcia, Karen; López, Patricia; Pedreschi, Franco

doi:10.1016/j.jfoodeng.2011.02.012

Cited by 26 publications

(14 citation statements)

References 28 publications

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“…Obtained results showed that fractal method was more sensitive in difference detection where colour patterns have a non-homogenous colour surface. [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.…”

Section: Effect Of Cut On Lightness Of the Colourmentioning

confidence: 99%

“…[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. [29] FD and lacunarity were studied to evaluate the structural changes in quality of the fresh papaya sliced during environmental conditions.…”

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%

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 other words, during the browning of quinces, distribution of L* values on the area, it appears more heterogeneous and non-uniform color patterns emerge on images. This phenomenon is not quantified when an average of L* value is used [20]. So, use a parameter (FD L* ) that represent entire form and distributing these L* value over the area instead of using the average of these L* values is better.…”

Section: Enzymatic Browning Modelmentioning

confidence: 99%

“…Recently, Leon et al (2006) used CVS to measure color in L*a*b* from image [15,19]. Average L* value is used to the description of browning kinetics while that browning in surface quince slices was non-homogenous color [20,21].…”

Section: Introductionmentioning

confidence: 99%

Quantification of enzymatic browning kinetics of quince preserved by edible coating using the fractal texture Fourier image

et al. 2015

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The effect of different coating [Aloe vera, Chitosan (0.5 and 1.5 %), Carboxymethlcellulose (0.5 and 1.5 %)] on the enzymatic browning kinetics of quince was determined by traditional and fractal browning indicator methods (FBI) at during cold storage. Power-law model used to model the enzymatic kinetic of fractal dimension value (FD L* ) and average L* value (conventional method). The results showed that the average of L* value decreased during an enzymatic browning in fruit slices, while FD L* rose. The more changes in L* value was observed for quinces coated with CMC 0.5 % that about similar to changes in uncoated quinces were from 90.083 to 67.571 and 90.736 to 66.786 respectively at nine days. The quinces treated with Chitosan 1.5 % had more changes in FD L* value compared to another treatment. In other words, enzymatic browning in quinces coated with Chitosan 1.5 % has more heterogeneous and non-uniform color patterns. Kinetic rate (K) got from FD L* was the higher than kinetic rate (K) got using average L* value. Kinetic's order (shape factor) got the FBI method compared to the conventional method was lower because in conventional method assuming occurs homogenous surface coloration.

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“…In addition, based on fractal analysis and CIELab parameters, Zheng and Lu (2012) employed least-squares SVM to classify mangoes into different grades and the results demonstrated that a classifier based on both fractal analysis and CIELab (with an accuracy of 100%) performed better than that based only on either fractal analysis (88.98%) or CIELab (85.19%). Moreover, computer vision evaluating systems were developed to detect enzymatic browning in pear slices (Quevedo et al, 2009a;Quevedo et al, 2011) and avocado purée (Quevedo et al, 2011). In these studies, color in digital images was transformed into L*a*b* color space by means of a transformation function, and three kinds of pears were detected, and the results were encouraging.…”

Section: Mangoes and Pearsmentioning

confidence: 99%

Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances

Sun

et al. 2014

Critical Reviews in Food Science and Nutrition

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With consumer concerns increasing over food quality and safety, the food industry has begun to pay much more attention to the development of rapid and reliable food-evaluation systems over the years. As a result, there is a great need for manufacturers and retailers to operate effective real-time assessments for food quality and safety during food production and processing. Computer vision, comprising a nondestructive assessment approach, has the aptitude to estimate the characteristics of food products with its advantages of fast speed, ease of use, and minimal sample preparation. Specifically, computer vision systems are feasible for classifying food products into specific grades, detecting defects, and estimating properties such as color, shape, size, surface defects, and contamination. Therefore, in order to track the latest research developments of this technology in the agri-food industry, this review aims to present the fundamentals and instrumentation of computer vision systems with details of applications in quality assessment of agri-food products from 2007 to 2013 and also discuss its future trends in combination with spectroscopy.

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Enzymatic browning in sliced and puréed avocado: A fractal kinetic study

Cited by 26 publications

References 28 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

Quantification of enzymatic browning kinetics of quince preserved by edible coating using the fractal texture Fourier image

Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances

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