Machine Vision Analysis of Antibrowning Potency for Oxalic Acid: A Comparative Investigation on Banana and Apple

Yoruk, R.; Yoruk, S.; Balaban, Murat Ö.; Marshall, Maurice R.

doi:10.1111/j.1365-2621.2004.tb10999.x

Cited by 42 publications

(28 citation statements)

References 25 publications

(27 reference statements)

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“…Average L * , a * , b * values of the whole fillet surface were calculated using a colour analysis program. 9,12,13 Both the Minolta colorimeter and the machine vision system used average daylight illuminant D65 mode with a colour temperature of 6504 K.…”

Section: Colour Analysismentioning

confidence: 99%

Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon

et al. 2009

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BACKGROUND: Minolta and machine vision are two different instrumental techniques used for measuring the colour of muscle food products. Between these two techniques, machine vision has many advantages, such as its ability to determine L * , a * , b * values for each pixel of a sample's image and to analyse the entire surface of a food regardless of surface uniformity and colour variation. The objective of this study was to measure the colour of irradiated Atlantic salmon fillets using a hand-held Minolta colorimeter and a machine vision system and to compare their performance.

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Section: Colour Analysismentioning

confidence: 99%

Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon

et al. 2009

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“…However, in apple slices, the development of non-uniform color patterns during browning (specifically L* color) was observed. With the aim of quantifying non-homogenous color surfaces in apple slices during browning, Yoruk et al (2004) employed an approximation, based on the reduction of the original number of red, green and blue intensity levéis. They adopted a sub-color space derived from the RGB space, in which each color axis (Red, Green, Blue), normally ranging from 0 to 255, was divided by eight so that the colors were regrouped in 8x8x8 = 512 ranges.…”

Section: Introductionmentioning

confidence: 99%

A multispectral vision system to evaluate enzymatic browning in fresh-cut apple slices

Lunadei

Galleguillos

Diezma

et al. 2011

Postharvest Biology and Technology

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Keywords:Fresh-cut apples Enzymatic browning CIÉ L*a*f>* color space Multispectral images Image analysisThe main objective of this study was to develop a visión system that is able to classify fresh-cut apple slices according to the development of enzymatic browning. The experiment was carried out on 'Granny Smith' apple slices stored at 7.5 °C for 9 days (n = 120). Twenty-four samples were analyzed per day: at zero time and after storage for 1, 3, 7 and 9 days, which corresponds to treatments to, ti, h, ti and t% respectively. Multispectral images were acquired from the samples by employing a 3-CCD camera centered at the infrared (IR, 800nm), red (R, 680nm) and blue (B, 450nm) wavelengths. Apple slices were evaluated visually according to a visual color scale of 1 -5 (where 1 corresponds to fresh samples without any browning and 5 to samples with severe discoloration), to obtain a sensory evaluation Índex (¡SE) for each sample. Finally, for each sample and for each treatment, visible (VIS) relative reflectance spectra (360-740 nm) were obtained. In order to identify the most related wavelengths to enzymatic browning evolution, unsupervised pattern recognition analysis of VIS reflectance spectra was performed by principal components analysis (PCA) on the autoscaled data. Máximum loading valúes corresponding to the B and R áreas were observed. Therefore, a classification procedure was applied to the relative histograms of the following monochromatic images (virtual images), which were computed pixel by pixel: (R-B)/(R + B),R-B and B/R. Inall cases,a non-supervised classification procedure was able to genérate three image-based browningreference classes (BRC): Cluster A (corresponding to the to samples), ClusterB (ti andt3 samples) and Cluster C(t7 and tg samples). Aninternal and anexternal validation (n = 120) were carried out, and the best classifications were obtained with the (R -B)/(R + B) and B/R image histograms (internal validation: 99.2% of samples correctly classified for both virtual images; external validation: 84% with (R -B)/(R + B) and 81% with B/R). The camera classification was evaluated according to the colorimetric measurements, which were usually utilized to evalúate enzymatic browning development (CIÉ L'a'b* color parameters and browning Índex, BI) and according to ¡SE-For both validation phases a*, b*, BI and ¡SE increased while I* valúes decreased with image-based class number, thereby reflecting their browning state.

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“…Figure 1 showed the average of L* value decreased during an enzymatic browning in fruit slices, while FD L* increased (Fig. 3) [19,29,30]. Increasing FD L* value showing increasing irregularity of SI L* .…”

Section: Enzymatic Browning Modelmentioning

confidence: 87%

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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Machine Vision Analysis of Antibrowning Potency for Oxalic Acid: A Comparative Investigation on Banana and Apple

Cited by 42 publications

References 25 publications

Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon

Comparison of Minolta colorimeter and machine vision system in measuring colour of irradiated Atlantic salmon

A multispectral vision system to evaluate enzymatic browning in fresh-cut apple slices

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

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