نشریه فناوری های جدید در صنعت غذا
سال دهم شماره 4 (پیاپی 40، تابستان 1402)

Hyperspectral imaging, a technology that combines imaging and spectroscopy, provides extensive spatial and spectral information, simultaneously. It is currently being developed as a non-destructive and rapid diagnostic tool for assessing food quality and safety. In this study, hyperspectral imaging was utilized to investigate the process of bread staleness and its effect on the behavior of the bread crumb within the wavelength range of 950-400 nm and with a resolution of 0.795 nm. Principal components were extracted and three modeling methods - PCR, PLSR, and GRNN - were employed to predict texture characteristics during six days of storage. Based on the findings of this study, it was observed that the General Regression Neural Network (GRNN) method demonstrated superior performance in terms of R2 values for both springiness and stiffness, with values of 0.96 and 0.94, respectively. Furthermore, the GRNN method also exhibited the lowest Root Mean Square Error (RMSE) values for cohesiveness and stiffness, with values of 0.11 and 0.32, respectively. This demonstrates the capability of the generalized regression neural network model to predict the textural characteristics of bread.

Today, human’s specific attention to food quality has led to the development of fast, easy and non-destructive methods to assess the quality of foodstuffs. Meat is one of the most important foods and its freshness is considered as the most important qualitative feature. Therefore, checking its quality for consumption has great value worthwhile. The main objective of the present study is to investigate the possibility of using electronic nose and artificial neural network methods for detecting the freshness of chicken meat during storage in a refrigerator at 4 ºC. In the used neural network system, the input layer consists of 10 neurons based on the number of sensors and the output layer includes 3 neurons related to classes of different freshness classes of chicken meat. Different classifier networks were designed and after investigation of different network structures; the best structure of the network was obtained with a hidden layer and 6 neurons in that layer. Finally, the optimal network with a general structure of 10-6-3 was created to detect the freshness of chicken meat during different days of storage. The used statistical indices to assess the classifier to evaluate the freshness of chicken meat including accuracy, precision, sensitivity, specificity and area under the curve factors. The values of these indices for classification using selected characteristics are 95.77, 94.7, 92.18, 95.95, and 94.1 respectively. Therefore, given that the main objective of the present study was to develop and implementation of an intelligent diagnosis system of chicken meat freshness using an electronic nose system. The acceptable obtained results of the present study indicate that the proposed applied system based on the electronic nose system and artificial neural networks methods as a smart and reliable method can online classification of chicken meat as fast, easy, economical, non-destructive and with appropriate accuracy.

The common methods that are usually used to identify the devoid rough rice from the healthy ones are often time-consuming and expensive. For this reason, in this research, a smart and fast method based on machine vision system coupled with artificial neural networks is presented in order to predict the percentage of devoid/healthy rough rice grains. Digital images of five varieties of paddy were prepared in three states: healthy, devoid, and mixed, in two states scattered and piled. After pre-processing and segmentation, 3 color features and 5 morphological features were extracted for each rice grain. Principal component analysis (PCA) method was then used in order to identify the most effective features in distinguishing devoid rough from healthy rice. In the next step, multilayer perceptron (MLP) algorithm based on the main components obtained by PCA method was used to create models for identifying and classifying the samples. Root Mean Square Error (RMSE), correlation coefficient (R2), specificity and sensitivity were used to evaluate the modeling capability and validation of each algorithm. The obtained results showed that the designed intelligent method can identify devoid rough rice seeds with acceptable accuracy in all cultivars (R2P>0.81, RMSEp<0.219, Sensitivity>0.8 & Specificity>0.98). Therefore, the machine vision system in combination with artificial neural networks can be used as an intelligent and fast method at the entrance of rice bleaching factories to evaluate the quality of harvested rough rice and predict the percentage of unhealthy rough rice.

Camelina oil is highly unsaturated and is a rich source of omega-3 fatty acids. Camelina oil contains high amounts of tocopherol which confers a reasonable shelf life without the need for special storage conditions. Generally crud oils contain many unwanted matters which must be removed to yield a stable product with a bland or pleasant taste. Chemical refining includes degumming, neutralization, bleaching and deodorization as separate process. In this study, the qualitative (FFA and PV) and compositional characteristics of camelina oil obtained from four regions of Ilam, Kermanshah, Hamedan and Fars were investigated after chemical refining operations. Changes in composional specifications were also evaluated before and after the final stage of refining, deodorization.Oils were extracted from camelina seeds from above region by soxhlet method, The extracted oils were refined. Fatty acid methyl ester (FAME), tocopherols FFA and PV were determined. Collected data was subjected to a one- way analysis of variance and Duncan's posthoc at the P<0.05.The most important fatty acid in terms of quantity in all samples was linolenic acid (LAn-3) and then omega- 6 linoleic acid.The trans acid isomers content, not detected more than 0.06% in any of the samples. Total tocopherol content in the camelina oil samples before deodorization were measured from 893.1-1122mg/kg and after deodorization ranged from 626.68-727.53mg/kg. Significantly loss in tocopherol content (total and individual) was observed after deodorization in all samples (p<0.05). The predominantly measured tocopherol isomer was gamma tocopherol. The present study concluded that the chemical refining of camelina oil has no significant effect on the optimal composition of its fatty acids and no trans isomers was formed. FFA and PV after deodorization were in the range of Iran national standard organization. The loss of tocopherol can be seen both in total and individual.

Melon (Cucumis melo L.) is one of the most important fruits that is consumed all over the world. The fresh cut fruit and vegetable industry is one of the relatively new and growing sectors of the fresh food products industry. Fresh-cut fruits, in addition to ease of consumption, bring benefits such as higher added value, reduction of waste and losses, increased product variety, improved security and quality, and less work in stores. Quality retention and shelf-life extension of fresh-cut fruits are crucial for industry because of their economic impact. Fresh-cut fruits and vegetables with high pH and water activity are considered to be highly perishable when they are not subjected to preservative processes and delay undesirable biological and biochemical changes. A recent approach to prolong the shelf life of fresh-cut fruit and vegetables is the use of edible coatings either alone or combined with modified atmosphere packaging. Numerous studies on improving the shelf life of fresh-cut fruits are extensive with the application of modified atmosphere packaging, and edible coatings and films. Chitosan, a polysaccharides-based edible coating, has been used individually or in combination with nanocomposite and other biological materials such as extracts or essential oils of various plants. On the other hand, edible films and coatings, due to their high ability to carry active compounds including antimicrobial compounds, can increase product shelf life and reduce the risk of pathogen growth on fresh-cut surfaces. Thymol (2-isopropyl-5-methylphenol) is a monoterpenoid phenol with the molecular formula C4H10O and isomer of carvacrol, which is slightly soluble in water with neutral pH, but is very soluble in alcohols and other organic solvents. MA packaging technology has been representatively used to maintain quality of fresh-cut products during preservation by carbon dioxide elevation and reduction in oxygen levels.

Melon fruit was harvested with full maturity at the right time. The outer surface of the fruit was disinfected with sodium hypochlorite solution (200 ppm) and cube slices with dimensions of 4x4x4 cm3 and an approximate weight of 9 g were prepared from it. To prepare the coating solution, 1 or 2 g of chitosan with 0.5 g of tween 80 was dissolved in 100 g of 1% acetic acid solution and thymol was added to the solution at 3 concentrations (zero, 0.25 and 0.5%). The final pH of the product was adjusted to 5.6 using NaOH 0.1 M. Then the solution was homogenized with a magnetic stirrer (1500 rpm) for 2 min. Fruit slices were immersed in each of the solutions separately for 2 min. After coating and removing excess solutions, the fruit slices were dried at room temperature for 8 min. Then, 30±2 g of treated and the control samples (uncoated) were weighed inside a polyethylene container and covered with a double-layer film (with a total thickness of 85 µm with an outer layer of polyethylene and an inner layer of polyamide) were packed in a modified or natural atmosphere. Atmosphere change was done using a MAP device equipped with a gas injection system. The levels of CO2, O2 and N2 inside the package immediately after sealing were 10, 5 and 85%, respectively. Freshcut packages were kept at 4±2°C for 8 days. All physicochemical (O2 and CO2 levels, weight loss, TSS. TA, ascorbic acid, color and firrmness) charactrestics were performed during storage time (immediately after harvesting, after 4 and 8 days). At the end of the storage time, microbial contamination (total count, mold and yeast count) and sensory characteristics were evaluted.

The results of analysis of variance showed a significant effect of the type of packaging atmosphere on the level of O2 and CO2 gases inside the packages (p<0.05). The results showed the CO2 and O2 levels, repectively increased and decreased inside the different fresh –cut melon packages during storage at 4ºC under natural and modified atmospheres. However, in the samples coated with chitosan and thymol, the intensity of O2 reduction and CO2 increase was less than the uncoated samples (control). This phenomenon is probably due to the gas blocking properties of the chitosan coating and the antimicrobial properties of thymol, which reduce oxygen consumption and carbon dioxide production by reducing the respration rate. At the end of 8 days of storage, the weight loss in the samples coated with chitosan and thymol and stored under modified atmosphere was much less than the control sample (0.34% compared to 13.60%). Chitosan coating and packaging under modified atmosphere provide relative semi-permeable barriers against oxygen, carbon dioxide and moisture, and as a result, weight loss is reduced by decreasing respration rate and moisture loss. Increasing the concentration of chitosan and packaging under modified atmosphere caused an increase in the amount of soluble solids, titratable acid, ascorbic acid, and firmness of the melon slices, but increasing the concentration of thymol had no significant effect on these quality characteristics. The color indices of green-redness (a*), blueyellowness (b*), brightness (L*) and browning index (BI) were also affected by the type of packaging and chitosan concentration. Evaluting the interaction effect of storage time with chitosan concentration showed that the amount of a* and b* indexes in the samples coated with 1% chitosan after 4 days of storage was not significantly different from the first sample. However, after 8 days of storage, these indexes decreased significantly. The interaction effect of chitosan and thymol concentration showed that melon slices treated with 1% chitosan with 0.25% or 0.5% thymol had the lowest microbial load. Coating with chitosan and thymol and the same type of packaging had a significant effect on all sensory attributes of melon slices (color, texture, smell, taste and overall acceptance) (P<0.05). Generally, the panelists preferred 1% chitosan over 2% in overall acceptanc.

The results showed that the physicochemical, sensory and microbial characteristics of fresh melon slices decrease during the storage period. Coating fresh-cut melons with chitosan and thymol due to its gas barrier and antimicrobial properties helped to preserve the quality and also prevent some undesirable changes. The integration of coating and packaging under modified atmosphere caused more maintaining the quality of fresh- cut melons. So that coating with chitosan 1% chitosan with thymol 0.5% and packed under modified atmosphere reduces microbial spoilage and preserves more qualitative features, color components and sensory attributes in fresh -cut melons.

Introductio: 

Active anti-microbial packages, metal nanocomposites are a new generation of packages with nano structure, which are produced by direct combination of metal nanoparticles with base resin. This research was conducted with the aim of investigating the physicochemical, antioxidant and antimicrobial properties of whey protein concentrate smart film containing pomegranate and red grape anthocyanins and zinc oxide nanoparticles.

permeability to water vapor, antioxidant properties, antimicrobial properties by disk diffusion method and differential scanning calorimeter test were performed on the prepared films. Agar diffusion method was used to determine the antimicrobial effects of the film.

By increasing the percentage of zinc oxide nanoparticles and anthocyanin in the film, the percentage of solids in the film increased. The antioxidant activity of active films increased significantly with the increase of anthocyanin content of the films. The highest antioxidant activity with a significant difference (p<0.05) was attributed to the film sample with 2.6 cc extract. According to the data obtained from the DSC test, with the addition of anthocyanins, the temperature of 290 and the glass transition have changed to some extent, and on the other hand, it can be concluded that the addition of nanoparticles to the film can reduce the glass transition temperature.

In general, this study showed that anthocyanins and zinc oxide nanoparticles have the potential to be used to prepare films based on bioactive whey concentrate with improved physicochemical properties and biological properties such as antioxidant properties when used in appropriate concentrations.