جستجوی مقالات مرتبط با کلیدواژه « pomegranate » در نشریات گروه « مکانیزاسیون کشاورزی »

Pomegranate fruit is one of the essential garden products in Iran, which, in addition to its high economic-commercial value, has many nutritional benefits. Due to the lack of appropriate development of the industry in the processing sector for this product, factories use completely traditional and limited methods for measuring the quality of pomegranate, which reduces the quality of the processed product. In the present study, the feasibility of visible and near-infrared (Vis/NIR) spectroscopy as non-destructive technology was used to determine the pomegranate fruit juice volume, which is one of the crucial quality attributes of the product. Spectral data of the samples obtained by applying waves in the range of 400 to 2500 nm, were evaluated by five methods including multiplicative scatter correlation, standard normal variate (SNV), vector normalization, first derivative, second derivative, as well as non-processed state. Then partial least square regression (PLSR) was used to estimate the juice volume. These processes were implemented according to machine learning algorithms using PYTHON 3.8 software. Lowest modeling error (18.61) was achieved with 36 principal components of extracted features from spectral signature. The results showed that this method estimated the amount of pomegranate juice with a coefficient of determination of 94 %, mean absolute error of 5.3 and distance of 0.98. This outcome resulted from combination of SNV preprocessing with PLSR regression in the range of 400 to 2500 nm. In spite of the effect of preprocessing for juice volume estimation, Vis-NIR spectroscopy possess desired condition for estimation of pomegranate juice volume.

Extended abstract Knowledge about the soil quality in agriculatral lands and natural resources is essential for achievement the best management and maximum economic efficiency. The land use change is the important human activity in environmental ecosystems, which effect on some soil processes such as microbial activity, mineralization of carbon and nitrogen content. In addition, land use has an important role on temporal and spatial variation of soil properties and quality. Agricultural practices may affect positive or negative effect on soil quality. Intensive cultivation of plants decreases soil physical and quality, as a result of this yield of plants, production efficiency and environment quality decrease. In this research, the effect of three land uses on soil physical, fertility and quality properties were studied. The studied area (Hossein abad) is located 30 km far from the northern Nehbandan town (South Khorasan, Iran).To study the effect of land uses change on soil properties were selected three land uses including pomegranate (Punica granatum ), olive (Olea europaea) and wheat (Triticum aestivum ). The 45 soil samples (15 samples from each land use) were taken from surface soil (0-30 cm). Then some soil physical and fertility properties which affect the soil quality were measured and the effect of land use change from wheat cultivation to olive and pomegranate gardens during the recent 20 years were studied. In addition, soil quality in each land use was determined based on cornel university test. To compare soil properties and quality, the randomized complete block design was applied. The results showed that land use change had a significant effect on organic carbon, mean weight diameter of aggregates (MWD), water stable aggregates (WSA), macro nutrients (N, P, and K), and some micro nutrients (Fe and Mn) (P < 0.001). Comparison of means demonstrated that the difference between organic carbon content in olive and pomegranate land uses was not significant, and the content of OC in both land uses was significantly higher than wheat land use. Olive and pomegranate land uses cause to stability of soil structure increase, probably due to reduction the traffic of wheals and also somewhat increasing the organic carbon as a result of littering. Therefore, the MWD in olive land use was significantly higher than two land uses and the lowest value was obtained in what land use. Also, the value of WSA in three land uses was significantly different (P < 0.05) and their content in olive and wheat land uses were the maximum and minimum, respectively. The concentration of total nitrogen in pomegranate land use was more significant than two other land uses (P < 0.05). But the concentration of phosphorous (P), potassium (K), Fe and Mn in wheat land use was the highest content and significantly greater than other two land uses. Despite the concentrations of P, K, and Fe nutrients in pomegranate land use were the lowest value, but, there were no significant difference between the concentration of them in olive and pomegranate land uses. It seems that this variation especially P and Fe is probably due to pH and the Ca and Mg concentration and creation insoluble component of Fe, Mn and P in these land uses.
According to the results of cornel university test, soil quality in garden land uses was decreased and the range of soil quality score was varied from 49.5 (olive) to 61.2 (wheat). Among the soil properties affecting the soil quality, fertility and chemical properties such as electrical conductivity (EC), absorption sodium ratio (SAR) and somewhat pH of soil saturated extract decreased the soil quality in olive land use. Also, OM, Fe, Zn, and Mn decreased the soil quality in 3 land uses, of course in olive and pomegranate land uses, micro nutrients (Fe and Mn) had the more effect on decreasing the soil quality compared to wheat land use. In addition, bulk density (Bd), mean weight diameter of aggregates (MWD), aeration porosity (AC), P, K, and Cu contents increased soil quality in all 3 land uses. In general, when wheat land use change to olive and pomegranate land uses decreased some soil properties and quality in arid area of Nehbandan, probably due to low quality of irrigation water.

IntroductionPomegranate (Punica grantum L.) is classified into the family of Punicaceae. One of the most influential factors in postharvest life and quality of horticultural products is temperature. In precooling, heat is reduced in fruit and vegetable after harvesting to prepare it quickly for transport and storage. Fikiin (1983), Dennis (1984) and Hass (1976) reported that cold air velocity is one of the effective factors in cooling vegetables and fruits. Determining the time-temperature profiles is an important step in cooling process of agricultural products. The objective of this study was the analysis of cooling rate in the center (arils) and outer layer (peel) of pomegranate and comparison of the two sections at different cold air velocities. These results are useful for designing and optimizing the precooling systems.
Materials and MethodsThe pomegranate variety was Rabab (thick peel) and the experiments were performed on arils (center) and peel (outer layer) of a pomegranate. The velocities of 0.5, 1 and 1.3 m s-1 were selected for testing. To perform the research, the cooling instrument was designed and built at Department of Biosystems Engineering of Tabriz University, Tabriz, Iran. In each experiment six pt100 temperature sensors was used in a single pomegranate. The cooling of pomegranate was continued until the central temperature reached to 10°C and then the instrument turned off. The average of air and product temperatures was 7.2 and 22.2°C, respectively. The following parameters were measured to analyze the process of precooling: a) Dimensionless temperature (θ), b) Cooling coefficient (C), c) Lag factor (J), d) Half-cooling time (H), e) Seven-eighths cooling time (S), f) Cooling heterogeneity, g) Fruit mass loss, h) Instantaneous cooling rate, and i) convective heat transfer coefficient.
Results and DiscussionAt any air velocity, with increasing the radius from center to outer layer, the lag factor decreased and cooling coefficient increased. Also, half-cooling time and seven-eighths cooling time reduced and so cooling rate enhanced. Thus, despite a reduction lag factor, due to a significant increase in cooling coefficient, half and seven-eighths cooling declined. Dimensionless temperature, θ, less than 0.2 and 0.1 in the center and peel and at different velocities had little impact on the rate of cooling in pomegranate. The difference in primary cooling time (0-500 sec) and in high lag factor (greater than 1) occurred, which represents an internal resistance of heat transfer in fruit against the airflow. Cooling the center of pomegranate starts with time delay which causes the beginning of the cooling curve becomes flat. Seven-eighths cooling time is the part of half-cooling time. The range of S was 2.5-3.5H in the present study. At first, cooling heterogeneity at 0.5 m s-1 was low in the center and peel of pomegranate and then with increasing the velocity up to 1 m s-1, it enhanced and again decreased at 1.3 m s-1. After a period of cooling (5000 sec), almost layers of pomegranate reached the same temperature and so heterogeneity reduced. The maximum instantaneous cooling rate was 8.09 × 10-4 ºC s-1 at 1.3 m s-1 in the center of pomegranate. By increasing the airflow velocity from 0.5 to 1.3 m s-1, the convective heat transfer coefficient increased from 11.05 to 17.51 W m-2 K-1. Therefore, the velocity of cold air is an important factor in variation of convective heat transfer coefficient.
ConclusionsCooling efficiency is evaluated based on rapid and uniformity of cooling. Cooling curves against time reduced exponentially at the different airflow velocities in the center (aril) and outer layer (peel) of pomegranate. By increasing the air flow velocity, half and seven-eighths cooling time reduced and cooling rate increased that showed direct impact of this variable. The main reason was the variation of convective heat transfer coefficient. The lowest level of uniformity obtained at the highest velocity (1.3 m s-1), which made more uniform temperature distribution in the fruit. The results showed that applied method in this experiment could be used for the fruits which are similar to sphere and could explain the unsteady heat transfer without complex calculations in the cooling process. Based on the results of this research, the airflow velocity of 1.3 m s-1 is recommended for forced air precooling operations of pomegranate.

Iran is a frontier of pomegranate fruit production in the world (with almost 40 % of the world`s production). However due to traditional processing operations is not ranked as the largest pomegranate exporter. Saveh, Neyriz and Ferdows are the top pomegranate producing cities in Iran. Pomegranate is consumed as a fresh fruit as well as processed product as food additive, paste, syrup, jelly, pectin, jam, beverage, essence, vinegar and concentrate. Aril extraction is the first and essential postharvest operation for pomegranate processing. Arils are mostly extracted manually even in large scales for fresh and processed consumption. This labor intensive operation is rational when aril quality is an important index for consumer. But whenever pomegranate juice is desired, the aril quality has no priority for consumer, and therefore arils can be extracted with less care. Sarig (1985) was the first inventor of a pomegranate aril extractor who employed air jet force to extract the arils. Later, other researchers employed the same method as well as water jet to extract fruit juice and sac. In the present study, fabrication and evaluation of vibratory aril extractor augmented with air system was conducted.
The study was conducted using Rabab cultivar samples which were manually harvested from an orchard in Neyriz town, Fars province. Samples were kept in refrigerator at 5 0C till experimental trials. Initial moisture content of fruit skin, arils and internal fleshes were measured by gravimetric method as 31.7±2.6 %, 61.5±1.8 % and 42.8±1.4 %, respectively and for a whole fruit was measured 45.3±11.5 % (w.b.). For conducting laboratory tests, an aril extraction unit was designed and fabricated. It comprised a steel main frame, a 746 W electric motor, drive mechanism (eccentric and shaft), sample retentive unit, air jet unit, aril tank, and an air compressor-tank assembly. Sample retentive unit was designed in such a manner to hold a halved fruit. This unit was made from four elements, a hemisphere bowel, four pressure (spring) arms to apply force on skin of the sample, and four tension (spring) arms for fixing the sample in the bowel by applying pressure on the edges of the halved sample. Such configuration helped sample to open more and more while extracting the arils to expose trapped aril for easier extraction. Sample retentive assembly was vibrated by the electric motor and drive mechanism. Electric motor was equipped with an electric convertor to create different levels of vibration frequency. Also, the drive mechanism was designed in such a manner to create different levels of vibration amplitudes. According to the previous studies, 2 nozzles with 3.5 mm diameter were selected for air jet unit. Nozzles were spaced at 8 cm apart according to the measured mean diameter of samples. Outlet air jet from nozzles covered the cross sectional area of the halved fruit. Nozzles assembly was rotated 180 degrees clockwise and counterclockwise with an electronically controlled stepper motor. Pressurized air (from air tank) was transferred to nozzles assembly by flexible pipes. Air pressure was controlled at 500 kPa level by air regulator. To conduct experimental trials, samples halved at three different cutting directions (horizontal (equatorial), vertical and oblique) by a sharp cutter and halved samples were used for tests. Halved sample was fixed in bowel and then the unit was excited by the electric motor. The assembly was vibrated for 60 seconds before blowing the air jet for extra 30 seconds. Tests for air jet alone were conducted for 90 seconds and percentage of detached and damaged arils were calculated. Damaged aril during cutting process was subtracted from total damaged arils for each trial. Collected data were analyzed according to factorial experiments based on completely randomized design, and means were compared by Duncan post-hoc test. Data of combined and air jet alone systems were analyzed by two independent sample t tests.
ANOVA results revealed that cutting type, frequency and amplitude, significantly influenced the percentage of aril extraction at 5 % level of significance. The highest amount of extraction was obtained at 30 Hz frequency and 4 mm amplitude for diagonal cutting by 87 %. At this condition, 13.9 % of arils were damaged by air jet pressure. A significant difference in percentage of extracted and damaged arils was observed between vibratory-air and air systems at 5 % level of significance. The highest amount of aril extraction as well as damage was observed for vibratory-air system with the means of 80.1 % and 9.9 %, respectively.
Maximum percentages of extraction and aril damage were achieved by applying the combined system with as compared to air jet system alone, so that combined system increased aril extraction by 7.1 % with 2.2 % extra damages.

The pomegranate journey from orchard to supermarket is very complex and pomegranates are subjected to the variety of static and dynamic loads that could result in this damage and bruise occurring. Bruise area and bruise volume are the most important parameters to evaluate fruit damage occurred in harvest and postharvest stages. The bruising is defined as damage to fruit flesh usually with no abrasion of the peel. The two different types of dynamic loading which can physically cause fruit bruising are impact and vibration. The impact and vibration loadings may occur during picking or sorting as the pomegranates are dropped into storage bins and during transportation. The focus of this work was on the impact loading as this appeared to be the most prevalent. In view of the limitations of conventional testing methods (ASTM D3332 Standard Test Methods for Mechanical Shock Fragility of Products), the method and procedure for determining dropping bruise boundary of fruit were also established by adapting free-fall dropping tests.
After the ‘Malas-e-Saveh’ pomegranates had been selected, they were numbered, and the weight and dimension of each sample were measured and recorded. Firmness in cheek region of each fruit was also measured. Fruit firmness was determined by measuring the maximum force during perforating the sample to a depth of 10 mm at a velocity of 100 mm min-1 with an 8 mm diameter cylindrical penetrometer mounted onto a STM-5 Universal Testing Machine (SANTAM, Design CO. LTD., England). Free-fall dropping tests with a series of drop heights (6, 7, 10, 15, 30 and 60 cm) were conducted on fresh ‘Malas-e-Saveh’ pomegranates. Three samples were used for each dropping height, and each sample was subjected to impact on two different positions. Before the test was started, it was necessary to control the sample's drop position. The cheek of sample was placed on the fruit holder. An aluminum plate mounted on upper part of the piezoelectric force sensor was the dropping impact surface of the device. After dropping impact, the sample was caught by hand to prevent a second impact due to sample rebound. After impact, the samples were stored at room temperature for 48h, during which time bruise tissues and arils turned brown. The bruise area and bruise volume of each sample were calculated according to equations (1 and 2).
Dropping impact acceleration versus time curves for the typical samples at ten drop heights are shown in figure 5. Drop height notably affected the impact acceleration. The peak force increased while contact times decreased with increasing drop height, which resulted in an increase of peak acceleration. Figure 6 shows the dropping impact velocity change during contact by theoretical calculation. The results showed that the velocities at the beginning of contact and the rebound velocities of the samples increased with increasing the drop height. Critical drop height of pomegranate in certain bruise area was determined and linear relationship between drop height and bruise volume for ‘Malas-e-Saveh’ pomegranates were obtained. It is clear that there were obvious differences between dropping bruise boundaries of pomegranates and the conventional damage boundary of products (as shown in figure 9). For the conventional damage boundary, the vertical line, critical velocity (Vc), represents the velocity change below which no damage occurs, regardless of the peak pulse acceleration. The horizontal line, critical acceleration (AC), represents the acceleration at which the product will be damaged if velocity exceeds VC. At the same time, for a conventional product, there is only one damage boundary at one shock condition. However, for fruit, a change in drop height (velocity) will lead to a change in bruise ratio. A series of bruise boundaries can be determined for different bruise ratios. Moreover, even if the velocity approaches zero, the fruit can still be bruised if its acceleration exceeds a certain value. These relationships provide an effective basis to predict and control drop bruising, which may be achieved through the design of reasonable cushioning packaging for fruit.
This research applied the concept of dropping bruise for pomegranate fruits. Because of the limitations in using conventional testing methods to test product of a viscoelastic nature, such as fruit, free fall dropping tests were adapted to determine dropping bruise fragility and bruise boundary for ‘Malas-e-Saveh’ pomegranates at different drop heights. For viscoelastic products such as fruit, even if the dropping impact velocity approached zero, the fruit could be bruised as long as the impact acceleration exceeded a certain value (critical acceleration). A series of bruise boundaries can be established for different levels of bruise ratios, i.e., a contour of constant bruise ratio can be drawn on the velocity acceleration plane.

Temperature management is an important subject in maintaining the quality of horticultural products after harvest. One of the methods in suitable control of temperature, is precooling, that is conducted before storing of the product which increases shelf life and storage time the fruits. On the other hand, estimation of cooling parameters (half and seven-eighths cooling times) need precise sensors and is time consuming in precooling operations. In this research, airflow velocities as an effective factor in cooling at three levels of 0.5, 1, and 1.3 m s-1 was considered. Parameters including lag factor, cooling coefficiency and half and seven-eighths cooling times were calculated based on recorded data of the temperature sensors. Finally, using the dimensionless numbers, Fourier and Reynolds, the estimation of regression models obtained for cooling times and compared with experimental data. With increasing airflow velocity, cooling times decreased and convective heat transfer coefficient was enhanced up to 58.46%. The overall results showed that for sphere shaped products like pomegranate, using Fo-Re correlation, cooling times are estimated with suitable precision (maximum error for half and seven-eighths cooling times 11.46 and 10.83, respectively) and without using complex equations.

Fast and accurate determination of geometrical properties of agricultural products has many applications in agricultural operations like planting, cultivating, harvesting and post-harvesting. Calculations related to storing, shipping and storage-coating materials as well as peeling time and surface-microbial concentrations are some applications of estimating product volume and surface area. Sphericity is also a parameter by which the shape differences between fruits, vegetables, grains and seeds can be quantified. This parameter is important in grading systems and inspecting rolling capability of agricultural products. Bayram presented a new dimensional method and equation to calculate the sphericity of certain shapesand some granular food materials (Bayram, 2005). Kumar and Mathew proposed atheoretically soundmethod for estimating the surface area of ellipsoidal food materials (Kumar and Mathew, 2003). Clayton et al. used non-linear regression models for calculation of apple surface area using the fruit mass or volume (Clayton et al., 1995). Humeida and Hobani predicted surface area and volume of pomegranates based on the weight and geometrical diametermean (Humeida and Hobani, 1993). Wang and Nguang designeda low cost sensor system to automatically compute the volume and surface area of axi-symmetricagricultural products such as eggs, lemons, limes and tamarillos (Wang and Nguang, 2007). The main objective of this study was to investigate the potential of Artificial Neural Network (ANN) technique as an alternative method to predict the volume, surface area and sphericity of pomegranates. The water displacement method (WDM) was used for measuring the actual volume of pomegranates. Also, the sphericity and surface area are computed by using analytical methods. In this study, the neural MLP models were designed based upon the three nominal diameters of pomegranatesas variable inputs, while the output model consisted of each of the three parameters including the volume, sphericity and surface area. Priorto any ANN training process, the data normalized over the range of [0, 1]. Fig. 1 shows a MLP with one hidden layer. In this study, back-propagation with declininglearning-rate factor (BDLRF) training algorithm was employed. The mean absolute percentage error (MAPE) and the coefficient of determinationof the linear regression line between the predicted values fromthe MLP model and the actual output were used to evaluate the performance of the model. The number of neurons in the hidden layerand also theoptimal values for the learning parameters η and αwere selected bytrial and error method. The bestresult was achieved with five neurons in the hidden layer. The results showed thatthe optimum modelof performance was obtained at constant momentum termequal to 0.8 and learning rate equal to 0.9. In this study, 300 epochs were selected as the starting points of the BDLRF. Some statistical characteristics of the actual values of volume were estimated by WDM, surface area was computed by equation (3) and sphericity of pomegranates was computed by equation (1) and the predicted values of them using the neural network method were shown in Table 1. The obtained results verified that the differences between theactual values and the estimated ones can be ignored. But, the predicted values of the volume using the MLP model in comparison with equation (2) are much closer to the actual values. Statistical comparisons of desired and predicted data and the corresponding p values are given in Table 2. The results showed that P-value was greater than 0.08 in all cases. Therefore, there was no significant difference between the statistical parameters. However, the P-value for equation 2 is much less than that of the MLP model. The results shown in Figures 2, 3 and 4 show that the coefficients of determination between actual and predicted data were greater than 0.9. Considering all the results in our study, the MLP model is more accurate than the WDM and analytical methods. In this paper, we first measure the actual volume of the pomegranate using WDM and equation (2). Also, assuming an elliptical fruit, the sphericity and surface area are computed analytically based on the three nominal diameters of a pomegranate. Finally, the results of achievements of the MLP designed revealed that the MLP model could be successfully applied to the prediction of thesphericity and surface area. Therefore, the MLP model can be a viable alternative to the analytical methods. However, this is possible only if there is a precise way to compute the three nominal diameters of pomegranates. In addition, according to the MAPE, the accuracy of the MLP model in prediction of volume of pomegranates was twicethe analytical method.

In this research, the effect of variety, harvesting time and fruit size were investigated on the mechanical properties of skin, density and mechanical strength. The results showed that pomegranate cultivars (Ardestani, Shisheh-Cap and Malas) had different skin thickness resulting difference in forces required for penetration of pomegranate fruit (10%). The skin of Shisheh-Cap variety was thicker than others. Mechanical strength of Shisheh-Cap and Ardestani varieties were 453 and 428 N respectively. The results revealed that Malas variety had the least strength against compression forces and it decreased (15%) with delay in harvesting of pomegranate fruit. It was shown that by increasing of fruit size, the density reduced (39%) and the mechanical strength increased (25%).

design equipment and facilities to dry, preserve and process pomegranates, it is To necessary to know their specific heat and thermal conductivity. The objectives of this study were to determine the specific heat and thermal conductivity of pomegranates and -The effects of moisture content (15 mathematical estimation models for them. develop 75% w.b.) and temperature (5-20°C) on the thermal properties of pomegranates (Alak variety) were studied. Specific heat was measured using the mixtures method. The thermal conductivity was measured using a line heat source probe for pomegranate exocarps and The results showed that an mesocarps and the bare-wire transient method for the seeds. increase in moisture content and temperature produced a linear increase in the specific 0.931 to 3.066 kJ/kg°C for mesocarps, and heat from 1.127 to 2.789 kJ/kg°C for seeds, 1.516 to 3.411 kJ/kg°C for exocarps. Thermal conductivity increased from 0.1524 to 0.4218 W/m°C for seeds, 0.148 to 0.451 W/m°C for mesocarps and 0.131 to 0.4204 W/m°C for exocarps as moisture content and temperature increased. However, the effect of moisture content was greater than the effect of temperature on specific heat and thermal conductivity. The empirical equations for these thermal properties were subsequently expressed as a function of moisture content and temperature.