Comparison of three image-analysis-based visual texture calculation methods: energy, entropy, and texture change index.

BACKGROUND: Three image analysis methods to measure visual texture were applied to an image with much texture (scaled carp), and one with little texture (mirror carp). For each method, the effect of image rotation at 0°, 10°, 20°, 30°, 45°, 60°, 75° and 90° was evaluated. RESULTS: Rotation did not change energy (E) and entropy (H) calculations using image histograms. Using co-occurrence matrices with different step size d (1-19 in increases of 2) and step angle θ (0°, 45°, 90° and 135°) showed that, as d increased, E decreased and H increased, and the number of legitimate pixel pairs decreased linearly. Averaging E and H at different θ values rendered the results rotation invariant. Theoretically, the 'texture primitives' method is not rotation independent. However, the variation in texture change index (TCI) with image rotation was negligible. Also, the increase in TCI between the less textured image and the more textured image was 5.3-11. In comparison, the E values from histograms for the images above were 0.0069-0.0081. For co-occurrence matrix-based calculations, at d = 1 and for all θ, E range was from 220 to 389 for scaled carp and from 232 to 412 for mirror carp. CONCLUSION: The more than doubling of TCI for these images implies that it is a more precise method than energy and entropy to discern between visual texture levels. © 2022 Society of Chemical Industry.

Kinetically-arrested single-polymer nanostructures from amphiphilic mikto-grafted bottlebrushes in solution: a simulation study.

Solution self-assembly of molecular bottlebrushes offers a rich platform to create complex functional organic nanostructures. Recently, it has become evident that kinetics, not just thermodynamics, plays an important role in defining the self-assembled structures that can be formed. In this work, we present results from extensive molecular dynamics simulations that explore the self-assembly behavior of mikto-grafted bottlebrushes when the solvent quality for one of the side blocks is changed by a rapid quench. We have performed a systematic study of the effect of different structural parameters and the degree of incompatibility between side chains on the final self-assembled nanostructures in the low concentration limit. We found that kinetically-trapped complex nanostructures are prevalent as the number of macromonomers increases. We performed a quantitative analysis of the self-assembled morphologies by computing the radius of gyration tensor and relative shape anisotropy as the different relevant parameters were varied. Our results are summarized in terms of non-equilibrium morphology diagrams.

Citrus peel extract incorporated ice cubes to protect the quality of common pandora: Fish storage in ice with citrus.

The objective of this study was to investigate the effects of ice with albedo and flavedo fragments of Citrus (Grapefruit (Citrus paradisi) and Bitter orange (Citrus aurantium L.)) extracts on the quality of common pandora (Pagellus erythrinus). Concentrated citrus extracts were diluted with distilled water (1/100 w/v) before making of ice. The ice cubes were spread on each layer of fishes and stored at 0 °C for 15 days. The pH value showed a regular increase in all samples. TVB-N levels of bitter orange treatment groups were recorded lower than the other groups reaching to 25.11 ± 0.02 mg/100 g at the end of the storage. The TMA-N values of bitter orange treatment groups were lower than that of control and grapefruit treatment groups. In terms of TBARS value, alteration was observed in the control samples and this value significantly (p < 0.01) increased from 0.101 ± 0.011 mg MA/kg to 0.495 ± 0.083 mg MA/kg, while remained lower in the citrus extracts treatment groups at the end of storage since their antioxidant capacity. The oxidation was suppressed in citrus extracts treatment groups, especially in bitter orange flavedo treatment. The results showed the bitter orange albedo and bitter orange flavedo extracts in combination with ice storage have more effectiveness in controlling the biochemical indices in common pandora.

Color of rainbow trout (Oncorhynchus mykiss) fillets by image and sensory analysis, and correlation with SalmoFan numbers.

A total of 72 male and 50 female trout (Oncorhynchus mykiss) fillets were weighed (range 328-794 g, mean 546.2 ± 101.8 g; and range 426-994 g, mean 672.2 ± 106.1 g, respectively), the pictures of whom were taken in a light box, and image analysis was done to measure pixel colors, length, and view area of the fillets. Weight (W) was predicted using view area (V) obtained by image analysis using linear (W = A + BV), and power (W = AVB ) equations. R2 values were between 0.823 and 0.937. Although there was no difference between mean L* and a* values of male and female fillets, significant differences were found between mean b* values (p < 0.05). The colors of SalmoFan™ (SF) mini were also measured by image analysis and their mean L*, a*, b* values, and their entire color index (ECI) and reduced RGB values from 122 images were calculated. A total of 96 untrained panelists were asked to select the SF color of 5 representative fillets and to designate which point on the fillet image best described the SF color chosen. To predict SF numbers of the fillets by image analysis, four cases were considered: (1) whole fillet, (2) whole fillet with pixels a* > 25, (3) a rectangle along the length of the fillet to approximate panelists' selection, and (4) pixels in this rectangle with a* > 25. Mean L*a*b* values, mean reduced RGB values, and mean ECI of the four cases were used to predict fillet SF numbers. Different results obtained imply that image analysis can do repeatable and objective SF color classification of fillets, depending on the pixel selection method, and the color representation. PRACTICAL APPLICATION: Rainbow trout fillets can be assigned SalmoFan (SF) numbers using image analysis of the fillets. However, the selection of pixels and the color representation method affect the results. If these are standardized, SF numbers can be assigned objectively and automatically.

Effects of olive oil and olive oil-pomegranate juice sauces on chemical, oxidative and sensorial quality of marinated anchovy.

This study describes the potential use of olive oil and olive oil-pomegranate juice sauces as antioxidant, preservative and flavoring agent in fish marinades. The olive oil and sauces, produced from emulsifying of olive oil and pomegranate juice with gums, were blended with marinated anchovy (Engraulis encrasicholus) fillets. The aim of the present study was to produce a new polyphenol-rich marinade sauces by emulsifying pomegranate juice with olive oil in different proportions (25%, 35% and 50%v:v). In order to evaluate the effects of olive oil and olive oil-pomegranate juice sauces on quality of anchovy marinades, the chemical (TVB-N and TMA), oxidative (peroxides value, K230, thiobarbituric acid and K270) and sensory analyses were carried out during storage at 4°C. The present study showed that saucing of anchovy marinades with olive oil-pomegranate sauce can retard the undesirable quality changes, prolong the lipid oxidation and improve the sensory properties.

Prediction of the weight of Alaskan pollock using image analysis.

Determining the size and quality attributes of fish by machine vision is gaining acceptance and increasing use in the seafood industry. Objectivity, speed, and record keeping are advantages in using this method. The objective of this work was to develop the mathematical correlations to predict the weight of whole Alaskan Pollock (Theragra chalcogramma) based on its view area from a camera. One hundred and sixty whole Pollock were obtained fresh, within 2 d after catch from a Kodiak, Alaska, processing plant. The fish were first weighed, then placed in a light box equipped with a Nikon D200 digital camera. A reference square of known surface area was placed by the fish. The obtained image was analyzed to calculate the view area of each fish. The following equations were used to fit the view area (X) compared with weight (Y) data: linear, power, and 2nd-order polynomial. The power fit (Y = A · X(B)) gave the highest R(2) for the fit (0.99). The effect of fins and tail on the accuracy of the weight prediction using view area were evaluated. Removing fins and tails did not improve prediction accuracy. Machine vision can accurately predict the weight of whole Pollock. Practical Application: The weight of Alaskan Pollock can be predicted automatically by taking the image of the fish and using it in one of the correlations developed in this study. The removal of the fins or the fins and the tail did not increase the prediction accuracy of the method. Therefore, intact fish images should be used.