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Finding natural, inexpensive and new polysaccharides resources is essential due to the high potential for utilization in the food and medicinal industries. Therefore, the current study was aimed to extraction optimization of polysaccharides from feijoa leaves in order to maximize extraction yield and, evaluate chemical, structural characteristics and antioxidant activity. In this regard, the effects of three independent parameters including extraction temperature (50-90°C), pH of water (3.5-5.5) and extraction time (1-4 h) on the extraction yield were studied. Optimum conditions were obtained at extraction temperature of 68°C, pH of 6.75 and extraction time of 2.96 h. Under optimum conditions, the predicted yield (3.38%) was consistent with the experimental yield (3.35±0.02%). The preliminary chemical characteristics of the polysaccharides extracted from the feijoa leaves were determined under optimum conditions. Based on the results obtained, total carbohydrate content was 54.77%, polyphenols and protein were 0.14 mg GAE and 0.18%, respectively. The FT-IR spectrum demonstrated obvious characteristic peaks of polysaccharides. Feijoa leave polysaccharides mainly consisted of glucose, ribose, mannose, arabinose and galactose. The results of antioxidant activity revealed the good ability of feijoa leave polysaccharides to scavenge DPPH free radicals and to reducing iron ions. Finally, the feijoa leave can be introduced as a natural, inexpensive and new resource for the extraction of polysaccharides with good biological activity for the production of functional foods or medicines.

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In the present study, the extract containing bioactive compounds from marigold (Calendula officinalis L.) medicinal plant was extracted using water, ethanol, acetone, ethanol/water and acetone/water as solvent. Among the solvents studied, the ethanolic extract contained the highest total phenolic compounds. The effect of the solvent to raw material ratio (40:1-10:1 mL/g) and particle size (0.5-2.36 mm) on the quantitative and qualitative properties of ethanolic extract at ambient temperature (25°C) were investigated. Based on the results, the highest crude extraction yield and total phenolic compounds equal to 3.5 ± 0.17% and 36.94 ± 0.81 mg GAE/gram of sample was obtained using a ratio of 30:1 mL/g and a particle size of 1 mm at ambient temperature. At the concentration of 1 mg/ml, the antioxidant activity of the extract was 62.95 ± 2.68 % and 153.18 ± 1.20 μΜ Fe²⁺/L, respectively. The high correlation coefficient (R²>09594) between total phenolic compounds and antioxidant activity indicates the key role of phenolic compounds in antioxidant activity. Finally, the ethanolic extract obtained from C. officinalis under mentioned conditions can be introduced as a natural source of phenolic antioxidants for application in the food and nutraceutical industry as a natural preservative.

 

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The aim of this research was to investigate the degradation kinetics of the major quality properties of medlar (Mespilus germanica) during cold storage. Medlar is a widely growth in northern Iran and its fruit is used as a nutritional component and as a medicinal remedy. In fruits, quality properties are used as a consumer-based criteria of acceptability. So it is important to evaluate parameters that affected the medlar quality. Measurement of these parameters is an expensive and time-consuming process. Therefore, parameter prediction due to affecting factors will be more useful. In the present research, mathematical models and artificial neural networks (ANN) were used for modelling the relationship between physicochemical properties and color attributes with cold storage time. Five kinetic models viz. zero order, first order, Second order, fractional conversion and Weibull models were used for modelling using MATLAB. Among the kinetics models, the Weibull model was found to be more suitable to predict the changes in all physicochemical ( , ) and color ( , ) parameters. In ANN, multi-layer perception (MLP) used with different number of neurons. The network’s inputs include storage time, medlar moisture content and ripening stage and the network’s output were the values of the physicochemical and color properties. The training rule was Momentum Levenberg-Marquardt. The transfer functions were Tansig, Purelin and Logsig. The results showed that MLP network with Levenberg-Marquardt training function, Purelin transfer function and 3-8-4-3 and 3-7-2 topologies had the best accuracy for prediction of for physicochemical and color properties. This network can predict physicochemical and color properties of the medlar with  coefficient of 0.9983 and 0.9992 and MSE of 0.021, 0.000008 and 0.000059 respectively.

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It is important to control the ripening stages of agricultural products during storage and their quality grading based on their ripening stage. Edible coatings can prolong the storage life of agricultural products and protect them through the handling, storage, processing and marketing. The purpose of the current study was to develop an artificial vision system for quality control and segregation of cherry tomatoes in two different conditions including with and without Aloe vera gel coating. For this purpose, physicochemical properties including titrable acidity, total soluble solids and firmness of cherry tomatoes were measured in both conditions. Based on these properties, the ripening index (RPI) was determined and the samples were classified to MS1 and MS2 according to the ripening stage. Subsequently, the samples were classified using color features, color texture features separately and their combination through principal component analysis (PCA) and back propagation neural network (BPNN). Classification results showed that the use of color and color texture features combination made the classification more accurate; PCA and BPNN methods were able to segregate the samples with high accuracy (85.72 and 98.21, respectively) using the 21 color and color texture features. The higher accuracy of the BPNN method is due to its nonlinear performance. The results of this study indicate that Aloe vera gel is promising in delaying the ripening process of cherry tomatoes and artificial vision system can be used as a non-destructive method for evaluation of cherry tomato ripening level based on the color and color texture features.

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In this study, the effects of Farsi gum (0, 1.5% and 3%) coating containing hemp seed oil (0, 0.075% and 0.15%) on mass and volume changes of grape were investigated during storage at 4°C for 28 days. Machine vision system with learning machine methods was used to detect coated grapes from an image and estimate their mass and volume based on the image features (length, width, height and area). Four machine learning models, including linear regression (LR), artificial neural networks (ANN), radial basis function support vector regression (RBF-SVR) and Linear basis function support vector regression (LBF-SVR) were developed to predict the mass and volume of the single grape. The estimated grape mass and volume by these methods was compared statistically with actual values. The mass and volume in all treatments showed a decreasing pattern during the cold storage. The results indicated that mass and volume change decrease with Farsi gum and hemp seed oil increasing. Furthermore, according to the model evaluation results, the prediction performance of RBF-SVR model had achieved better predictive accuracy compared with the results of LR, ANN and LBF-SVR models, with R2 of 0.998 and 0.989 for mass and volume estimation, respectively, which also showed a good agreement between actual and predicted values. These results revealed that SVR model was a promising tool for estimating the mass and volume of grape during storage.

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In the present study, in the first step, the effect of Aloe vera gel (75% v/v) coating containing different concentrations of hemp seed oil (1-5% v/v) on some physicochemical properties of cherry tomatoes during storage at room temperature was investigated. The results revealed the ability of hemp seed oil to improve the physicochemical properties of cherry tomatoes during storage, although no significant difference was observed between 3 and 5% levels of hemp seed oil (p> 0.05). Slope change in the ripening index trend occurred for A. vera gel (75% v/v) coated sample on day 12 and for A. vera gel containing 3% hemp seed oil coated sample on day 16. Using an image processing system, the changes of the coated samples were evaluated based on the color statistical and color texture features extracted from the images and were graded through different procedures. The results showed that the principal component analysis (PCA) and artificial neural network (ANN) methods were able to divide the cherry tomatoes into intact and blemished grades which the ANN method was graded samples using color texture features with higher accuracy (97.41%). The adaptive neuro-fuzzy inference system (ANFIS) method had higher diagnostic power than the other two methods and was able to grade the samples into three grades including intact, grade 2 and unusable with accuracy of 98.96%.

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Drying is one of the most common and effective techniques for maintaining the quantitative and qualitative characteristics of medicinal plants in the postharvest stage. Thus, in the current study, the effect of different drying methods including shade drying (SD), hot air (HAD; 40 and 60 ºC) and freeze drying (FD) on the extraction yield, chemical compositions, total phenolic and flavonoid content and antioxidant activity of essential oil from aerial parts of Ferulago angulata was investigated. The results revealed that the drying method has a significant effect on the studied properties. The lowest (0.89%v/w) and the highest essential oil extraction yield (2.5%v/w) were obtained for SD and FD aerial parts of F. angulata, respectively. The identified chemical compounds using gas chromatography-mass spectrometry represented 74.74-96.97% of the essential oil. Cyclofenchene (15.02-21.65%), Trans-ß-Ocimene (14.90-20.10%), O-Cymene (4.48-8.88%), Bornyl acetate (4.57-7.94%), ß-Myrcene (2.84-3.75%), ɣ-Terpinene (2.77-4.61%), Trans-Verbenol (2.15-3.29%), Limonene (2.15-2.92%),  β-Pinene (1.55-2.58%) and Germacra-D (1.38-3.46%) were the main chemical constituents of the SD, HAD and FD aerial parts of F. angulata essential oil. FD preserves the maximum chemical constituents and increasing temperature in HAD reduces the amount of chemical constituents of the essential oil. Total phenolic content of essential oil from FD (188 ± 0.23 mg GAE/g), HAD 40°C (185± 0.31 mg GAE/g), HAD 60ºC (169.56 ±0.26 mg GAE/g) and SD (167.03± 0.19 mg GAE/g) were almost more than twice the total flavonoid content. The highest scavenging activity of DPPH· and ABTS^· based on IC₅₀ were obtained for FD sample and were equal to 5.614±0.25 and 3.368±0.62 mg/mL, respectively. In addition, the FRAP of essential oil from FD aerial parts of F. angulata was obtained in the range of 5.923-11.074 mM FeSO₄.7H₂0. Finally, it can be concluded that FD could be a suitable method for drying aerial parts of F. angulata.

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Cherry tomato as a climacteric product has a short postharvest life and so it is necessary to use methods such as coating to increase its shelf life. Therefore, the aim of the current study was to investigate the effect of fresh Aloe vera gel edible coating concentration (25, 50, 75 and 100% v/v) and storage temperature (5, 12 and 25 °C) on postharvest quality characteristics of cherry tomatoes such as weight loss, titratable acidity, total soluble solids and sensorial properties stored for 24 days and also to study the kinetics of their changes. During the storage period, the weight loss, total soluble solids of all samples increased and the titratable acidity decreased. The use of A. vera gel considerably controlled the quality characteristics changes while the increase in temperature intensified the changes in the studied characteristics. In addition, the use of A. vera gel and low storage temperature reduced the incidence of decay and increased the score of sensory properties. Kinetic studies showed that the changes in weight loss and total soluble solids followed the first-order model and the titratable acidity followed the fractional conversion model. The constant rate of postharvest characteristics changes under different conditions followed Arrhenius equation. Based on the findings of the current study, it seems that applying fresh A. vera gel with 75% concentration and storage temperature of 5 °C improves the postharvest qualitative and sensorial characteristics of cherry tomatoes during 24 days of storage.

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In the current study, a simple image processing method based on a RGB images using machine vision system has been designed to evaluate the color and texture features of low-calorie doughnut crumb. The effect of maltodextrin substitution with margarine at the levels of 25, 50, 75 and 100% (w/w) was evaluated on vision properties. These features were crumb color (L*, a* and b*), pore area fraction, number of cells/cm², pore shape, Euler number, fractal dimension of pore boundaries and crumb texture (contrast, entropy, correlation, energy and homogeneity). Results revealed that the addition of maltodextrin increased L* value and decrease a* value of crumb color significantly. The contrast, entropy and Euler number of doughnut crumb containing 75 and 100% maltodextrin were considerably higher than control, 25% and 50% samples. Correlation, energy, homogeneity, mean pore area and diameter, number of cells per square centimeter and pore area fraction decreased after maltodextrin addition (75 or 100%) but no significant difference observed between control, 25% and 50% samples. The fractal dimension value of pore boundaries in doughnut containing 100% maltodextrin were the highest which indicates that the addition of maltodextrin caused more irregular and tortuosity porous boundaries.

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Proteins are one of the most important food constituents due to their unique functional properties and health benefits. Among plant proteins, fenugreek seed protein is of great interest due to its high content of essential amino acids. The current study was carried out to optimize ultrasound-assisted extraction of fenugreek seed protein and evaluation of its functional, structural and antioxidant properties. The optimal conditions for protein extraction were ultrasonic power of 80 W and sonication time of 28.39 min which under these conditions, the predicted extraction yield was 8.65% which was in good agreement with the experimental value (8.57%). Amide A, amides type I, II, and III bands were observed in Fourier transform infrared spectrum. The solubility was pH-dependent. The water and oil absorption capacity was 6.24 and 2.72 mL/g, respectively. The lowest (44.66%) and highest (92.49%) foaming capacities were observed at pH 4.5 and 10, respectively. The highest emulsifying capacity (84.53%) was observed at pH 10, while the lowest (54.82%) was at isoelectric point. At the constant pH, the foam and emulsion stability decreased over time. The results revealed that ultrasound can be applied effectively to reduce the time of protein extraction process from fenugreek seeds. In addition, the fenugreek seeds extracted by using ultrasound have desirable functional and antioxidant properties that make it feasible for utilization in the food industry.

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In the current study, ultrasound-assisted extraction of bioactive compounds from Cucurbita seeds was performed using ultrasound amplitude of 50%, temperature of 57 °C and 54 min sonication time. The major phenolic compounds were determined using high-performance liquid chromatography. The effect of bioactive compounds on the oxidative stability of ground mutton beef at refrigerated temperature was evaluated. The values of pH, peroxide value (PV), thiobarbituric acid reactive substances (TBARS), and sensorial evaluation were performed during storage of samples considering 5-day intervals. According to the results, coumaric acid, syringic acid, ferulic acid, caffeic acid, and protocatechuic acid were detected in the bioactive compounds extracted while coumaric acid (14.36 ± 0.17 mg/g) showed the highest content among the others. The highest value of PV was determined in the negative control, while the lower values were observed in the samples treated with natural and then synthetic bioactive compounds during 15 days of storage at 4 °C. According to the results from sensorial analysis, the improved characteristics of color, odor, and total acceptance was observed in the treated samples with the bioactive compounds obtained from Cucurbita seeds.
 

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In the current study, the effect of different new extraction methods including supercritical carbon dioxide extraction (SC-CO₂), microwave-assisted extraction (MAE) and also conventional Soxhlet extraction (CSE) were investigated on bioactive compounds recovery from Silybum marianum seed. The crude extraction yield (22.40± 0.15%) was obtained using CSE, while the efficiency of SC-CO₂ and MAE were about 89 and 50% of those obtained using CSE. The highest free radical scavenging activity in terms of DPPH and HO radicals was obtained in extract obtained using SC-CO₂. From the TPC analysis, the highest and lowest value was determined in extracts obtained using SC-CO₂ (102.93± 0.14 mg GAE/g) and CSE (14.50± 0.18 mg GAE/g), respectively. Fatty acid composition was analyzed using Gas Chromatography–Mass Spectrometry. Linoleic and oleic acids were determined as the main fatty acids. Finally, it can be concluded that S. marianum seed is a potential source of bioactive compounds and new extraction techniques of SC-CO₂ and MAE could be suggested as promising methods to substitute conventional method for successful recovery of bioactive compounds.