Development of a computer vision system to measure the color of potato chips

Visual analysis of sea buckthorn fruit moisture content based on deep image processing technology

The effect of moisture content changes during drying processing on the appearance of sea buckthorn was studied. Using computer vision methods and various image processing methods to collect and analyze images during the drying process of sea buckthorn fruit. Sea buckthorn is dried in a drying oven at a temperature of 65 °C and Level 1 wind speed conditions. The images of the entire drying process of sea buckthorn fruit were collected at 30-min intervals. Deep mining and transformation of image information through various image processing methods. By calibrating and modeling the color components, real-time online detection of the moisture content of sea buckthorn fruit can be achieved. After modeling, this article attempted to use LSTM (Long Short Term Memory) to predict the appearance of sea buckthorn fruit with supercritical moisture content. Different agricultural products adapt to different color spaces, but after standard modeling with a certain amount of data, applying color components to detect moisture content is a very good method.

Dual-Stage ultrasound in deep frying of potato chips; effects on the oil absorption and the quality of fried chips

Potato chips are popular high-consuming ready-to-eat meals in all of the world which specially attract a lot of attention from youth and children. Reducing oil absorption and improving the quality of chips are major undertakings within the industry. This research aimed to find the best ultrasonic bath-based method by investigating the optimal ultrasonic pre-treatment and developing an ultrasound (US) assisted frying system (UAFS) to reduce the oil absorption of potato chips while maintaining an acceptable quality. Through this technique, the potato chips get sonicated during deep frying in hot oil. US-pretreatment at temperatures of 25 °C and 73 °C, along with US-assisted frying, resulted in the minimal amount of oil which may be due to the US creating potential pores during the pre-treatment phase, which then expand further during the subsequent sonication stage. UAFS in combination with US-pretreatment produced more crispy chips due to the fact that the texture of potato slices becomes more porous. UAFS resulted in a decrease in the moisture content of the fried chips attributed to an increase in the effective diffusion coefficient and mass. Pretreating the chips at 73 °C significantly reduce the color change producing brighter product by inactivation of enzymes such as polyphenol oxidase. Finally, the result of TOPSIS optimization based on potato chips properties confirms that US-pretreatment in 73 °C brine followed by frying using UAFS is the best approach. Scanning electron microscope (SEM) images of potato chips also support this issue.

Effect of Dissolution Time on the Development of All-Cellulose Composites Using the NaOH/Urea Solvent System

Innovative and sustainable all-cellulose composites (ACCs) can be obtained by partial dissolution of cellulosic fibers and regeneration of the dissolved fraction. Among cellulose solvents, sodium hydroxide/urea solutions are recognized as promising low-environmental impact systems. In this work, filter paper (FP) was dissolved with a 7 wt% NaOH/12 wt% urea aqueous solution, kept at −18 °C for different time intervals, regenerated with distilled water and finally dried under different conditions. The developed films were characterized in terms of morphology, porosity, optical properties, crystalline structure, hydration and mechanical properties. The porosity of the composites decreased with dissolution time due to the progressive filling of voids as the cellulosic fibers’ surface skin layer was dissolved and regenerated. Samples treated for 4 h showed the minimum values of porosity and opacity, high hydration and a substantial change from cellulose I to cellulose II. Hot pressing during drying led to relevant improvements in ACCs stiffness and strength values.

Water distribution and key aroma compounds in the process of beef roasting

The key aroma compounds and water distribution of the beef at different roasting times (0, 3, 6, 9, 12, 15, and 18 min) were identified and analyzed. The results showed that the L^* value increased considerably before peaking and then decreased. On average, a^* values decreased significantly first and then kept stable, while b^* values increased first and then decreased. A total of 47 odorants were identified in all samples, including 14 alcohols, 18 aldehydes, 6 ketones, 1 ester, 3 acids, 4 heterocyclic compounds, and 1 other compound. Among them, 11 key aroma compounds were selected and aldehydes and alcohols predominantly contributed to the key aroma compounds. The fluidity of the water in the beef during the roasting process was decreased, and the water with a high degree of freedom migrated to the water with a low degree of freedom. The correlation analysis showed that water content and L^* were negatively correlated with key aroma compounds of the samples, while M₂₁ was positively correlated with key aroma compounds.

Application of Supercooling for the Enhanced Shelf Life of Asparagus (Asparagus officinalis L.)

Freezing extends the shelf-life of food by slowing down the physical and biochemical reactions; however, ice crystal formation can result in irreversible damage to the cell's structure and texture. Supercooling technology has the potential to preserve the original freshness of food without freezing damage. In this study, fresh asparagus was preserved in a supercooled state and its quality changes such as color, weight loss, texture, chlorophyll and anthocyanin content, and enzymatic activities (superoxide dismutase and catalase) were evaluated. The asparagus samples were successfully supercooled at -3 °C with the combination treatment of pulsed electric field (PEF) and oscillating magnetic field (OMF), and the supercooled state was maintained for up to 14 days. Asparagus spears preserved in the supercooled state exhibited lower weight loss and higher levels of quality factors in comparison to the frozen and refrigerated control samples.

Feeding, Muscle and Packaging Effects on Lipid Oxidation and Color of Avileña Negra-Ibérica Beef

In order to increase the economic profitability of Avileña-Negra Ibérica beef production, the inclusion of corn silage in total mixed rations was proposed during the fattening period. Twenty-four Avileña-Negra Ibérica breed entire young bulls were used to evaluate the effects of two feeding systems-concentrate (CON) and corn silage (SIL)-and two packaging systems-vacuum (VAC) and modified atmosphere (MAP)-on the lipid oxidation, color evolution and visual color acceptability of meat throughout display with either oxygen-permeable film (FILM) or modified atmosphere (MAP). Two muscles were assessed: Longissimus thoracis (LT) and Semitendinosus (ST). Meat from SIL-fed animals had higher TBA values than CON-fed animals after 7 days in MAP packaging. Lipid oxidation was prevented more effectively by VAC packaging than MAP. Display time highly influenced lipid oxidation, since oxidation rates were lower with VAC than MAP packaging. After 14 days of display in MAP, the LT from CON was lighter than the ST. Meat discoloration after 7 days of display was significantly different between packaging systems. Vacuum-packaged meat kept the same color throughout the storage time. Visual color acceptability for the LT was higher throughout display than for the ST. Samples from the MAP were well accepted by consumers, especially the meat from the SIL group. Alternatively, feeding with corn silage could be used for this type of animals without affecting important aspects of meat quality.

Effect of hydrocolloid coatings (Basil seed gum, xanthan, and methyl cellulose) on the mass transfer kinetics and quality of fried potato strips

In this research, the effect of different temperatures (160, 180, and 190 °C) and hydrocolloid coatings (Basil seed gum [BSG], xanthan gum [XG], methylcellulose [MC], BSG-XG, and BSG-MC mixtures) were investigated on the physicochemical properties (oil uptake, moisture loss, color, microscopic structure, activation energy, and texture), mass transfer kinetic of fried potato strips in deep-fat frying, and oil partitions using frying and postfrying cooling phase. An increase in frying time reduced the moisture content and hardness of potato strips; however, the oil content and color difference increased. The oil content in the coated samples had lower rates than that in the noncoated ones. The treated samples using BSG-xanthan mixture (50:50) and BSG had the lowest oil uptake at 0.13% and 0.14% Dry basis (d.b.), respectively. The maximum and minimum values of effective moisture diffusivity were measured in control and samples coated with BSG-XG and BSG, respectively. As frying temperature increased, the specific rate of oil uptake increased and the equilibrium oil content decreased. Overall, BSG-XG mixture-coated potato strips can be used as a promising product due to absorbing the lowest oil rate and being similar to the control in terms of organoleptic properties.

The Effect of UV-C Stimulation of Potato Tubers and Soaking of Potato Strips in Water on Color and Analyzed Color by CIE L*a*b*

The color of French fries is an organoleptic attribute indicative of this product quality and also a reliable indicator of its safety. The darker the product color, the higher its acrylamide concentration. Acrylamide is an organic compound of the amide group showing neurotoxic and potential mutagenic actions in the human body. The content of acrylamide in fried potato products essentially depends on the contents of reducing sugars in intermediates of French fries’ production. The present study aimed to investigate the effect of UV-C irradiation and the soaking of potato strips in water on French fries’ color. The study was conducted on French fries obtained from tubers of the Innovator variety. The study was performed with the use of a special chamber for UV-C irradiation of biological samples and the CIE L*a*b* model for color analysis. The results of the study demonstrated that UV-C stimulation of potato tubers before processing had a beneficial effect on French fries’ color while the blanching of potato strips and soaking in water at a temperature of 40 °C resulted in the production of French fries lighter in color.

Multivariate Analysis and Machine Learning for Ripeness Classification of Cape Gooseberry Fruits

This paper explores five multivariate techniques for information fusion on sorting the visual ripeness of Cape gooseberry fruits (principal component analysis, linear discriminant analysis, independent component analysis, eigenvector centrality feature selection, and multi-cluster feature selection.) These techniques are applied to the concatenated channels corresponding to red, green, and blue (RGB), hue, saturation, value (HSV), and lightness, red/green value, and blue/yellow value (L*a*b) color spaces (9 features in total). Machine learning techniques have been reported for sorting the Cape gooseberry fruits’ ripeness. Classifiers such as neural networks, support vector machines, and nearest neighbors discriminate on fruit samples using different color spaces. Despite the color spaces being equivalent up to a transformation, a few classifiers enable better performances due to differences in the pixel distribution of samples. Experimental results show that selection and combination of color channels allow classifiers to reach similar levels of accuracy; however, combination methods still require higher computational complexity. The highest level of accuracy was obtained using the seven-dimensional principal component analysis feature space.

RNA Interference by Ingested dsRNA-Expressing Bacteria to Study Shell Biosynthesis and Pigmentation in Crassostrea gigas

RNA interference (RNAi) is an important molecular tool for analysis of gene function in vivo. Although the Pacific oyster Crassostrea gigas is an economically important species with fully sequenced genome, very few mechanistic studies have been carried out due to the lack of molecular techniques to alter gene expression without inducing stress. In this present study, we used unicellular alga Platymonas subcordiformis and Nitzschia closterium f. minutissima as a vector to feed oysters with Escherichia coli strain HT115 engineered to express double-stranded RNAs (dsRNAs) targeting specific genes involved in shell pigmentation. A C. gigas strain with black shell was used to target tyrosinase or peroxidase gene expression by RNAi using the above-mentioned approach. The results showed that feeding oyster with dsRNA of tyrosinase could knock down the expression of corresponding tyrosinase and hinder the developed shell growth. Feeding oyster with dsRNA of peroxidase could knock down the expression of the corresponding peroxidase and result in reduced black pigmentation in the newly developed shell. This non-invasive RNAi study demonstrated that tyrosinase played a vital role in the assembly and maturation of shell matrices and peroxidase was essential for black pigmentation in the shell. Moreover, the RNA interference by ingested dsRNA-expressing bacteria is a relatively simple and effective method for knockdown of a gene expression in adult oysters, thus further advances the use of C. gigas as model organism in functional genomic studies.

Computer Vision Method in Beer Quality Evaluation—A Review

Beers are differentiated mainly according to their visual appearance and their fermentation process. The main quality characteristics of beer are appearance, aroma, flavor, and mouthfeel. Important visual attributes of beer are foam appearance (volume and persistence), as well as the color and clarity. To replace manual inspection, automatic, objective, rapid and repeatable external quality inspection systems, such as computer vision, are becoming very important and necessary. Computer vision is a non-contact optical technique, suitable for the non-destructive evaluation of the food product quality. Currently, the main application of computer vision occurs in automated inspection and measurement, allowing manufacturers to keep control of product quality. This paper presents an overview of the applications and the latest achievements of the computer vision methods in determining the external quality attributes of beer.

Effect of (-)-epigallocatechin gallate (EGCG) extracted from green tea in reducing the formation of acrylamide during the bread baking process

This is the first study to investigate the extent of reduction in acrylamide formation during baking with the addition of (-)-epigallocatechin gallate (EGCG) extracted from green tea, and to determine whether EGCG influences the texture and colour attributes of bread, or interacts with other ingredients. EGCG powders were added to white bread formulations at the concentrations of 3.3, 6.6 and 9.9g·kg^-1. The amount of acrylamide in the bread was analysed using liquid chromatography-mass spectrometry. EGCG addition significantly reduced the acrylamide formation by 37% compared to the control and decreased the moisture content of the bread by 6%. It did not affect its texture attribute, but increased the lightness and the yellowness and decreased the redness of bread crust (with contrasting results in crumb). It also decreased granule size and porosity. In conclusion, EGCG fortification is a feasible method to decrease acrylamide formation in baked bread.

Appearance and characterization of fruit image textures for quality sorting using wavelet transform and genetic algorithms

Images of four qualities of mangoes and guavas are evaluated for color and textural features to characterize and classify them, and to model the fruit appearance grading. The paper discusses three approaches to identify most discriminating texture features of both the fruits. In the first approach, fruit's color and texture features are selected using Mahalanobis distance. A total of 20 color features and 40 textural features are extracted for analysis. Using Mahalanobis distance and feature intercorrelation analyses, one best color feature (mean of a* [L*a*b* color space]) and two textural features (energy a*, contrast of H*) are selected as features for Guava while two best color features (R std, H std) and one textural features (energy b*) are selected as features for mangoes with the highest discriminate power. The second approach studies some common wavelet families for searching the best classification model for fruit quality grading. The wavelet features extracted from five basic mother wavelets (db, bior, rbior, Coif, Sym) are explored to characterize fruits texture appearance. In third approach, genetic algorithm is used to select only those color and wavelet texture features that are relevant to the separation of the class, from a large universe of features. The study shows that image color and texture features which were identified using a genetic algorithm can distinguish between various qualities classes of fruits. The experimental results showed that support vector machine classifier is elected for Guava grading with an accuracy of 97.61% and artificial neural network is elected from Mango grading with an accuracy of 95.65%.

PRACTICAL APPLICATIONS

The proposed method is nondestructive fruit quality assessment method. The experimental results has proven that Genetic algorithm along with wavelet textures feature has potential to discriminate fruit quality. Finally, it can be concluded that discussed method is an accurate, reliable, and objective tool to determine fruit quality namely Mango and Guava, and might be applicable to in-line sorting systems.

Image Analysis and High Dimensional Control Chart for Inspection of Sausage Color Homogeneity and Uniformity

Sausage color usually influences consumers’ selection due to the perceptions of quality. Extensive studies have applied image processing to capture the characteristics of food products according to the high-dimensional nature of the resultant images. However, the color homogeneity (i. e. “within pack” variation) and uniformity (i. e. “between-pack” variation) have rarely been studied. Therefore, this paper proposes a new framework to detect both variations using images. In addition, a new approach has been developed to deal with high-dimension data involving colorimetric characteristics, namely L*, a*, b*, hue (h) and chroma (C*). These high-dimensional data are transformed to represent color homogeneity and uniformity. Hotelling T2 chart is used to detect color abnormalities. Our approach indicates that the out-of-control items can be identified with the control chart signals. Nonetheless, the out-of-control signals alone are inadequate for determination of the possible causes. Then, the proposed analysis framework was subsequently applied to identify possible causes that contributed to the process deviations. Furthermore, prior to the experiments with sausages, the image inspection device was tested for gauge repeatability and reproducibility.

Application of CMC as Thickener on Nanoemulsions Based on Olive Oil: Physical Properties and Stability

Carboxymethyl cellulose (CMC) is a hydrocolloid with surface activity that could act as emulsifiers in oil-in-water emulsions; however the principal role is that it acts as structuring, thickening, or gelling agent in the aqueous phase. This study aims to evaluate the application of CMC as thickener into nanoemulsions based on olive oil and their influence on particle characteristics, flow behavior, and color. Four nanoemulsions with different oil (5% and 15% w/w olive oil) and CMC (0.5% and 0.75% w/w) concentration and two control samples without CMC added were prepared using Tween 80 as emulsifier. All physical properties studied on nanoemulsions were depending on both oil and CMC concentration. In general, z-average particle size varied among 107–121 nm and those samples with 5% oil and CMC were the most polydisperse. The addition of CMC increased anionic charge of nanoemulsions obtaining zeta potential values among −41 and −55 mV. The oil concentration increased both consistency and pseudoplasticity of samples, although samples were more stable to gravitational separation at the highest CMC concentration. Color of nanoemulsions was affected principally by the oil concentration. Finally, the results showed that CMC could be applied in nanoemulsions as thickener increasing their physical stability although modifying their physical properties.